Making of RIL/Tata/Adani Super App

Tatas, Adani, Ambanis in scramble for super app

  • The groups plan to take on well-entrenched players like Amazon, Flipkart, and Paytm by merging their offline businesses with e-commerce initiatives.
  • India’s top business groups, such as Tata, Adani, and Reliance Industries, are scouting for acquisition targets to offer additional goods and services under their “super app” umbrella.
  • The conglomerates are planning to offer personal loans, travel bookings, and movie tickets to create a consolidated digital platform that will support their existing offline businesses, say bankers.
  • Tata, Adani, and RIL have millions of customers across their verticals. The super app will just bring them under one umbrella and help cross-sell products. They are looking for those digital companies that are not in their current portfolio and offer a ready customer base.
  • The Adani group is the latest to join the bandwagon by acquiring a minority stake in travel portal, Cleartrip, from Walmart-backed Flipkart group. Like Tata and RIL, the Adani super app will support its offline businesses. The group had in September acquired a 10 per cent stake in CSC Grameen eStore, a rural-focused grocery store, to offer its range of food products, including Fortune oil, to rural customers, say bankers. The group aims to add 1 billion customers to its digital platform by 2030.
  • The Tata group, which recently bought several e-commerce companies, is also on the prowl. Tata Digital, which plans to launch TataNeu super app, will offer all goods and services from the Tata group companies, including airline and hotel bookings. The recently acquired e-commerce companies by the group, including BigBasket and pharmaceutical product delivery firm 1MG, have been integrated into the super app.
  • The Tata group employees have been currently given access to the super app to check for any last-minute issues.
  • Tata Capital, which has a significant retail and corporate loan portfolio, is also expected to chip in by offering loans to its super app customers.
  • Mukesh Ambani-owned RIL is investing heavily in building its super app ecosystem and will offer services from movie ticket bookings to travel tickets. It is also planning to integrate the database from its latest acquisition, JustDial, to help customers connect with small businesses around them.
  • Analysts are forecasting a 50 per cent market share for RIL in the online grocery market by the financial year 2024-25, with a 30 per cent market share in overall e-commerce.
  • This translates into $35 billion e-commerce GMV (gross merchant value) for RIL by FY25, with $19 billion in grocery and rest by non-grocery. Overall, we expect retail Ebitda (earnings before interest, tax, depreciation and amortisation) to grow 10 times from current levels by FY30.
  • The new entrants would make a dent in the market share of Paytm, Amazon, and Flipkart that are offering a range of services to their customers, including payment gateways and air ticket bookings. Paytm is currently the leading payments platform in India with a gross merchant value (GMV) of Rs 4.03 trillion as of March 2021. But with cash-rich conglomerates entering the market, it will be interesting to watch how the current players retain their market share.
  • What is a Super App and how to build one ?

70 Percent of Value in Tech is Driven by Network Effects

  • The Big 5 — Apple, Google, Microsoft, Facebook and Amazon — are hitting all-time high valuations. Airbnb is worth more than Hilton in the private market. Uber is worth more than GM. Spotify and Dropbox IPOed in 2018, with Slack and Didi Chuxing on an IPO track.
  • It’s fitting they should all be mentioned in the same breath, because other than Amazon, their business DNA is amazingly similar.
  • They are all network effect businesses. And it turns out that most of the outsized returns of companies since 1994 have used network effects.
  • If you know the playbook, you shouldn’t be shocked at these companies’ rapid growth. But it’s surprising how few people know the network effects playbook. Many still confuse it with viral effects. Many know it’s important, but don’t know what it means.
  • You might wonder what the secret sauce of these tech companies’ rapid growth and high valuation is. The simple answer to that is Network Effect. A network effect is when another user makes the service more valuable for every other user. In traditional market, more customers would drive more units produced. That would spread fixed cost across units and lower average cost per unit. While, in digital market, more units consumed would create more value to the network and would increase value per unit. That’s why network effect is also known as the demand-side economies of scale.

Definition — A product displays network effects when more usage of the product by any user increases the product’s value for other users (and sometimes all users).

  • Once a company achieves a network effect, users won’t find much value in competitors’ smaller networks, which makes any business hard to catch and an existing player would achieve economic moat.
  • Similar to positive network effect, there is also a negative network effect. A negative network effect occurs when welfare decreases with the addition of more users. i.e. network congestion, lock-in or switching cost and conflicts of interest.

Types of Network Effects

There are different types of network effects and their behaviors are different.

“Not all network effects are created equal — some are stronger and tend to produce more value than others.”

There are various ways to classify network effects. At a high-level, there are five major types of network effects.

1. Direct Network Effect

The strongest and simplest network effects are direct: increased usage of a product leads to a direct increase in the value of that product to its users.

LinkedIn, WhatsApp and Facebook demonstrate this type of network effect. Once you have friends on Facebook or WhatsApp, you wouldn’t join other services. A new entrant has to achieve significant network effect in order to create values for users.

2. Two-sided Network Effect

The real distinguishing characteristic of a 2-sided network is that there are two different classes of users: supply-side and demand-side users. They each come to the network for different reasons, and they produce complementary value for the other side.

Marketplace and platform are two-sided network effect. This type of network effect is seen in Airbnb and Uber. When more drivers join Uber, it creates value for riders by reducing wait time for riders. Thus, more riders join Uber and rider demand creates value for drivers.

3. Data Network Effect

When a product’s value increases with more data, and when additional usage of that product yields data, then you have a Data Network Effect. If data is really central to the way the product benefits users, then the data network effects of that product has the potential to be very powerful.

Examples for this type of network effects are Waze and Google Maps. Waze users consumes data as well as contributes useful data to the network. Users’ data contribute to determine traffic and Waze provides optimal route to the users. So, if network is larger, Waze can provide more accurate data on traffic to the users.

4. Tech Performance Network Effect

When the technical performance of a product directly improves with increased numbers of users, it has Tech Performance nfx. For networks with Tech Performance network effect, the more devices or users on a network, the better the underlying technology works. This makes the product faster, cheaper or easier.

Every person downloading a file from BitTorrent is also seeding files to the network. So, the services get faster for all users as more nodes are on the network.

5. Social Network Effect

Social network effect work through psychology and the interactions between people. There is an unseen network among people, where our physical bodies are the nodes, and our words and behaviors with each other are the connections.

Social network effect can add value to people in three different ways:

  • Language — brand name that people will verbalize (Uber, Google).
  • Belief — the more people believe in value of something, the more valuable it gets in reality (Bitcoin).
  • Bandwagon — when social pressure to join a network causes people to feel they don’t want to be left out (Slack, Apple).

Why Network Effects are Important

In digital world, there are four ways to create defensibility:

  • Supply-Side Economies of Scale,
  • Brand,
  • Embedding and
  • Network effects. Network effects is the most important way to achieve defensibility. Companies with the strongest types of network effects built into their business model can achieve scalable growth and win big.
  • Network effects is one of the most important strategies to achieve organic growth. Companies can grow from paid acquisition, but customer acquisition cost (CAC) would be too high and as markets saturate, CAC would rise and make it difficult to achieve profitability in long run. However, this is not true with network effects. As networks grow, all participants benefit and create value for other users which attract more users to use product. Thus, CAC remains constant or decreases over time and helps business grow organically.
  • For example, Dropbox employed paid campaigns to acquire new customers during its initial days. Due to this, customer acquisition cost (CAC) was very high ~$300, compared to yearly revenue ~ $120 (~ $10/month). Clearly, it wasn’t sustainable for Dropbox to achieve organic growth with this model. Dropbox employed growth hacking tactic such as double referral program to boost user base. Once users started using Dropbox and shared a folder with other people to collaborate, it created a link that other people could use. This created an eco-system where new users started using the service because their friends shared a file with them. Furthermore, it led to a barrier to switch to a different file-sharing system and helped Dropbox to acquire new customers. Thus, an existing users hooked new users to use Dropbox. In other words, Dropbox achieved network effect which helped them to achieve growth and reduce CAC.

How Network Effect Works

  • Network effect becomes significant after only when certain number of users are using the product. This certain number is called critical mass. The challenge lies in getting users to join in before the critical mass is achieved. In order to achieve critical mass, companies could offer services for free for a limited time and adopt various growth hacking tactics, such as referral bonus (as mentioned earlier in Dropbox’s case), request a friend to sign up or subsidizing fees for service.
  • Once this critical mass has been achieved, the value obtained from the product or service is greater than or equal to the cost for the product or service. As the value increases by the number of users of a product, more users would want to subscribe/purchase the product, and hence more users would be added to that product, which would further increase value of product and make more people to join it.
  • The above graph, depicts concept of network effects. It shows that once product achieves network effects, value Increases exponentially while cost increases linearly. The cost of maintaining the network does not grow as fast as the value of the network. The value increases as the size of the network increases. In the long run, it’ll be difficult for competitors to enter in the market as existing players would have more valuable network. So, there will tend to be fewer players, and they will continue to grow larger.
  • For example, one of the most valuable aspects of the Spotify platform is music discovery. Listeners want to explore different genres of music and listen music beyond top playlists, while artists/record labels want their music to be reached to more customers.
  • As more record labels/artists join Spotify, more users tend to join Spotify due to more music choices available on the platform, which in turn attracts more artists/record labels and collectively increases value of Spotify’s network. Also, Spotify users can see their friends’ playlist and recent activity. So, once you have more friends on Spotify, it creates stickiness of the product. The platform therefore ultimately becomes more valuable to users as more users join. Spotify curates and creates its own playlists, but much of the value comes from other users’ tastes. As more music listeners, bloggers, organizations get on Spotify, the more valuable it becomes to a listener as they have more curated music. Simultaneously, the more users on Spotify, the better it is for artists (increased streaming royalties and exposure).
  • The more playlists, the more users, the better the music — discovery. Once Spotify has more users and artist on its network, in other words network effect is achieved, it’s really difficult for users and playlist to switch to other service.
  • Considering network effects as a foundation, RIL JIO explores different types of network effects and various business models enabled by them to create never before realized valuations.

The Study

  • We wanted to put an actual number on the amount of value network effects have created in the digital world.
  • The short answer: over the past 23 years, network effects have accounted for approximately 70% of the value creation in tech.
  • We did a study of the digital companies that were founded since the Internet was widely available in 1994 and that went on to become worth more than a $1 billion.
  • 336 companies between 1994 and 2019 met this criteria.
  • By looking at each of the companies’ business models and comparing them to our list of 13 known network effects, we estimate 35 percent of those companies had network effects at their core. They were, however, typically much more valuable than companies without network effects so they added up to 68% of the total value in our spreadsheet.
  • In other words, companies that leverage network effects have asymmetric upside. They punch above their weight. They are the Davids that beat the Goliaths, and then become the Goliaths.
  • The other 65% of $1B+ companies used other defensibilities to create their value — namely embedding, scale and brand. These are good approaches, and created 219 $1B+ companies. 65% of the total. But those companies’ valuations typically top out in the $1-$2B range, leading to the results of this study.

The Single Most Important Predictor of Tech Value

  • It turns out that having a network effect is the single most predictable attribute of the highest value technology companies — other than perhaps “having a great CEO.”
  • And yet surprisingly, only 20 percent of the business plans we came across had network effects in them.
  • We believe that most founders fail to design network effects into their businesses because they don’t understand them well enough. And not understanding them, they don’t build them in from the beginning.
  • It’s sad to watch, because just as the Big Five are now consolidating their dominant threat to startups, and just as startups have lost the favorable winds of the Internet and mobile tech shifts, most founders are missing a key ingredient they will need to have a dog in the fight.
  • Unless founders wise up to the importance and discipline of network effects, the scales will be heavily tipped in favor of those who have.
  • If Your Startup Doesn’t Have Network Effects, You Need to Rethink Your Strategy.
  • There still remains a huge gap between how little is written and known about network effects and how massive of an impact they have on value creation (to say nothing of their impacts on society and the future of our economics and politics, but that’s a different discussion).

Network Effects and the Next Big Thing

  • Some have asked, “The top companies of 2019 have network effects, but many of those companies were founded 5–20 years ago…will the power of network effects continue with new startups?”
  • Unequivocally, yes.
  • In fact, network effects will increase in importance because the new platforms — and the re-invented verticals — are being born networked:

– Crypto-Assets
– Synthetic
– Biology
– Augmented Reality
– Artificial Intelligence
– Virtual Reality
– Internet of Things
– Robotics
– Drones
– Transportation
– Smart Cities
– Agriculture
– Health Care
– FinTech

  • Understanding the principles of network effects and applying them to new companies today should produce the same or greater defensibility and value-creation advantages that we saw in post-1994 companies, particularly because there are now over 3B people networked to the Internet. If we have to design an AI company with or without network effects, we’ll take the one with network effects every time.

Learn the Network Effects Playbooks

  • When you’re creating your digital business, architect your product to allow users to participate in value creation. Let their use of the product add value to the other users. Let customer 2 add value to customer 1. This makes the company defensible because competitors have a hard time adding as much value to users once you get ahead, and defensibility creates value.
  • If history tells us anything, the next SnapChat, Airbnb, and Uber will be created in the next twenty-four months. While the next billion dollar startup won’t look just like those companies on the outside, it’s a good bet that they will have network effects on the inside.

The Rise of the 4th Platform: Pervasive Community, Data, Devices, and Intelligence

  • These days it’s still pretty common to talk about social business, mobility, analytics (especially when it’s called big data), cloud, and the Internet of Things — SMACT is the current acronym for all this — as on the agenda of key digital improvements underway in the typical enterprise.
  • While many organizations have executed solid starts against these fronts, and are usually just at the end of the beginning overall in incorporating these technologies into their business, the majority still have a good way to go away.
  • What’s coming next in digital and the enterprise. While examining the more strategic up-and-coming technologies for the last year, this doesn’t really begin to paint the strategic picture that organizations must manage to now.
  • After all, a laundry list of technologies is just that, and won’t create results by itself. But carefully situating emerging technologies within a business in a way that truly takes advantage of their innate and unique abilities to realize value creation does, and is the essential description of the hot topic today among CIOs and others in the C-Suite, digital transformation.
  • After all, the whole point of digital transformation is realizing that technology fundamentally changes how you do business in just about every way. It therefore poses very difficult questions to business and technology leaders: Who best should do our work today? Where does the value come from? What do these new ways of working actually look like? How can we best organize to achieve them? To answer these questions, we must understand the overall narrative of our modern digital journey: Where is technology actually taking us? What is it making possible that wasn’t before? How can these possibilities give rise to uniquely valuable new types of assets that would allow us to sustain our businesses?
  • These are a lot of open questions, but we do have a sense of some of the answers now. For example, in terms of who does the work and where value comes from, we’ve learned that the network can and will (and should) do most of it, if we only enable the possibilities through platforms and digital communities. The answers to other questions are more complex, though their broad outlines are becoming clear as well, such as how can we best organize this year to achieve digital change. Why are they tough questions? Because while digital devices and networks enable broad and reasonably well-understood realms of possibility, how precisely they apply to our industry, our business, and our corporate culture is often very different between organizations.
  • So when we talk about framing up the overall digital journey we are all on, the discussion is often about “computing eras”, or the emerging of new types of platforms (the cloud, for instance.) while these views are often gross simplifications, these are also useful conceptual frame-ups. Probably one of the most widely referenced view these days is IDC’s articulation of a vision they’ve dubbed the 3rd platform. In the large, this view does indeed describe what’s happening, though it leaves out some of the unique flavor of what’s special about what’s happening in digital today. We’ve previously described some of the more detailed possibilities in a view called Web OS, but this really never became a popular way of thinking about it, though it did provide the extra layer of detail many need to understand what’s happening and has held up well in my opinion.

What’s Missing, and What’s Coming for Today’s Strategic Digital Perspectives?

  • Probably the most important concept that’s almost always missing from these views is the unique power of networks, especially ones made of people. One of the more remarkable is the sheer number of connections between nodes on the network that are potentially possible. Old ways of thinking about digital created largely point-to-point connections. The advent of social media made potent many-to-many network effects possible. The key word here is possible. Just because we’re connected to just about everyone in the developed world 24 hours today, doesn’t mean we actually realize that possibility. But today’s global networked platforms gives rise to the potential. In fact, for many reasons, having the ability to tap live into one’s social network is often better than having data on-hand, which is likely to be out-of-date.
  • So, for example, our view of what’s coming next, we don’t track the amount of data that is accumulating today. That is a great deal and growing rapidly by every account. But data isn’t useful until it’s needed, instead the ability to produce whatever is needed, when it is in fact needed, has far more ultimate value. So in our view, it’s key to understanding the strategic business nature of digital networks. This is a key point that summarizes excellent Power of Platforms series:
But in a world of mounting performance pressure, we should also expect a fourth form of platform to become prominent. Dynamic and demanding environments favor those who are able to learn best and fastest. Business leaders who understand this will likely increasingly seek out platforms that not only make work lighter for their participants, but also grow their knowledge, accelerate performance improvement, and hone their capabilities in the process.
  • The core concept here is that whoever learns fastest, wins, and those with the best platform and ecosystem around it, will have value that can be tapped into more rapidly for sustained strategic benefit. Plus, it will ensure coverage of virtually all of the top level types of collaboration in business today.

What’s Next: Networks/Sensors In Everything, Machine Learning, and Us

  • Just about every non-trivial object will be connected to our networks within 10 years, as part of the rapidly emerging Internet of Things revolution. With the introduction of low power protocols like Bluetooth 4 and ultra long-lived batteries in devices like the tiny — and terrific in experience — Tile locator, we now believe it’s going to be more like five years.
  • It’s also clear that mobility is going to transform and essentially disappear, into us. Wearables and smartphones will very quickly quaint when everything we need can be beamed into our heads or embedded as needed. Computing devices will almost completely disappear into our personal and work objects, and even ourselves. While this is certainly as scary a topic as the loss of privacy on the Internet was to many of us a decade ago, it’s clear that our computing devices are going to vanish and melt into the backdrop, like any sufficient mature technology. In fact, almost every technology eventually becomes naturalized. This will be the case with the end-state of digital experiences as direct man/machine interfaces, which have long been in the lab and is becoming increasingly sophisticated en route to the market.
  • Thus it won’t be long from now — as strange as it may seem today — that we can turn on the lights in our office just by thinking about it or order a product from Amazon after having an algorithm sift through the reviews for us simply by conceiving of doing so. We will reach a state of shared perception through all of our mutually connected devices and having knowledge networks consisting of our social graph, all devices, and the machine learning capabilities we trust most. In other words, collaboration with people and our machines will soon be truly frictionless.

The Fourth Platform: Ambient, Pervasive, AI-Boosted Digital Networks

  • All of this together: Networks of people in digital communities, pervasive sensors/controllers in nearly everything, and new types of truly frictionless interfaces will give rise to new types of ecosystems, including on-demand app creation services such as the now-famous IFTTT service.
  • The 3rd platforms enabled enormous commercial ecosystems such as those created by Google (especially their decentralized AdWords network), Facebook, Amazon’s Cloud, Apple’s phones, iTunes and App Stores, and the list goes on. In the 4th platform, these platforms will become even more important — rightly or wrongly — and the most useful ones to us will literally become part of our mental furniture.
  • The fourth platform is ambient computing, which strong components that turn network potential from our favorite ecosystems into data, and then data into knowledge, and make it as easy as just thinking about it. The next generation commercial ecosystems will even augment time and thought for us, even predicting what we’ll need before we figure it out ourselves.
  • If all of this sounds a little futuristic, it is also now all just within the realm of possibility, and so it will almost certainly happen, it’s just matter of exactly when. It also gives our organizations a clearer target to shoot for, at least if your organization considers moon shots. Because most organizations are struggling with being a digital contemporary in basic terms, much less getting ahead of the game. But there are ways of getting there, if organizations are prepared, it just takes a vision of the future to aim for.
  • We will explore more about the fourth platform soon, but would love to hear your thoughts on how networks, people, and devices are coming together to create all new possibilities for the enterprises.

CyberPhysicality — Defining a Digital Twin Platform

  • Digital Twin is considered one of the key trends for IoT. The idea of a digital twin is to create a digital replica of a physical object and use the twin as the main point of digital interaction. A digital twin could be a factory lathe, a windmill, a container ship, or automobile. Gartner Group has listed digital twins as one of their top 10 technology trends. A survey conducted by Gartner found close to half of organizations are using or plan to use digital twins in 2018.
  • A lot of has been written about digital twins, especially about the concept and benefits. There are lots of very cool demos/videos that showcase digital twins in simulations and VR/AR scenarios.
  • What is less clear is the technology required to build and deploy digital twins. What technology is needed for organizations to make digital twins a reality for large-scale deployments. How do you manage thousands of digital twins or thousands of different types of digital twins? How do you integrate a digital twins with other systems?
  • For organizations that want to scale out a digital twin strategy, we believe they are going to require something like a digital twin platform. However, the question becomes what defines a digital twin platform? It seems there are 6 key features that would define any scalable digital twin platform.
  1. Manage the Digital Twin Lifecycle — How do you design, build, test, deploy and maintain a digital twin and its digital master? Digital twins are the instantiations of something called the digital thread or digital master. For instance, each windmill will be based on a common digital master that represent the engineering diagrams, bill of material, software versions and other artifacts used to create each windmill. A digital twin platform needs the tools to bring all this information together to create the digital master and then manage any changes to the digital master. Tools then need to be available to test, deploy and manage each digital twin based on a specific digital master. The tools also need to be able to handle hundreds of digital masters and thousands of digital twins.
  2. Single Source of Truth — A digital twin is suppose to be an exact replica of a physical asset and the data coming from the asset. However, the maintenance of a physical asset can often change its physical state. For instance, a specific windmill might have a replacement part or a different version of firmware installed; other windmills might not have the same updates. A digital twin platform is able to update and provide the exact state for each individual digital twin, creating a single source of truth.
  3. Open API — A well defined digital twin becomes the interface and integration point for an Industrial IoT solution. A digital twin platform provides an open api that allows any system to interact with the digital twin. For instance, machine learning and analytics services should be able to interact with a digital twin through an API. An organization should be able to integrate their digital twin into other enterprise systems, like ERP or SCM systems. A digital twin API should really enable the concept of Device as a Service.
  4. Visualization and Analysis — Organizations should be able to use their digital twin platform to create visualizations, dashboards, and in-depth analysis of this live data from the digital twin. The live data should be linked to the digital master to allow for drill-downs into design documents or other components of the digital master.
  5. Event and process management — It should be possible to setup events and business processed to be executed based on digital twin data. For instance, events to schedule maintenance calls based on live data and an accurate view of the current maintenance status of the physical asset.
  6. Customer and User Perspective — A digital twin platform needs to provide a customer and user perspective. What organization own or operate each digital twin? What users are allowed to access the data and information associated with the digital twin. How can you share information with other users that might be involved in the design of a new release for the asset. A digital twin platform needs to enable collaboration between the stakeholders of the digital twin.

4 Th Platform

  • Platform business models are fast becoming the golden child of the digital revolution. As digital platforms disrupt and dominate markets to create communities of enormous scale, they deliver compelling customer experiences and offer new forms of innovation and value creation. Yet, most new platform businesses will fail unless players acquire a new mindset and business approach.

Platforms are pervasive

  • Until recently, digital platforms were the preserve
    of technology and digital-born companies, such as Google, Apple, Facebook and Amazon, and of digital start-ups, such as Airbnb and Uber, that are fueling the on-demand or sharing economy. Now, resourceful entrepreneurs acting as digital partners — app developers, complementors or affiliate providers — can reap rewards from the platform economy. They can generate revenue, reduce costs, innovate products and services, or gain speed to market. And, as this report shows, they can do it anywhere.
  • Traditional incumbents, too, are developing their own platforms, working with innovative entrepreneurs and undertaking alliances or acquiring companies. For example, Philips is reinventing itself in the fast- emerging health technology market in this way. Research suggests platforms’ total market value is US$4.3 trillion, with an employment base of at least 1.3 million direct employees and several million indirectly employed at partner companies that service or complement platforms.

Platform Success Relies on Five Steps

  • Five factors that generate the network effects and critical mass crucial to the success of platform ecosystems (proposition, personalization, price, protection and partners) and highlight the five underlying environmental enablers that are necessary for platforms to flourish (digital user size and savviness, digital talent and entrepreneurship, technology and governance, open innovation culture and policy and regulation).
  • In assessing the digitalization maturity of several countries, it is found that not all countries provide an environment that is conducive to platform success. Platform Readiness Index shows that the United States, China, the United Kingdom, India and Germany top the rankings of those countries with the biggest opportunity to grow and scale digital platforms — and will retain their top five ranking in 2020. Countries such as Italy, South Africa and Russia are currently at the bottom of the table and must rapidly introduce ambitious policies if they are to boost digital platforms and narrow the gap with leading countries by 2020.

The pervasive power of platforms

  • Digital platforms are transforming market competition in all industries around the world and platform-based companies are gaining market share rapidly. Entrepreneurs are ideally placed to play a variety of roles in the platform economy as a means to accelerate their own growth.
  • Although traditional incumbents have started to react, less than
    15 percent of Fortune 100 companies have a developed platform
    model today. But the trend toward platform adoption is expected
    to continue — IDC predicts that, by 2021, more than 50 percent of
    large enterprises will create or partner with industry platforms. The platform revolution that began in the business-to-consumer (B2C) area through eCommerce, FinTech and circular economy business models, is expanding into the business-to-business (B2B) space with innovation- based ecosystems and data-enabled business models, such as the industrial Internet of Things (loT). This is mainly driven by companies shifting their focus from selling products to offering outcome-based services through digital platforms.
  • The concept behind platforms is not new. Shopping malls link consumers with merchants, and newspapers have connected subscribers and advertisers for more than a century. Now, the availability and convergence of affordable digital technologies is enabling companies
    of all sizes to embrace mobile and data and analytics while adopting
    a “cloud first” approach to redesign their business models. One of the advantages of digital platforms is their ability to introduce a new “pay- as-you-go” business model that enables efficient, low-cost speed to scale and the creation of new, richer customer experiences.

What is a digital platform?

  • A digital platform is a technology-enabled business model that creates value by facilitating exchanges between two or more interdependent groups. Most commonly, platforms bring together end users and producers to transact with each other. They also enable companies to share information to enhance collaboration or the innovation of new products and services. The platform’s ecosystem connects two or more sides, creating powerful network effects whereby the value increases as more members participate.
  • Platforms’ development can be accelerated by third parties’ provision of application programming interfaces (APIs) that enable participants to share data to create new services. Thanks to cloud and other technologies, they can provide resources on an as-a-service basis. Successful platforms operate under clear governance conditions that protect intellectual property and data ownership, fostering trust among participants.

Three sources of discrete power

  • The power behind digital platforms lies with three distinct features. First, the network effect of bringing together market participants means that more customers attract a greater number of merchants and partners, and vice versa. This shifts the cost and risk burden of creating markets from the business to the network. As the network gathers its own dynamic momentum, the platform owner acts as a facilitator to spread that burden among a growing number of participants.
  • Second, the concurrence of technologies — cloud, automation, analytics, artificial intelligence, mobile and the industrial internet — is creating
    a new “as-a-service” economy, where services are dynamic, on-demand and targeted, and have a huge impact on cost to serve, investment levels and speed to market. By integrating business processes, software and infrastructure and making them available “on demand,” large and small companies can benefit from plug-in, modular, scalable services. Entrepreneurs are particular beneficiaries here; without the constraints of funding the full costs of a platform business up front, they have access to new markets and distribution channels.
  • Finally, open and shared data can be mined intelligently by specialists, including those from adjacent industries, to create new forms of value. Insights might be generated from monitoring customer behavior at scale or from products or machines being used in the field. Indeed, huge volumes of data are being generated today and are estimated to double every two years to 2020. This new, collaborative and agile way of working is catching manyorganizations off-balance.
  • While it used to take Fortune 500 companies an average
    of 20 years to reach a billion-dollar valuation, today’s digital start-ups can get there in four years. Digital platforms are largely responsible for this shift.

Platform opportunities for all enterprises

Platforms open up the potential for entrepreneurs and small businesses to generate demand-side economies of scale that would be otherwise far beyond their reach. More specifically, they can play an active role in the platform economy as:

  • Platform owners: design and develop the platform, control intellectual property and decide how it will be run. Owners also manage users and partners who can add value to the core platform offering. For instance, Germany’s Fidor Bank, recently acquired by French banking group BPCE, solicits the participation of community users and partners to enable both traditional lending and lending via peer-to-peer capabilities.
  • Digital partners: team with platform owners to offer complementary products and services using application programing interfaces (APIs). For example, Fidor Bank maintains a close alliance with global payments provider, Currency Cloud, and extends multi-currency payment services through API integration with the provider.
  • Producers or suppliers: act as merchants selling goods directly to consumers or to businesses in the marketplace. For example, individuals in the Fidor banking community supply credit to their community peers that are in need of finance.
A recent survey suggests that additional revenues and cost reduction are the main benefits from platform businesses
  • To succeed, entrepreneurs must determine whether they will act as platform owners, digital partners or suppliers. Entrepreneurs acting as platform owners need to consider a host of market factors and individual capabilities before deciding to launch their platform. One of the primary considerations is whether markets are contestable or if the barriers to entry and sunk costs are too high. In China, for instance, all new contenders to the search engine space have failed within three years as Baidu continues to hold a formidable market share.
  • Yet, newcomers with a compelling value proposition have forged their own success and disrupted markets previously dominated by incumbents. The opportunity is undeniable; business avenues that were previously beyond the reach of entrepreneurs are now accessible. The United Kingdom’s Venture Founders is a platform owner that has opened up early-stage investments to a wider base of savvy investors — previously reserved for the likes of private equity, venture capital and angel networks.
  • Entrepreneurs acting as digital partners can help platform owners achieve scale by offering complementary products, growing alongside platform owners as a result. For example, Canada’s Shopify, which provides cloud- based commerce solutions, expanded to about 150 countries within a decade of being set up. Entrepreneurs also benefit from the technical, financial and mentoring support of platform owners. For example, the United Kingdom’s Swave start-up is developing a consumer financial literacy app and benefits from its access to Lloyds Bank’s digital experts and data for building the product. Entrepreneurs will need to adapt their business models to offer services “on demand” — for instance, accounting as a service. Further, platform owners seek to engage in an end-to-end collaboration in which the digital partner assumes some responsibility for the success of initiatives and accepts compensation based on the outcomes it commits to deliver.
  • Entrepreneurs acting as suppliers on a platform have access to a new distribution channel and benefit from additional revenue and reduced transaction costs, among others. In particular, eCommerce platforms facilitate suppliers’ participation in global value chains due to improved access to market information and marketing skills.
  • Participating in platforms is not without risk and requires entrepreneurs in all roles to reassess their strategies, capabilities and resources. Small companies and entrepreneurs need to rethink traditional product-driven approaches to become more customer experience-driven. Complexities arise around monopolies and competition, ownership and intellectual property rights. Open architectures and data sharing place an even greater emphasis on managing data privacy and security for customer data collection and usage. Finally, platform success often depends on the ability to form partnerships with players, often in adjacent fields, to create and deliver new customer experiences. Platform business models require continuous adaptation and agility to maintain the equilibrium of the two-sided market, which in turn generates positive network effects.
  • Ultimately, entrepreneurs must plan for the long term and acquire the critical mass and scale that is integral to platform success. Smaller players can survive or resist being acquired when operating with a strong, niche offering, but the ability to access growth capital and scale fast still lies at the heart of platform success.

A winning formula

Two essential dimensions must be mastered to develop a successful digital platform business

  • Create a dynamic platform ecosystem that enables businesses to achieve critical mass:Critical mass is dependent on mastering five distinctive capabilities that we call the five Ps: a differentiated value proposition, service personalization, market responsive pricing, effective cyber protection, alongside taking advantage of the scalability power of ecosystem partners.
  • Foster a supportive enabling environment:
    There are factors and conditions within the broader economy that are required for platforms to emerge and grow — digital user size and savviness, digital talent and entrepreneurship, technology and governance, open innovation culture and public policies.

Create a dynamic platform ecosystem — Five ways to win

  • Competition in the platform economy will be fierce, especially as companies from adjacent sectors extend beyond their traditional markets. Yet, although there is no “one-size-fits-all” platform model, we have identified five ways a dynamic ecosystem can drive platform success.
  • Platform failure is surprisingly hard to track. Fortune notes that nine out of 10 startups fail while CB Insights reports that more than 70 percent of all failed technology companies have been in the internet sector — and this percentage has been consistent over the last few years. On the failure list, online marketplaces rank second after social companies.
  • Less than 10 percent of start-up platforms will succeed to become profitable independent entities — even lower in markets such as China where the platform market is highly competitive. For example, the vast number of online lending platforms in China alone was reported to be in the range of 1,500 to 1,700 in early 2015. It is questionable how feasible it will be for this number of peer-to-peer lending platforms to scale in a fragmented market that is further fractured by offline lending institutions.
  • Barriers to entry are becoming higher. Large platform players are expanding geographically, shifting from business-to-consumer to business-to-business (examples include Airbnb,, Expedia and Uber), or developing online-to-offline models that move them from digital channels to physical stores (like Amazon, DHgate or Paytm).
  • Large companies will also be challenged to adapt their culture, practices and operations to suit the particular demands of customers and partners in the platform world.
  • Adjacency between industries, sectors and countries will increase in the coming years, bringing more and more players into direct competition with each other. For instance, Google has expanded from search to maps, a mobile operating system and autonomous cars. In financial services, digital wallet products from Google, Apple, Facebook and Amazon (“GAFA”) as well as Baidu, Alibaba and Tencent (“BAT”) have encroached on the territory of digital players like Paypal, as well as traditional banks.18 In India, Flipkart has added a mobile wallet to its eCommerce platform, and mobile payments service, Patym, has entered the digital commerce marketplace with a banking license and its own eCommerce service.
  • The challenge does not end here. As the market has shown, the power of network effects can act in reverse and destroy value at explosive speed — companies can miscalculate one or more sides of the multisided marketplace or quickly lose their critical mass to a peer platform, such as Orkut’s closure in 2014 as social media enthusiasts shifted to Facebook.

Create a dynamic platform ecosystem: Five ways to win

  • Attracting a critical mass of users — on both demand and supply sides — is important to create value at scale. Frequently, platform owners must emphasize critical mass over profit generation in the initial stages of platform development, while maintaining a focus on value creation. For example, Alibaba’s Taobao platform used free listings to gain user momentum. Although the platform began to charge once it achieved critical mass, sustained value has been achieved through the personalization of the user experience, a wide range of horizontal services and the protection of customers by addressing security and counterfeit issues.
  • Critical mass is a function of proposition, personalization, price and protection, orchestrated by the owner with an ecosystem of partners. Each of these five Ps takes on new meaning as companies move from traditional “pipeline” businesses (that succeed by optimizing the activities in their value chains, most of which they own or control) to platform businesses (that bring together consumers and producers).

Proposition: Present a compelling solution through modularity

  • Traditionally, proposition is about the value produced by companies and sold to consumers, but in the platform world it is about users creating value for other users, facilitated by the owner. A platform requires continuous innovation in terms of value proposition and business model to create superior value for users, suppliers and partners in the ecosystem. For example, China-founded’s B2B proposition, “from factory to global customers,” is realized through a cross- border trading ecosystem — representing logistics, payments, internet financing, and technology innovation capabilities. Sellers benefit from increased margins with no middlemen, a shorter business cycle and extended global reach, along with strong local language services. Buyers enjoy a seamless and secure bulk purchase experience, supported by sellers’ customer service representatives trained by DHgate. The use of APIs is critical to market proposition, enabling a modular approach to platform development and revenue growth. For instance, Salesforce reportedly generates 50 percent of its revenues through APIs, eBay nearly 60 percent and Expedia a substantial 90 percent.22

Personalization: Center on the user journey

  • From a customer point of view, the driving force behind platforms is the personalization of an experience that is less oriented around products, as in the traditional business world, and more around the outcomes. Targeting individuals and organizations through tailored experiences across all channels at scale relies on mass personalization. The aim is to understand customer intent and then dynamically and uniquely tailor experiences to each customer and context in a seamless manner across channels. For example, Amazon uses “interest and intent collection management tools” to encourage buyers’ “stickiness” (see “Data-driven personalization at Amazon”). The platform’s ability to use customer data to personalize interactions will vary by country and even region based on data privacy laws.

Data-driven personalization at Amazon

  • The success of Amazon is data driven and its use of customer data to predict market needs and optimize business operations helps it to maintain market leadership. The company draws on predictive analytics to power recommendations that help it upsell. Service features, such as #AmazonWishList, enable customers to tailor buying lists that create stickiness, drive engagement and improve buyer retention. Predicting purchases based on behavioral patterns of a customer’s previous transactions on Amazon is also set to create a more personalized approach. A patent for anticipatory shipping will take data about a customer’s browsing and buying habits on the site, alongside real-world information such as telephone inquiries, to ship goods before a customer has even made the decision to buy. The combination of voice control and artificial intelligence offers a further opportunity for the hyper-personalization of the shopping experience. Amazon’s Echo devices, with the built-in voice- enabled Alexa platform, enable customers to order anywhere, anytime, while providing Amazon valuable insights on user behaviors.

Price: Engage participants through sophisticated, dynamic pricing

  • Where traditional business pricing policies merely aim to recover charges from customers, pricing strategies can differentiate platforms by presenting opportunities for greater flexibility and reward. A freemium approach means users have easy, generally free, access to a platform before deciding whether they want to be buyers. Alternatively, pay-as-you-go pricing can be combined with fixed subscription fees. Surge pricing is increasingly used to manage peak demand, in contrast with discount pricing in periods of low demand. For example, Airbnb has rolled out a smart pricing system for all hosts on its platform that adjusts room prices based on changes in demand in real time. A platform’s flexibility with surge pricing will depend on local rules, such as the legal directive for Uber and others not to charge beyond government-prescribed rates in India.25 More generally, pricing on platforms depends on price elasticities on the demand side versus the supply side: the side with the greater elasticity often ends up being “subsidized” by the other side, at least during the period of initial launch of the platform. Scale can transform pricing strategies. China’s Alipay offers online payment rates that are a fraction of local and global peers, being on average 0.6 percent compared to Paypal’s 2.9 percent. But the company is profitable due to a user base that is two and half times the size of Paypal’s and payment volumes that are seven times higher than its American peer. Data monetization remains one of the most promising opportunities of platforms

Protection: Embed trust at the heart of the platform

  • Cyber security is key — customers need to be sure the right safeguards are in place. Authentication of community members and their activities is the primary responsibility of the platform owner and partners, far more than in an offline business where physical verification is fundamental. Protecting a platform needs to account for both prevention and compensation. Handled correctly, platform owners can differentiate themselves with their commitment to protection. For instance, China’s, the B2B eCommerce platform, has announced 2016 as the “Year of Trust and Safety.” The company’s partnership with Authenticate it around product tracking, anti-counterfeit technology, upgrades to the merchant rating system and an escrow system, aims to build buyers’ confidence. Additionally,’s compensation measures include a collateral fund, buyer inconvenience reimbursement and penalties for fake shipping numbers.

Partners: Collaborate for scalable capability and agility

  • The vital role of digital partners should not be underestimated — whether as product or service complementors, payment providers
    or app developers — in helping to complete the platform offering and jointly fulfill customer needs. This contrasts a traditional company whose vendors are often detached from business outcomes. And partners can support platform owners to scale quickly. This is well illustrated in the open innovation that is behind many of the new FinTech companies’ approaches. For example, the modular design of U.S.-based Quicken means that large parts of the production chain are conducted by external providers, including sophisticated functions, such as predictive and specialized fraud analytics, and not only simple back-office activities.26 In its simplest form, collaboration may be a joint go-to-market approach, such as the referral partnerships of the UK’s NoviCap with TransferWise and Kantox on foreign exchange services for SMEs, and Sage on accounting software.

Data monetization — the quintessential competency

  • Data generated by platforms proliferates — whether from analysis of user experience, behaviors, service consumption or productivity measures. In turn, this creates a multiplier loop, where the value of data multiplies with the number of users and partners in the ecosystem. Platforms enable the gathering of data and the generation of real-time insights on customers, market trends and operations. Indeed, the rich volumes of data and the speed of intelligent service enhancement that is feasible on platforms are possibly beyond reach of the traditional business model.
  • The largest data-driven opportunity is the ability of a platform to capture value by creating new products and services, improving user experiences, managing risk and increasing productivity. These are avenues of internal monetization where data-driven enhancements are generated within the company. The impact is difficult to measure and the opportunity is often not maximized. Data monetization can also be achieved by providing data-based services to third-parties — which can be a high-margin business for platform players.
  • Although the largest opportunity will be internal monetization, the potential for external monetization is high if the platform holds unique data and has the capability to package innovative services around that data for third parties. While some platforms are primarily transaction oriented and others are strongly data oriented, the opportunity from data monetization is undeniable for all platforms.
  • The quality, uniqueness and richness of data are not the only determinants of internal and external monetization. Technology and workforces must have the capabilities to draw insights from the data. Platform players must adhere not only to privacy regulations, but also meet ever-increasing customer expectations around trust, privacy and security. Platform owners must safeguard usage and data rights, and ensure all participants conform to the local regulations for the jurisdictions in which the platform operates.
Data Monetization Opportunity
  • Alibaba’s asset-light model means China’s biggest online eCommerce company can invest in next-generation technologies and services, such as cloud computing and big data, to maintain its competitive edge. Data — and better understanding of it — is integral to the company’s operations. More than 37 percent of Alibaba’s workforce is science, technology, engineering and mathematics (STEM) talent, mainly employed in database management, machine learning and artificial intelligence.
    The data insights gained are being monetized in a number of different ways. For instance, Alibaba uses data to derive 49 percent of its group revenue from advertising services, including third-party advertisers. “Super-ID” under the Dharma Sword initiative tracks the preferences of 630 million users, the vast majority of China’s internet population. Sellers pay a monthly fee for Alibaba software that they use to analyze relevant
    data and personalize services for customers. Smart logistics
    data predicts supply and demand and guides platform sellers
    to pre-transfer merchandise to designated warehouses where there is strong demand. Finally, Alibaba is developing a unique enterprise credit system by bringing together data on sellers’ financial records, including affiliate Ant Financial’s records, past transactions and information from partners, such as banks.
  • Unique data can be of immense value to businesses and societies outside the platform business. For example, the Singapore- headquartered Tickled Media, a community platform for parents in Asia, has more than six million users across India, Indonesia, Malaysia, the Philippines, Singapore and Thailand. The company created a separate unit called theAsianparent Insights that aims to drive one-half of its revenues from providing data on the niche segment, the parents, to large companies such as Nestlé, Pfizer, Unilever and others. The data business unit can create on-demand market research solutions faster than any consumer survey company can today by running surveys, competitions or testing products and marketing strategies among its extensive user network on behalf of corporate clients

How incumbent companies can succeed

  • Traditional companies can successfully embrace platform-based business models if they align their operating model and culture, and work effectively with entrepreneurs in the platform environment. Company age is irrelevant when it comes to creating a platform business. Apple was more than 20 years old before it launched the iTunes and App Store platforms. General Electric was a century old when
    it launched its software for the industrial internet, PredixTM. Incumbents are well positioned to make the best use of their current customer base, brand, market expertise and industry know-how when launching a digital platform. Yet, incumbents must be mindful of the specific demands of a platform business.
  • It is essential to identify early on which areas of the traditional business are prime for disruption and where the platform model can be a growth engine that generates network effects. For some, this means freeing themselves from traditional industry vertical boundaries; for instance, the Bosch ConnectedWorld of IoT-empowered solutions in energy, industry, transportation and buildings. For others, a vertical depth is integral to the strategy, such as the Philips HealthSuite digital platform that brings connected care for patients and providers.
  • Each platform plan needs to be supported by new technology capabilities, especially APIs, and take account of their integration. This is where the partner ecosystem is critical to success. Other technology capabilities include mobile development platforms, the Internet of Things, infrastructure and cloud services, data-driven intelligent operations, rapid prototyping and testing capabilities, and real-time integration between the platform and the rest of the business. For example, Siemens MindSphere, a cloud platform for industry, collects and analyzes data that is created during production processes at industrial companies, as well as during the delivery of services. Based on this data, companies have new opportunities to further optimize their processes — and to develop new data-driven business models. Success of the platform is founded on Siemens helping its MindSphere corporate clients embrace new data capabilities, including the development of customer-specific business models and integration of different IT systems.
  • Operating model transformation is also a necessity. Incumbents must design new open organization structures and processes. Using a dual operation model can address the tensions between legacy organizations and processes on the one hand and new infrastructure on the other, allowing the two to merge over time. Incumbents must attract and motivate talent — specifically from the developer community — and promote a creative culture. Governance of platform businesses is different than in traditional business, due to the way data
    and transactions are shared between participants. Incumbents need to reconsider their governance plan specifically around intellectual property and data ownership to manage a platform’s open ecosystem and shared licensing models. For example, data governance was a key consideration in the implementation of Walgreens’ Connected Health platform to secure the full spectrum of patient data.
  • By embedding a collaboration culture to innovate and co-create with start-ups and entrepreneurs in the ecosystem, incumbents can develop viable platform businesses. Bank of New York Mellon runs NEXEN, an open-source, cloud-based technology platform that enables it to develop microservices in API format. NEXEN, together with private cloud and big data components, is expected to raise the bank’s bottom line by around 10 percent in 2017. Its success is attributed to an early cultural change transformation that attracted new millennial talent, encouraged employees to use design thinking, and effectively migrated legacy technology to the NEXEN platform.
  • The successful platforms became so based on network effects, the large demand economies of scale where users create value for users. Note that the biggest firms occur in the U.S. or China, where there are large homogenous markets. So be aware of policies that introduce fragmentation. Policy makers should be setting policy that helps create the greatest value for the greatest number of people and reduce fragmentation of markets. That will allow the large network effects to emerge.
  • The national economic, business and regulatory environment in which digital platform businesses are founded determines how they develop and scale. Each country — driven by its city or regional clusters — appears to be exporting its own local competitiveness to the global platform economy. For example, the New York area is home to a high number of FinTech unicorn platforms as a natural progression of its strength in traditional financial services. Yet, five common success factors stand out:

1. Digital user size and savviness: The scale of the market matters; countries with a large installed digital base and uniform culture, language and regulations have a competitive edge.

2. Digital talent and entrepreneurship: Science, technology, engineering and mathematics (STEM), entrepreneurial and creative skills are fundamental in enabling digital innovation. It is vital for governments to focus on nurturing these skills in their educational priorities, and for businesses to locate themselves based on talent pool availabilities.

3. Technology readiness: The status of technology and digital assets, including levels of connectivity and investment in next-generation technologies — such as the industrial internet and artificial intelligence — will influence platform generation, growth and scale.

4. Open innovation culture: Increasingly, innovation — embedded in business culture and in how the platform operates — relies on organizations partnering with developers or service complementors. Large companies need to design new open organization structures, processes and governance to manage platforms’ open ecosystems, while embedding a collaboration culture. Governments need to foster innovation hubs, bringing together universities, laboratories, start-ups and large businesses.

5. Adaptive policy and regulation: Rapid speed of change demands proactive and participative policy making, working jointly with platform players on complex areas, such as data privacy, blockchain or cybersecurity.

Unlock trapped value with digital platforms

  • Entrepreneurs, incumbent large companies and policy makers all have a role to play to orchestrate a vibrant platform economy.
  • Platform disruption is not new. In the nineteenth century, the new technologies of electricity and steel smelting supported the development of the platforms of the day: factories. These new platforms united workers, producers, suppliers and distribution channels in ways that released value that was trapped in pre-existing forms of production. New ecosystems unlocked that value by improving the efficiency and scale of manufacturing. And those same ecosystems also enabled the innovation that resulted in the variety of goods that changed not just industry, but wider society.
  • Today’s platforms are enabled by new digital technologies. Their ecosystems also involve great scale, bringing together customers, producers and innovators. Beyond scale, digital platforms use data to create value in new ways, resulting in entirely new products and services.
  • Just as in the early days of factories, a proliferation of platforms will result in high levels of failure and consolidation. And just as in the era of industrialization, some economies will outperform others due to the enabling factors they have put in place.
  • Our analysis of platform critical success factors shows that companies can begin to use digital technologies to release the trapped value now residing in the new ecosystems and markets that platforms are creating. But business leaders, entrepreneurs and policy makers must recognize the wider significance of digital platforms that will not merely create new opportunities for individual businesses, but transform entire sectors and economies. Platforms will reshape the way we produce, consume and do business. And, as history has shown us, today’s digital platforms can open up the potential for small businesses to reshape the industrial landscape.
  • The task ahead is not just reimagining new business models and markets, but also appreciating the role of digital platforms in the transformation of economies worldwide.
Five Factors of the Platform Readiness Index
  • Network effects are sometimes referred to as “Metcalfe’s Law” or “network externalities.” But don’t let the dull names fool you — this concept is rocket fuel for technology firms. Bill Gates leveraged network effects to turn Windows and Office into virtual monopolies and in the process became the wealthiest man in America. Mark Zuckerberg of Facebook, Sergey Brin and Larry Page of Google, Pierre Omidyar of eBay, Andrew Mason of Groupon, Evan Williams and Biz Stone of Twitter, Nik Zennström and Janus Friis of Skype, Steve Chen and Chad Hurley of YouTube, all these entrepreneurs have built massive user bases by leveraging the concept. When network effects are present, the value of a product or service increases as the number of users grows. Simply, more users = more value. Of course, most products aren’t subject to network effects — you probably don’t care if someone wears the same socks, uses the same pancake syrup, or buys the same trash bags as you. But when network effects are present they’re among the most important reasons you’ll pick one product or service over another. You may care very much, for example, if others are part of your social network, if your video game console is popular, and if the Wikipedia article you’re referencing has had prior readers. And all those folks who bought HD DVD players sure were bummed when the rest of the world declared Blu-ray the winner. In each of these examples, network effects are at work.

Not That Kind of Network

  • The term “network” sometimes stumps people when first learning about network effects. In this context, a network doesn’t refer to the physical wires or wireless systems that connect pieces of electronics. It just refers to a common user base that is able to communicate and share with one another. So Facebook users make up a network. So do owners of Blu-ray players, traders that buy and sell stock over the NASDAQ, or the sum total of hardware and outlets that support the BS 1363 electrical standard.


  • Network effects are among the most powerful strategic resources that can be created by technology-based innovation. Many category-dominating organizations and technologies, including Microsoft, Apple, NASDAQ, eBay, Facebook, and Visa, owe their success to network effects. Network effects are also behind the establishment of most standards, including Blu-ray, Wi-Fi, and Bluetooth.

Where’s All That Value Come From?

  • The value derived from network effects comes from three sources: exchange, staying power, and complementary benefits.


  • Facebook for one person isn’t much fun, and the first guy in the world with a fax machine didn’t have much more than a paperweight. But as each new Facebook friend or fax user comes online, a network becomes more valuable because its users can potentially communicate with more people. These examples show the importance of exchange in creating value. Every product or service subject to network effects fosters some kind of exchange. For firms leveraging technology, this might include anything you can represent in the ones and zeros of digital storage, such as movies, music, money, video games, and computer programs. And just about any standard that allows things to plug into one another, interconnect, or otherwise communicate will live or die based on its ability to snare network effects.

Exercise: Graph It

  • Some people refer to network effects by the name Metcalfe’s Law. It got this name when, toward the start of the dot-com boom, Bob Metcalfe (the inventor of the Ethernet networking standard) wrote a column in InfoWorld magazine stating that the value of a network equals its number of users squared. What do you think of this formula? Graph the law with the vertical axis labeled “value” and the horizontal axis labeled “users.” Do you think the graph is an accurate representation of what’s happening in network effects? If so, why? If not, what do you think the graph really looks like?

Staying Power

  • Users don’t want to buy a product or sign up for a service that’s likely to go away, and a number of factors can halt the availability of an effort: a firm could bankrupt or fail to attract a critical mass of user support, or a rival may successfully invade its market and draw away current customers. Networks with greater numbers of users suggest a stronger staying power. The staying power, or long-term viability, of a product or service is particularly important for consumers of technology products. Consider that when someone buys a personal computer and makes a choice of Windows, Mac OS, or Linux, their investment over time usually greatly exceeds the initial price paid for the operating system. A user invests in learning how to use a system, buying and installing software, entering preferences or other data, creating files — all of which mean that if a product isn’t supported anymore, much of this investment is lost.
  • The concept of staying power (and the fear of being stranded in an unsupported product or service) is directly related to switching costs (the cost a consumer incurs when moving from one product to another) and switching costs can strengthen the value of network effects as a strategic asset. The higher the value of the user’s overall investment, the more they’re likely to consider the staying power of any offering before choosing to adopt it. Similarly, the more a user has invested in a product, the less likely he or she is to leave.
  • Switching costs also go by other names. You might hear the business press refer to products (particularly Web sites) as being “sticky” or creating “friction.” Others may refer to the concept of “lock-in.” And the elite Boston Consulting Group is really talking about a firm’s switching costs when it refers to how well a company can create customers who are “barnacles” (that are tightly anchored to the firm) and not “butterflies” (that flutter away to rivals). The more friction available to prevent users from migrating to a rival, the greater the switching costs. And in a competitive market where rivals with new innovations show up all the time, that can be a very good thing!

How Important Are Switching Costs to Microsoft?

  • “It is this switching cost that has given our customers the patience to stick with Windows through all our mistakes, our buggy drivers, our high TCO [total cost of ownership], our lack of a sexy vision at times, and many other difficulties […] Customers constantly evaluate other desktop platforms, [but] it would be so much work to move over that they hope we just improve Windows rather than force them to move. […] In short, without this exclusive franchise [meaning Windows] we would have been dead a long time ago.”
  • “Microsoft: ‘Would Have Been Dead a Long Time Ago without Windows APIs,”

Complementary Benefits

  • Complementary benefits are those products or services that add additional value to the network. These products might include “how-to” books, software, and feature add-ons, even labor. You’ll find more books on auctioning that focus on eBay, more video cameras that upload to YouTube, and more accountants that know Excel than those tareted at any of their rivals. Why? Book authors, camera manufacturers, and accountants invest their time and resources where they’re likely to reach the biggest market and get the greatest benefit. In auctions, video, and spreadsheet software, eBay, YouTube, and Excel each dwarf their respective competition.
  • Products and services that encourage others to offer complementary goods are sometimes called platforms. Allowing other firms to contribute to your platform can be a brilliant strategy because those firms will spend their time and money to enhance your offerings. Consider the billion-dollar hardware ecosystem that Apple has cultivated around the iPod and that it’s now extending to other iOS products. There are over ninety brands selling some 280 models of iPod speaker systems. Thirty-four auto manufacturers now trumpet their cars as being iPod-ready, many with in-car docking stations and steering wheel music navigation systems. Each add-on enhances the value of choosing an iPod over a rival like the Microsoft Zune. And now with the App Store for the iPhone, iPod touch, and iPad, Apple is doing the same thing with software add-ons. Software-based ecosystems can grow very quickly. In less than a year after its introduction, the iTunes App Store boasted over fifty thousand applications, collectively downloaded over one billion times. Less than two years later, downloaded apps topped ten billion.
  • These three value-adding sources — exchange, staying power, and complementary benefits — often work together to reinforce one another in a way that makes the network effect even stronger. When users exchanging information attract more users, they can also attract firms offering complementaryproducts. When developers of complementary products invest time writing software — and users install, learn, and customize these products — switching costs are created that enhance the staying power of a given network. From a strategist’s perspective this can be great news for dominant firms in markets where network effects exist. The larger your network, the more difficult it becomes for rivals to challenge your leadership position.


  • Products and services subject to network effects get their value from exchange, perceived staying power, and complementary products and services. Tech firms and services that gain the lead in these categories often dominate all rivals.
  • Many firms attempt to enhance their network effects by creating a platform for the development of third-party products and services that enhance the primary offering.

One-Sided or Two-Sided Markets?

Understanding Network Structure

  • To understand the key sources of network value, it’s important to recognize the structure of the network. Some networks derive most of their value from a single class of users. An example of this kind of network is instant messaging (IM). While there might be some add-ons for the most popular IM tools, they don’t influence most users’ choice of an IM system. You pretty much choose one IM tool over another based on how many of your contacts you can reach. Economists would call IM a one-sided market (a market that derives most of its value from a single class of users), and the network effects derived from IM users attracting more IM users as being same-side exchange benefits (benefits derived by interaction among members of a single class of participant).
  • But some markets are comprised of two distinct categories of network participant. Consider video games. People buy a video game console largely based on the number of really great games available for the system. Software developers write games based on their ability to reach the greatest number of paying customers, so they’re most likely to write for the most popular consoles first. Economists would call this kind of network a two-sided market (network markets comprised of two distinct categories of participant, both of which that are needed to deliver value for the network to work). When an increase in the number of users on one side of the market (console owners, for example) creates a rise in the other side (software developers), that’s called a cross-side exchange benefit.

The Positive Feedback Loop of Network Effects

  • IM is considered a one-sided market (or one-sided network), where the value-creating, positive-feedback loop of network effects comes mostly from same-side benefits from a single group (IM members who attract other IM members who want to communicate with them). Discount deal sites like Groupon, however, are considered to be two-sided markets, where significant benefits come from two distinct classes of users that add value by attracting each other. In Groupon’s case, the more people that subscribe to receive the firm’s daily deal messages, the stronger the magnet that attracts potential advertisers who offer more deals, who in turn attract more subscribers (and so on). This dynamic has produced freak-show growth for the Chicago-based firm. Less than two years after Groupon was founded, Forbes declared the firm to be the fastest growing company in history. While the site has literally hundreds of competitors, few of the upstarts are formidable. The highly profitable Groupon ended 2010 with ten times the traffic of its nearest competitor Mashable. Groupon isn’t out of the clear yet. Firms like Facebook and Google — each with an established ad sales force and already strong relationships with advertisers — are launching their own daily deal efforts, gunning for Groupon’s growth. But as for the me-too wannabe upstarts — they’ve got nothing.
  • It’s also possible that a network may have both same-side and cross-side benefits, too. Xbox 360 benefits from cross-side benefits in that more users of that console attract more developers writing more software titles and vice versa. However, the Xbox Live network that allows users to play against each other has same-side benefits. If your buddies use Xbox Live and you want to play against them, you’re more likely to buy an Xbox.


  • In one-sided markets, users gain benefits from interacting with a similar category of users (think instant messaging, where everyone can send and receive messages to one another).
  • In two-sided markets, users gain benefits from interacting with a separate, complementary class of users (e.g., in Groupon’s daily-deal business, deal subscribers are attracted to the platform because there are more vendors offering deals, while vendors are attracted to Groupon because it has the most customers to receive the deals).

How Are These Markets Different?

  • When network effects play a starring role, competition in an industry can be fundamentally different than in conventional, nonnetwork industries.
  • First, network markets experience early, fierce competition. The positive-feedback loop inherent in network effects — where the biggest networks become even bigger — causes this. Firms are very aggressive in the early stages of these industries because once a leader becomes clear, bandwagonsform, and new adopters begin to overwhelmingly favor the leading product over rivals, tipping the market in favor of one dominant firm or standard. This tipping can be remarkably swift. Once the majority of major studios and retailers began to back Blu-ray over HD DVD, the latter effort folded within weeks.
  • These markets are also often winner-take-all or winner-take-most, exhibiting monopolistic tendencies where one firm dominates all rivals. Look at all of the examples listed so far — in nearly every case the dominant player has a market share well ahead of all competitors. When, during the U.S. Microsoft antitrust trial, Judge Thomas Penfield Jackson declared Microsoft to be a monopoly (a market where there are many buyers but only one dominant seller), the collective response should have been “of course.” Why? The natural state of a market where network effects are present (and this includes operating systems and Office software) is for there to be one major player. Since bigger networks offer more value, they can charge customers more. Firms with a commanding network effects advantage may also enjoy substantial bargaining power over partners. For example, Apple, which controls over 75 percent of digital music sales, for years was able to dictate song pricing, despite the tremendous protests of the record labels. In fact, Apple’s stranglehold was so strong that it leveraged bargaining power even though the “Big Four” record labels (Universal, Sony, EMI, and Warner) were themselves an oligopoly(a market dominated by a small number of powerful sellers) that together provide over 85 percent of music sold in the United States.
  • Finally, it’s important to note that the best product or service doesn’t always win. PlayStation 2 dominated the original Xbox in a prior generation’s game console war, despite the fact that nearly every review claimed the Xbox was hands-down a more technically superior machine. Why were users willing to choose an inferior product (PS2) over a superior one (Xbox)? The power of network effects! PS2 had more users, which attracted more developers offering more games.
  • This last note is a critical point to any newcomer wishing to attack an established rival. Winning customers away from a dominant player in a network industry isn’t as easy as offering a product or service that is better. Any product that is incompatible with the dominant network has to exceed the value of the technical features of the leading player, plus (since the newcomer likely starts without any users or third-party product complements) the value of the incumbent’s exchange, switching cost, and complementary product benefit . And the incumbent must not be able to easily copy any of the newcomer’s valuable new innovations; otherwise the dominant firm will quickly match any valuable improvements made by rivals. As such, technological leapfrogging, or competing by offering a superior generation of technology, can be really tough.

Is This Good for Innovation?

  • Critics of firms that leverage proprietary standards for market dominance often complain that network effects are bad for innovation. But this statement isn’t entirely true. While network effects limit competition against the dominant standard, innovation within a standard may actually blossom. Consider Windows. Microsoft has a huge advantage in the desktop operating system market, so few rivals try to compete with it. Apple’s Mac OS and the open source Linux operating system are the firm’s only credible rivals, and both have tiny market shares. But the dominance of Windows is a magnet for developers to innovate within the standard. Programmers with novel ideas are willing to make the investment in learning to write software for Windows because they’re sure that a Windows version can be used by the overwhelming majority of computer users.
  • By contrast, look at the mess we initially had in the mobile phone market. With so many different handsets containing differing computing hardware, offering different screen sizes, running different software, having different key layouts, and working on different carrier networks, writing a game that’s accessible by the majority of users is nearly impossible. Glu Mobile, a maker of online games, launched fifty-six reengineered builds of Monopoly to satisfy the diverse requirements of just one telecom carrier. As a result, entrepreneurs with great software ideas for the mobile market were deterred because writing, marketing, and maintaining multiple product versions is both costly and risky. It wasn’t until Apple’s iPhone arrived, offering developers both a huge market and a consistent set of development standards, that third-party software development for mobile phones really took off.


  • Unseating a firm that dominates with network effects can be extremely difficult, especially if the newcomer is not compatible with the established leader. Newcomers will find their technology will need to be so good that it must leapfrog not only the value of the established firm’s tech, but also the perceived stability of the dominant firm, the exchange benefits provided by the existing user base, and the benefits from any product complements. For evidence, just look at how difficult it’s been for rivals to unseat the dominance of Windows.
  • Because of this, network effects might limit the number of rivals that challenge a dominant firm. But the establishment of a dominant standard may actually encourage innovation within the standard, since firms producing complements for the leader have faith the leader will have staying power in the market.

Competing When Network Effects Matter

  • Why do you care whether networks are one-sided, two-sided, or some sort of hybrid? Well, when crafting your plan for market dominance, it’s critical to know if network effects exist, how strong they might be, where they come from, and how they might be harnessed to your benefit. Here’s a quick rundown of the tools at your disposal when competing in the presence of network effects.

Strategies for Competing in Markets with Network Effects (Examples in Parentheses)

  • Move early (Yahoo! Auctions in Japan)
  • Subsidize product adoption (PayPal)
  • Leverage viral promotion (Skype; Facebook feeds)
  • Expand by redefining the market to bring in new categories of users (Nintendo Wii) or through convergence (iPhone).
  • Form alliances and partnerships (NYCE vs. Citibank)
  • Establish distribution channels (Java with Netscape; Microsoft bundling Media Player with Windows)
  • Seed the market with complements (Blu-ray; Nintendo)
  • Encourage the development of complementary goods — this can include offering resources, subsidies, reduced fees, market research, development kits, venture capital (Facebook fbFund).
  • Maintain backward compatibility (Apple’s Mac OS X Rosetta translation software for PowerPC to Intel)
  • For rivals, be compatible with larger networks (Apple’s move to Intel; Live Search Maps)
  • For incumbents, constantly innovate to create a moving target and block rival efforts to access your network (Apple’s efforts to block access to its own systems)
  • For large firms with well-known followers, make preannouncements (Microsoft)

Move Early

  • In the world of network effects, this is a biggie. Being first allows your firm to start the network effects snowball rolling in your direction. In Japan, worldwide auction leader eBay showed up just five months after Yahoo! launched its Japanese auction service. But eBay was never able to mount a credible threat and ended up pulling out of the market. Being just five months late cost eBay billions in lost sales, and the firm eventually retreated, acknowledging it could never unseat Yahoo!’s network effects lead.
  • Another key lesson from the loss of eBay Japan? Exchange depends on the ability to communicate! EBay’s huge network effects in the United States and elsewhere didn’t translate to Japan because most Japanese aren’t comfortable with English, and most English speakers don’t know Japanese. The language barrier made Japan a “greenfield” market with no dominant player, and Yahoo!’s early move provided the catalyst for victory.
  • Timing is often critical in the video game console wars, too. Sony’s PlayStation 2 enjoyed an eighteen-month lead over the technically superior Xbox (as well as Nintendo’s GameCube). That time lead helped to create what for years was the single most profitable division at Sony. By contrast, the technically superior PS3 showed up months after Xbox 360 and at roughly the same time as the Nintendo Wii, and has struggled in its early years, racking up multibillion-dollar losses for Sony.

What If Microsoft Threw a Party and No One Showed Up?

  • Microsoft launched the Zune media player with features that should be subject to network effects — the ability to share photos and music by wirelessly “squirting” content to other Zune users. The firm even promoted Zune with the tagline “Welcome to the Social.” Problem was the Zune Social was a party no one wanted to attend. The late-arriving Zune garnered a market share of just 3 percent, and users remained hard pressed to find buddies to leverage these neat social features. A cool idea does not make a network effect happen.

Subsidize Adoption

  • Starting a network effect can be tough — there’s little incentive to join a network if there’s no one in the system to communicate with. In one admittedly risky strategy, firms may offer to subsidize initial adoption in hopes that network effects might kick in shortly after. Subsidies to adopters might include a price reduction, rebate, or other giveaways. PayPal, a service that allows users to pay one another using credit cards, gave users a modest rebate as a sign-up incentive to encourage adoption of its new effort (in one early promotion, users got back fifteen dollars when spending their first thirty dollars). This brief subsidy paid to early adopters paid off handsomely. EBay later tried to enter the market with a rival effort, but as a late mover its effort was never able to overcome PayPal’s momentum. PayPal was eventually purchased by eBay for $1.5 billion, and the business unit is now considered one of eBay’s key drivers of growth and profit.
  • Gilt Groupe, a high-end fashion flash deals site, used subsidies to increase adoption of the firm’s mobile app “Gilt on the Go” — fueling the growth of a new and vital distribution channel. Gilt knew that getting its app into the purses and pockets of more of its users would increase the chance that a customer would view more deals and act on them. To encourage mobile owners to download the Gilt app, the company offered instant membership (as opposed to its normal invitation-only model) and a ten-dollar credit to the first ten thousand new subscribers. Awareness of Gilt on the Go spread virally, and apps grew in a flash, accounting for 15 percent of the firm’s revenue within months. Some of the best approaches to competing in network markets will simultaneously leverage several of the strategies we’re outlining here, and in the case of Gilt, the subsidy helped create viral promotion that in turn helped establish a new distribution channel.

When Even Free Isn’t Good Enough

  • Subsidizing adoption after a rival has achieved dominance can be an uphill battle, and sometimes even offering a service for free isn’t enough to combat the dominant firm. When Yahoo! introduced a U.S. auction service to compete with eBay, it initially didn’t charge sellers at all (sellers typically pay eBay a small percentage of each completed auction). The hope was that with the elimination of seller fees, enough sellers would jump from eBay to Yahoo! helping the late-mover catch up in the network effect game.
  • But eBay sellers were reluctant to leave for two reasons. First, there weren’t enough buyers on Yahoo! to match the high bids they earned on much-larger eBay. Some savvy sellers played an arbitrage game where they’d buy items on Yahoo!’s auction service at lower prices and resell them on eBay, where more users bid prices higher.
  • Second, any established seller leaving eBay would give up their valuable “seller ratings,” and would need to build their Yahoo! reputation from scratch. Seller ratings represent a critical switching cost, as many users view a high rating as a method for reducing the risk of getting scammed or receiving lower-quality goods.
  • Auctions work best for differentiated goods. While Amazon has had some success in peeling away eBay sellers who provide commodity products (a real danger as eBay increasingly relies on fixed-price sales), eBay’s dominant share of the online auction market still towers over all rivals. While there’s no magic in the servers used to create eBay, the early use of technology allowed the firm to create both network effects and switching costs — a dual strategic advantage that has given it a hammerlock on auctions even as others have attempted to mimic its service and undercut its pricing model.

Leverage Viral Promotion

  • Since all products and services foster some sort of exchange, it’s often possible to leverage a firm’s customers to promote the product or service. Internet calling service Skype (now owned by Microsoft) has over six hundred million registered users yet has spent almost nothing on advertising. Most Skype users were recruited by others who shared the word on free and low-cost Internet calls. And rise of social media has made viral promotion a tool that many firms can exploit. Facebook and Twitter act as a catalyst for friends to share deals, spread a good word, sign up for services, and load applications.

Expand by Redefining the Market

  • If a big market attracts more users (and in two-sided markets, more complements), why not redefine the space to bring in more users? Nintendo did this when launching the Wii. While Sony and Microsoft focused on the graphics and raw processing power favored by hard-core male gamers, Nintendo chose to develop a machine to appeal to families, women, and age groups that normally shunned alien shoot-’em ups. By going after a bigger, redefined market, Nintendo was able to rack up sales that exceeded the Xbox 360, even though it followed the system by twelve months.

Seeking the Blue Ocean? Better Think Strategically

  • Reggie Fils-Aimé, the President of Nintendo of America, describes the Wii Strategy as a Blue Ocean effort. The concept of blue ocean strategy was popularized by European Institute of Business Administration (INSEAD) professors W. Chan Kim and Renée Mauborgne (authors of a book with the same title). The idea — instead of competing in blood-red waters where the sharks of highly competitive firms vie for every available market scrap, firms should seek the blue waters of uncontested, new market spaces.
  • For Nintendo, the granny gamers, moms, and partygoers who flocked to the Wii represented an undiscovered feast in the Blue Ocean. Talk about new markets! Consider that the best-selling video game at the start of 2009 was Wii Fit — a genre-busting title that comes with a scale so you can weigh yourself each time you play. That’s a far cry from Grand Theft Auto IV, the title ranking fifth in 2008 sales, and trailing four Wii-only exclusives.
  • Blue ocean strategy often works best when combined with strategic positioning described. If an early mover into a blue ocean can use this lead to create defensible assets for sustainable advantage, late moving rivals may find markets unresponsive to their presence. Of course, if your firm’s claim in the blue ocean is based on easily imitated resources (like technology features), then holding off rivals will be tougher. For holiday season 2010, Microsoft showed up with its own motion-gaming controller, the Kinect video camera system. Kinect was such a hit with generation Wii that it became the fastest-selling consumer electronics product in history, pumping up Xbox 360 console sales and goosing Microsoft’s entertainment division from zero to a billion dollars in profits in just two years.
  • Market expansion sometimes puts rivals who previously did not compete on a collision course as markets undergo convergence (when two or more markets, once considered distinctly separate, begin to offer similar features and capabilities). Consider the market for portable electronic devices. Separate product categories for media players, cameras, gaming devices, phones, and global positioning systems (GPS) are all starting to merge. Rather than cede its dominance as a media player, Apple leveraged a strategy known as envelopment, where a firm seeks to make an existing market a subset of its product offering. Apple deftly morphed the iPod into the iPhone, a device that captures all of these product categories in one device. But the firm went further; the iPhone is Wi-Fi capable, offers browsing, e-mail, and an application platform based on a scaled-down version of the same OS X operating system used in Macintosh computers. As a “Pocket Mac,” the appeal of the device broadened beyond just the phone or music player markets, and within two quarters of launch, iPhone become the second-leading smartphone in North America — outpacing Palm, Microsoft, Motorola and every other rival, except RIM’s BlackBerry.

Alliances and Partnerships

  • Firms can also use partnerships to grow market share for a network. Sometimes these efforts bring rivals together to take out a leader. In a classic example, consider ATM networks. Citibank was the first major bank in New York City to offer a large ATM network. But the Citi network was initially proprietary, meaning customers of other banks couldn’t take advantage of Citi ATMs. Citi’s innovation was wildly popular and being a pioneer in rolling out cash machines helped the firm grow deposits fourfold in just a few years. Competitors responded with a partnership. Instead of each rival bank offering another incompatible network destined to trail Citi’s lead, competing banks agreed to share their ATM operations through NYCE (New York Cash Exchange). While Citi’s network was initially the biggest, after the NYCE launch a Chase bank customer could use ATMs at a host of other banks that covered a geography far greater than Citi offered alone. Network effects in ATMs shifted to the rival bank alliance, Citi eventually joined NYCE and today, nearly every ATM in the United States carries a NYCE sticker.
  • Google has often pushed an approach to encourage rivals to cooperate to challenge a leader. Its Open Social standard for social networking (endorsed by MySpace, LinkedIn, Bebo, Yahoo! and others) is targeted at offering a larger alternative to Facebook’s more closed efforts , while its Android open source mobile phone operating system has gained commitments from many handset makers that collectively compete with Apple’s iPhone.

Share or Stay Proprietary?

  • Defensive moves like the ones above are often meant to diffuse the threat of a proprietary rival. Sometimes firms decide from the start to band together to create a new, more open standard, realizing that collective support is more likely to jumpstart a network than if one firm tried to act with a closed, proprietary offering. Examples of this include the coalitions of firms that have worked together to advance standards like Bluetooth and Wi-Fi. While no single member firm gains a direct profit from the sale of devices using these standards, the standard’s backers benefit when the market for devices expands as products become more useful because they are more interoperable.

Leverage Distribution Channels

  • Firms can also think about novel ways to distribute a product or service to consumers. Sun faced a challenge when launching the Java programming language — no computers could run it. In order for Java to work, computers need a little interpreter program called the Java Virtual Machine (JVM). Most users weren’t willing to download the JVM if there were no applications written in Java, and no developers were willing to write in Java if no one could run their code. Sun broke the logjam when it bundled the JVM with Netscape’s browser. When millions of users downloaded Netscape, Sun’s software snuck in, almost instantly creating a platform of millions for would-be Java developers. Today, even though Netscape has failed, Sun’s Java remains one of the world’s most popular programming languages. Indeed, Java was cited as one of the main reasons for Oracle’s 2009 acquisition of Sun, with Oracle’s CEO saying the language represented “the single most important software asset we have ever acquired.”
  • And when you don’t have distribution channels, create them. That’s what Apple did when it launched the Apple retail stores a little over a decade ago. At the time of launch, nearly every pundit expected the effort to fail. But it turns out, the attractive, high-service storefronts were the perfect platform to promote the uniqueness of Apple products. Apple’s 300+ stores worldwide now bring in about ten billion dollars in revenue and are among the world’s most successful retail outlets on a sales-per-square-foot basis.
  • Microsoft is in a particularly strong position to leverage this approach. The firm often bundles its new products into its operating systems, Office suite, Internet Explorer browser, and other offerings. The firm used this tactic to transform once market-leader Real Networks into an also-ran in streaming audio. Within a few years of bundling Windows Media Player (WMP) with its other products, WMP grabbed the majority of the market, while Real’s share had fallen to below 10 percent.
  • Caution is advised, however. Regional antitrust authorities may consider product bundling by dominant firms to be anticompetitive. European regulators have forced Microsoft to unbundle Windows Media Player from its operating system and to provide a choice of browsers alongside Internet Explorer.

Antitrust: Real Versus Microsoft

  • From October 2001 to March 2003, Microsoft’s bundling of Windows Media Player in versions of its operating system ensured that the software came preinstalled on nearly all of the estimated 207 million new PCs shipped during that period. By contrast, Real Networks’ digital media player was preinstalled on less than 2 percent of PCs. But here’s the kicker that got to regulators (and Real): Microsoft’s standard contract with PC manufacturers “prevented them not only from removing the Windows Media Player, but even [from] providing a desktop icon for Real Networks. While network effects create monopolies, governments may balk at allowing a firm to leverage its advantages in ways that are designed to deliberately keep rivals from the market.

Seed the Market

  • When Sony launched the PS3, it subsidized each console by selling at a price estimated at three hundred dollars below unit cost. Subsidizing consoles is a common practice in the video game industry — game player manufacturers usually make most of their money through royalties paid by game developers. But Sony’s subsidy had an additional benefit for the firm — it helped sneak a Blu-ray player into every home buying a PS3 (Sony was backing the Blu-ray standard over the rival HD DVD effort). PS3 has struggled with fierce competition, but initially seeding the market with low-cost Blu-ray players at a time when that hardware sold at a very high price gave eventual winner Blu-ray some extra momentum. Since Sony is also a movie studio and manufacturer of DVD players and other consumer electronics, it had a particularly strong set of assets to leverage to encourage the adoption of Blu-ray over rival HD DVD.
  • Giving away products for half of a two-sided market is an extreme example of this kind of behavior, but it’s often used. In two-sided markets, you charge the one who will pay. Adobe gives away the Acrobat reader to build a market for the sale of software that creates Acrobat files. Firms with Yellow Page directories give away countless copies of their products, delivered straight to your home, in order to create a market for selling advertising. And Google does much the same by providing free, ad-supported search.

Encourage the Development of Complementary Goods

  • There are several ways to motivate others to create complementary goods for your network. These efforts often involve some form of developer subsidy or other free or discounted service. A firm may charge lower royalties or offer a period of royalty-free licensing. It can also offer free software development kits (SDKs), training programs, co-marketing dollars, or even start-up capital to potential suppliers. Microsoft and Apple both allow developers to sell their products online through Xbox LIVE Marketplace and iTunes, respectively. This channel lowers developer expenses by eliminating costs associated with selling physical inventory in brick-and-mortar stores and can provide a free way to reach millions of potential consumers without significant promotional spending.
  • Venture funds can also prompt firms to create complementary goods. Facebook announced it would spur development for the site in part by administering the fbFund, which initially pledged $10 million in start-up funding (in allotments of up to $250,000 each) to firms writing applications for its platform.

Leverage Backward Compatibility

  • Those firms that control a standard would also be wise to ensure that new products have backward compatibility with earlier offerings. If not, they reenter a market at installed-base zero and give up a major source of advantage — the switching costs built up by prior customers. For example, when Nintendo introduced its 16-bit Super Nintendo system, it was incompatible with the firm’s highly successful prior generation 8-bit model. Rival Sega, which had entered the 16-bit market two years prior to Nintendo, had already built up a large library of 16-bit games for its system. Nintendo entered with only its debut titles, and no ability to play games owned by customers of its previous system, so there was little incentive for existing Nintendo fans to stick with the firm.
  • Backward compatibility was the centerpiece of Apple’s strategy to revitalize the Macintosh through its move to the Intel microprocessor. Intel chips aren’t compatible with the instruction set used by the PowerPC processor used in earlier Mac models. Think of this as two entirely different languages — Intel speaks French, PowerPC speaks Urdu. To ease the transition, Apple included a free software-based adaptor, called Rosetta, that automatically emulated the functionality of the old chip on all new Macs (a sort of Urdu to French translator). By doing so, all new Intel Macs could use the base of existing software written for the old chip; owners of PowerPC Macs were able to upgrade while preserving their investment in old software; and software firms could still sell older programs while they rewrote applications for new Intel-based Macs.
  • Even more significant, since Intel is the same standard used by Windows, Apple developed a free software adaptor called Boot Camp that allowed Windows to be installed on Macs. Boot Camp (and similar solutions by other vendors) dramatically lowered the cost for Windows users to switch to Macs. Within two years of making the switch, Mac sales skyrocketed to record levels. Apple now boasts a commanding lead in notebook sales to the education market and a survey by Yankee Group found that 87 percent of corporations were using at least some Macintosh computers, up from 48 percent at the end of the PowerPC era two years earlier.

Rivals: Be Compatible with the Leading Network

  • Companies will want to consider making new products compatible with the leading standard. Microsoft’s Live Maps and Virtual Earth 3D arrived late to the Internet mapping game. Users had already put in countless hours building resources that meshed with Google Maps and Google Earth. But by adopting the same keyhole markup language (KML) standard used by Google, Microsoft could, as TechCrunch put it, “drink from Google’s milkshake.” Any work done by users for Google in KML could be used by Microsoft. Voilà, an instant base of add-on content!

Incumbents: Close Off Rival Access and Constantly Innovate

  • Often times firms that control dominant networks will make compatibility difficult for rivals who try to connect with their systems. For example, while many firms offer video conferencing and Internet calling, the clear leader is Skype, a product that for years had been closed to unauthorized Skype clients.
  • Firms that constantly innovate make it particularly difficult for competitors to become compatible. Again, we can look to Apple as an example of these concepts in action. While Macs run Windows, Windows computers can’t run Mac programs. Apple has embedded key software in Mac hardware, making it tough for rivals to write a software emulator like Boot Camp that would let Windows PCs drink from the Mac milkshake. And if any firm gets close to cloning Mac hardware, Apple sues. The firm also modifies software on other products like the iPhone and iTunes each time wily hackers tap into closed aspects of its systems. And Apple has regularly moved to block third-party hardware, such as Palm’s mobile phones, from plugging into iTunes. Even if firms create adaptors that emulate a standard, a firm that constantly innovates creates a moving target that’s tough for others to keep up with.
  • Apple has been far more aggressive than Microsoft in introducing new versions of its software. Since the firm never stays still, would-be cloners never get enough time to create a reliable emulator that runs the latest Apple software.

Large, Well-Known Followers: Preannouncements

  • Large firms that find new markets attractive but don’t yet have products ready for delivery might preannounce efforts in order to cause potential adaptors to sit on the fence, delaying a purchasing decision until the new effort rolls out. Preannouncements only work if a firm is large enough to pose a credible threat to current market participants. Microsoft, for example, can cause potential customers to hold off on selecting a rival because users see that the firm has the resources to beat most players (suggesting staying power). Statements from start-ups, however, often lack credibility to delay user purchases. The tech industry acronym for the impact firms try to impart on markets through preannouncements is FUD for fear, uncertainty, and doubt.

The Osborne Effect

  • Preannouncers, beware. Announce an effort too early and a firm may fall victim to what’s known as “The Osborne Effect.” It’s been suggested that portable computer manufacturer Osborne Computer announced new models too early. Customers opted to wait for the new models, so sales of the firm’s current offerings plummeted. While evidence suggests that Osborne’s decline had more to do with rivals offering better products, the negative impact of preannouncements has hurt a host of other firms. Among these, Sega, which exited the video game console market entirely after preannouncements of a next-generation system killed enthusiasm for its Saturn console.

Too Much of a Good Thing?

  • When network effects are present, more users attract more users. That’s a good thing as long as a firm can earn money from this virtuous cycle. But sometimes a network effect attracts too many users and a service can be so overwhelmed it becomes unusable. These so-called congestion effects occur when increasing numbers of users lower the value of a product or service. This most often happens when a key resource becomes increasingly scarce. Users of the game Ultima were disappointed in an early online version that launched without enough monsters to fight or server power to handle the crush of fans. Twitter’s early infrastructure was often unable to handle the demands of a service in hypergrowth (leading to the frequent appearance of a not-in-service graphic known in the Twitter community as the “fail whale”). Facebook users with a large number of friends may also find their attention is a limited resource, as feeds push so much content that it becomes difficult to separate interesting information from the noise of friend actions.
  • And while network effects can attract positive complementary products, a dominant standard may also be the first place where virus writers and malicious hackers choose to strike.
  • Feel confident! Now you’ve got a solid grounding in network effects, the key resource leveraged by some of the most dominant firms in technology. And these concepts apply beyond the realm of tech, too. Network effects can explain phenomena ranging from why some stock markets are more popular than others to why English is so widely spoken, even among groups of nonnative speakers. On top of that, the strategies explored in the last half of the chapter show how to use these principles to sniff out, create, and protect this key strategic asset. Go forth, tech pioneer — opportunity awaits!


  • Moving early matters in network markets — firms that move early can often use that time to establish a lead in users, switching costs, and complementary products that can be difficult for rivals to match.
  • Additional factors that can help a firm establish a network effects lead include subsidizing adoption; leveraging viral marketing, creating alliances to promote a product or to increase a service’s user base; redefining the market to appeal to more users; leveraging unique distribution channels to reach new customers; seeding the market with complements; encouraging the development of complements; and maintaining backward compatibility.
  • Established firms may try to make it difficult for rivals to gain compatibility with their users, standards, or product complements. Large firms may also create uncertainty among those considering adoption of a rival by preannouncing competing products.

Building A Super App with The 4th Plaform and Network Effect — Digital Twin of Everything Physical

  • A super app is like an app of apps. It acts as an umbrella app and declutters the number of apps in a mobile phone.
  • In simple words, it is a marketplace of services and offerings, delivered via in-house technology and through third-party integrations. The term was originally coined in 2010 by Mike Lazaridis in 2010, the founder of BlackBerry WeChat: One of the most successful Super-Apps in is Tencent-owned WeChat in China which gained 40% market share in digital payments just within two years of its launch in 2011. Launched initially as a messaging app, WeChat has transformed into an …
  • Reliance Jio is working on a ‘super app’ that will offer more than 100 services at one platform. Reliance Industries already has plans to launch the world’s largest online-to-offline new e-commerce platform to take on Amazon and Walmart-Flipkart.
  • With an unparallel growth in data and voice traffic, Jio now serves more than 300 million subscribers in India. The ‘super app’ will help in putting Reliance in a pole position to create India’s WeChat in a market where companies like Paytm, Snapdeal, Freecharge, Flipkart and Hike have failed.
  • Reliance Jio ‘super app’ will help to facilitate e-commerce and online bookings, including payments, all at one place.
  • The ubiquitousness of Jio devices puts Reliance in a powerful position. It can connect its vast ecosystem of its users with a multi-layered fabric, offering a rich array of services, connecting online-to-offline, through a one-stop, super app”.
  • India is a mobile-first nation and such a self-contained network that offers convenience will find favour with demanding consumers”.
  • All of these layers, on top of the Jio devices network would put Reliance in a pole position to create India’s WeChat”.
  • According to a joint report by Deloitte India and Retail Association of India, India is the fastest growing e-commerce market that is poised to touch $84 billion by 2021. With Reliance planning to enter the market, the e-commerce space could see massive disruption in the market.
  • RIL aims at transforming the e-commerce platform and lives of more than three crore merchants across India via technology.
  • Reliance is working on creating the world’s largest online-to-offline New Commerce Platform.
  • With the successful execution of the mobility business, Jio focuses on catapulting India’s underserved Home and Enterprise connectivity market to global standards using the next-generation GigaFiber FTTH services
  • Businesses will further accelerate the pace of their digital activities in 2021 by creating new-age apps and platforms and the world will see this battle ratcheting up in intensity in India led by Reliance Jio Platforms.
  • According to global market research firm Forrester, Covid-19 affected Asia Pacific first, and they expect the region will also emerge from the crisis first in 2021, before the US and Europe.
  • APAC will see a platform surge. APAC is already home to some of the largest platforms in places like China and India. However, we will see this battle ratcheting up in intensity, especially in India.
  • Reliance’s Jio Platforms has already blazed the trail with more than $20 billion investment in their digital business.
  • They are simultaneously lining up more investments for their retail platform. Tata in India has thrown their hat in the ring with the announcement of their own super-app.
  • With Paytm and Walmart’s Flipkart in the fray, India will see some serious competition among these platforms.
  • Targeting Google’s dominance in the app distribution space in India, leading digital payments platform Paytm last has also set up a Rs 10 crore fund as equity investments for mini app developers in the country.
  • Paytm has also launched an Android Mini App Store to support local developers in the country.
  • On 5G, will finally make an impact and China will be its epicentre.
  • In China, with heavy government support, rapid rollouts across the country, and evolution of supporting tech, 5G will find an ideal breeding ground for innovations across various verticals.
  • China’s experimentation and adoption of 5G-enabled business models and 5G-led innovation will offer valuable lessons to other countries and enterprises.
  • Values-focused firms will deliver higher profits than those focusing on profits alone.
  • Brands can no longer work in shadows with a constant spotlight on each of their actions, statements, and associations across social media. They must show their explicit commitment to respect customers’ privacy, for example.
  • They must tackle complex economic, environmental, and social challenges that impact all of us. They must do so with integrity, competence, and transparency to earn the trust and loyalty of these values-conscious consumers.
  • The cybersecurity concerns will also dominate the agendas of businesses and governments alike.
  • We will see increased adoption of Zero Trust and evolution of regulatory frameworks for data protection and privacy. Further, we expect firms to sharpen their focus on employee experience as they struggle to deal with people’s aspect of pandemic.

JIO Valuations

  • It is Jio Platforms’ multiple revenue streams from the same user base.
  • Jio Platforms is a subscription driven model and has a lot of consumer data. It uses latest technology and cloud computing for delivery which decouples revenue from the number of users or subscribers that one has. Which means that the more times the same customer base is used for multiple revenue mechanism, the higher the valuation is.
  • And for an investor this is pretty shining and the growth in user base is also good quarter-on-quarter. When you are able to add that kind of subscriber base and do multiple times monetisation, then of course it makes it very interesting as a company.
  • Jio Infocomm, on the other hand, is capex heavy, and has a linear revenue model so it does not offer much in terms of valuation.
  • Jio Platforms, the digital subsidiary of Reliance Industries Ltd, houses the group’s digital business assets including Reliance Jio Infocomm Ltd which in turn holds the Jio connectivity business — mobile, broadband and enterprise and also the other digital assets such as JIO Apps, tech backbone and investments in other tech entities like Haptic, Reverie, Fynd, NowFloats, Hathaway and Den Networks, among others. These investments range from video content, music, natural language processing, regional language technology and even e-governance.
  • The technology start-ups RIL and its subsidiaries have added to its fold have also boosted valuation.
  • The valuation is seen as testament to the kind of brand Reliance has managed to build out of Jio. Silver Lakes an investor is of course seeking to replicate their success with Alibaba once again. But a larger trend here is the network effect. With each successful partnership, Jio is able to grow in value and Facebook’s investment aided that strongly.
  • In fact, Jio, like Alibaba, announced the launch of a video-conferencing tool JioMeet, adding to its portfolio of apps and on track to build a super-app like its other Asian counterparts.
  • According to a recent report by Bank of America Global Research, from a monetisation perspective for super-apps across Asia, the focus is moving towards payments and commerce rather than just ads. The most successful super-apps case-study is Tencent’s WeChat in China, where within two years it has gained a 40% market share in digital payments, leveraging social/ payments to market more content and services to its user base.
  • This strategy can boost user engagement, strengthen content and service eco-systems, and offer monetisation options.
  • WeChat gradually shifted from acting as a traffic channel for other online content and services to becoming increasingly a platform that facilitates user activities and transactions without coming out of the app.
  • RIL have also proved their capacity in retail services so the growth trajectory with investments in startups and from backers like Silver Lakes is in the right direction even if very little of the technology is available on-ground presently.

Reliance Jio: World’s First ‘Super Operator’?

  • In the world’s second largest mobile market, Reliance Jio, India’s leading Communication Service Provider (CSP) or mobile operator, has taken the entire global ICT industry by storm with its vision and the most successful “serial” fund-raising over the last eight weeks. RIL with the launch of greenfield 4G network Jio in 2016, changed the entire competitive and technology landscape in India, amassing close to 400 million 4G subscriptions.
  • India went from 14 operators down to 4, with two out of the remaining four already on a life support and a third one reeling under debt, instantly offering Reliance Jio a monopoly position. A monopoly position married with serious money muscle and a clairvoyant vision to build a digital platform to empower and democratize technology in a country of 1.3 billion people, making it the most attractive company for any investor or stakeholder to partner with. It is called Jio Platforms.

Jio Platforms Needed Strategic Partnerships to Cross the Chasm

  • Jio, while amassing a healthy base of 4G subscribers consuming almost 13GB per month, has been still generating an ARPU of less than $2 per user. But to create stickiness, it has also build a platform full of services spanning Content, Commerce, Cloud and Communication, the four key pillars of any consumer’s digital lives. Jio has also vertical ambitions of own-branded devices and in-house development of network and data center elements as it already generated to much scale and has a strong buying power against suppliers. Having said that, the deeper capability, reach, execution and adoption of some of these OTT apps and services has been behind as it competes with bigger rivals. This has also led to Jio going in for acquisitions and a partnership route over the last year or so to help it build, integrate and execute this vision for its 400 million subscribers, tens of millions of businesses, hundreds of millions of households and beyond. There have been significant gaps in its platform’s capabilities to help push digital platform services and applications over the chasm. Though the vision is still great but needed investments and partnerships with scale and tech know-how. The slider graphic at the end of the post highlights the breadth of Jio Platforms but the capability to execute and adopt has been low to moderate.

$20 Billion Investments in Jio Platforms in Eight Weeks

  • With the world reeling with the COVID-19 pandemic, the demand for operator services has shot up, offering the right moment for Jio to announce a series of investments cum partnerships from the biggest technology companies such as Facebook, Google, Intel and Qualcomm, and investors such as Silver Lake, KKR, Vista, Saudi Arabia’s PIF, General Atlantic and TPG, which it has been working on for several months. Reliance raised $20 billion in just eight weeks, selling close to 33% stake, as valuation of Jio Platforms climbed to $90 billion, giving it the best funding round ever for any technology company. With this money, Jio has cleared all its debts, which include more than $11 billion to build its 4G network. The end-result: Jio Platforms is now debt-free, well-funded, has a clear vision and the monopoly status to become a ‘Super Operator’.

‘Super Operator’

  • Reliance Jio or Jio Platforms is transforming into a Super Operator which is no longer a dumb pipe. With a platform approach, it is laying a strong foundation to play a key role across the users’ digital lives and businesses’ digital transformation journeys. None of the operators we can think of globally promises to build, offer and control what Jio is capable of.
  • Jio’s strategic partnerships with key companies such as Facebook, Google and Microsoft, the three biggest tech giants, will help it drive Commerce, Communication and Cloud areas, respectively, where it had been weak in terms of capabilities, reach and adoption. Further, acquisitions such as Haptik (AI voice Assistants), Embibe (Education Content Platform), Reverie (Multiple Language Integration), Savvn (Music Streaming), Tesserect (AR/VR) and Radisys (Network Stack) bridge many capability gaps to foster in the upcoming 5G era.
  • With 5G around the corner, Jio can lay out a fully-controlled greenfield network to build the software stack via Radisys in fixed as well as wireless networks. It remains to be seen if there are any other big moves on the Radio Access Network (RAN) hardware side or it will depend on the long-term partner Samsung.
  • With Google, Jio aims to democratize 5G hardware with plans to offer the most affordable 5G Android smartphone in the market with the OS specially optimized for a low-cost 5G Jio smartphone. We estimate this to soft launch in Q4 2021 and proliferate through 2022 and 2023 with a target price point of sub-$100.
  • This is how the portfolio vs capability graphic looks with investments, partnerships and acquisitions to make the company a Super Operator. Though all eyes will be on Jio over the next five years on how it builds on its vision and helps generate great ROI for the investors and partners once it goes public and beyond the Indian shores.

The Battle Of Super-Apps: How Reliance Jio Plans To Overtake Paytm Using Paytm Itself?

  • The battleground for being India’s top super-app is set, the players in full form with funds from international giants pouring into the indigenous startups.
  • Super-apps have undoubtedly become one of the biggest influences on mobile-service startups worldwide. These super-apps are multipurpose apps that have finely integrated multiple functions like chat options, payment and financial services, online shopping and much more.
  • The progress and profits of the Chinese giants like WeChat and Alipay as have not gone unnoticed by the rest of the world
  • Apart from China, other nations are also leaving no stone unturned in developing these super-apps. Recently in Japan, Yahoo Japan’s parent Z Corp. merged with LINE, the most popular chat app in Japan, Taiwan and Thailand to develop super-app models for both brands.
  • In the Southeast Asia region, startups like Grab and Gojek are making their full attempts to develop themselves into super-apps by adding payment services, food delivery and more to their core ride-hailing functions.
  • In India, the country’s most valuable startup, Paytm valued at $16 billion has had an intent to be as a super-app. The app which is backed by both Alibaba Group and Softbank Group has added grocery shopping, banking and financial services, health care and food delivery services to its mobile payment app over the past few years.
  • However, posing the greatest challenge to Paytm as a super-app is the new Facebook’s deal with Jio. On April 21, Facebook announced a $5.7 billion investment in Jio, India’s youngest but biggest mobile operator.
  • A combination of the world’s biggest social network and India’s biggest mobile network is sure to overtake some of the other giants in many spheres.
  • The goal lies somewhere near India’s most popular app, Whatsapp which has about 400 million users.
  • It had only been less than a week after the announcement when the masses were thrilled to note that Jio’s grocery shopping service, JioMart, opened a business account on WhatsApp. As easy as it sounds, consumers are simply connected to JioMart through automated text messaging on WhatsApp.
  • Having been rolled out in only a few urban districts, it aims to find out if the concept of multipurpose apps or super-apps can target millions of Indians on the popular chat application.
  • Jio has previously been known to release a plethora of apps, in its short three-and-a-half-year history that includes video and music streaming, chat, payment services and health care.
  • The danger of Whatsapp’s link to Jio’s multitude of services hovers over Paytm. With shopping as well as payment services, the app will act like a super-app, leaving Paytm in a perilous position.
  • With about 350 million registered consuming users and 200 million monthly active users, Paytm is accepted at roughly 15 million merchants. It had gained enormous popularity after India’s demonetisation, now the impact is such that roadside vendors with a QR code posted at the shopfront also accept Paytm wallet money.
  • On the other hand, the JioMart endeavours to link as many as 30 million small-scale retailers to local Jio subscribers with free delivery as a consequence of which Paytm might be adversely affected.
  • The damage would not single-handedly carried by Paytm, as other apps like, the online grocery startups like Big Basket and Grofers, as well as Dunzo, which provides “errand” service for residents in many cities will also be dented.
  • In the current dire times of the pandemic, online platforms like Amazon and Flipkart which are rampantly strengthening their grocery services, as groceries and medical items are the only things that the government allows to be delivered, will be challenged to their core.
  • Businesses will further accelerate the pace of their digital activities in 2021 by creating new-age apps and platforms and the world will see this battle ratcheting up in intensity in India led by Reliance Jio Platforms.

Facebook’s investment in Jio Platforms is likely to pave the way for a super app in the mould of WeChat

  • Integrating SME sellers into an app and scaling up the app’s service portfolio may allow Facebook and Reliance Jio to gain a substantial share of consumer attention.
  • In late April 2020, Facebook announced its intention to invest INR435.74 billion (USD5.7 billion) for a 9.99% stake in Jio Platforms (the parent company to Reliance Jio, India’s leading mobile operator) and, in a related move, to link up WhatsApp and JioMart (Reliance Industries’s click-and-collect e-grocery platform). This tie-up presents the two players with a joint opportunity to launch a super app (as reported by insider sources)1 that can help to mobilise India’s growing digital economy. The effects of this deal on other Indian telecoms operators and the broader digital sector in India are likely to be significant. We review the drivers of this deal and the potential impact on telecoms players and others.

Facebook’s investment in Jio Platforms will make it possible for both parties to launch a super app together

  • Facebook’s investment in Jio Platforms in April 2020 coincided with the launch of a partnership that links Reliance Industries’s JioMart and Facebook’s WhatsApp. This partnership allows WhatsApp users to access the JioMart app via a dedicated WhatsApp number. After making a purchase on the JioMart app, WhatsApp users will receive an invoice and the seller’s location via WhatsApp before collecting their order.
  • There are various reasons behind Facebook’s tie-up with Jio Platforms.
  • Facebook’s investment in Jio Platforms and the JioMart–WhatsApp partnership mark a step towards Facebook and Reliance Jio pooling their user bases (388 million Jio subscribers and 400 million WhatsApp users in India) and resources to launch a super app on a scale comparable to Tencent’s WeChat. Both Facebook and Reliance Industries have stated their intention to focus on digitalising India’s substantial small and medium-sized enterprise (SME) sector. RIL has also identified healthcare and education as future areas of collaboration with Facebook. Integrating SME sellers into an app and scaling up the app’s service portfolio to include services beyond communications and e-commerce can, if successful, allow Facebook and Reliance Jio to gain a substantial share of consumer attention, which will create further service and revenue opportunities in the future.
  • Facebook’s acquisition of a stake in Jio Platforms represents an opportunity for Facebook to gain more exposure to a fast-growing emerging market and, in particular, to India’s digital sector in which Reliance Jio plays a key role. It is also an opportunity for Facebook to deploy capital from its large cash pool (USD54.9 billion as of 2019). Most importantly, Facebook’s investment may give it an easier way into the Indian market. Facebook has had limited success in India; its most prominent venture, Free Basics (which offered free access to certain websites) was banned by the regulator in 2016 for violating net neutrality rules. Investing directly in India (especially at a time of COVID-19-driven economic hardship) suggests a firm commitment and can help win Facebook political capital to aid its business activities.
  • For Reliance Industries, selling a stake to Facebook is part of a drive to raise equity and deleverage. Reliance Industries intends to eliminate net debt whihc it has, and since Facebook’s stake acquisition it has also sold equity stakes in Jio Platforms to investment funds Silver Lake, Vista Equity Partners, General Atlantic and KKR to raise cash. Facebook’s investment also enables Reliance Industries to welcome a global digital innovator as a partner.
Figure 1: The individual and collective drivers behind the deal between Jio-Platforms and Facebook in April 2020

Reliance Jio and Facebook can together attract a substantial share of consumer attention

  • The impact on the telecoms market in India and the broader digital sector is potentially significant. For Reliance Jio, opening up its services to new customers may lead to revenue gains. Increasing its service range — or ultimately operating a super app — can help Reliance Jio to reduce mobile churn and to further build mobile ARPU, which stood at INR127.01 (USD1.83) as of 2019–10.1% above the market average. The tie-up with Facebook is also a boost to Reliance Jio’s ambitions as a B2B digital enabler and a digital lifestyle company. This move is likely to put pressure on Jio’s competitors, but it is not clear what impact it will have on the level of mobile market competition as a whole in India, which is increasingly an area of concern given Vodafone–Idea’s financial troubles.
  • This deal enables Facebook to realise its ambitions to have a stronger presence in India, but it remains unclear what relationship it will have with local authorities. The forthcoming Personal Data Protection Bill in India may impose high compliance costs relating to data localisation among other things. Furthermore, local sources report that the government in India is mulling new taxes for big tech companies. At the same time, in addition to gaining a useful local partner in Reliance Industries, Facebook will have won some goodwill from local authorities given the timing of its investment and the way that its aims correspond with the government’s ‘Digital India’ vision. The key, as-yet unanswered question is whether these new advantages will be sufficient to enable Facebook to operate its business with limited regulatory obstacles.

The benefits of this move will take time to materialise, but other operators in India and elsewhere may seek to partner with big tech

  • Facebook’s investment in Jio Platforms provides an interesting example of a big tech company investing in a telecoms company. Elsewhere, big tech companies typically compete with telecoms operators. India is a relatively unusual case because of the significant growth opportunities for the digital economy as well as the role that telecoms operators such as Reliance Jio play as central enablers of the digital economy. Operators in other countries are likely to view partnerships with tech companies as attractive, but the opportunities to form such partnerships are potentially more limited. It is not yet clear how Reliance Jio’s competitors will respond. To compete more effectively, a similar tie-up with a technology company is likely to now be higher on the agenda of Indian telecoms operator Bharti Airtel (Airtel), which has clear ambitions in both the financial services and digital services sectors, and Vodafone Idea.

The India Super App: here are the broader implications of the Facebook-Reliance Jio deal

  • In an ambition to build an India Super App, Reliance Jio has partnered with Facebook. The US social media giant is investing Rs 43,574 crore ($5.7 billion) and acquiring about 10 percent equity in Jio Platforms, consisting of several Jio apps.
  • This is indeed a notable deal, which may transform into something similar to the Chinese super app — WeChat. The app is owned by Tencent Holdings that has integrated “apps within app” and provides payment, ecommerce, taxi aggregator services, and food ordering. This is via around a million third-party apps that run on its platform.
  • The Jio platform includes apps like Jio TV, Jio Saavn (music streaming), Jio News, Jio Cinema (video streaming), Jio Cloud, Jio TV+, Jio Health Hub, JioMoney (payment app), RJio (ecommerce), and others.
  • The Jio Platform also has several tech capabilities like Big Data, Blockchain, and Internet of Things (IoT). In addition, the group is into the business of wired broadband (JioFibre), apart from providing 4G internet and VoIP (i.e. Internet Telephony) services.

A giant digital ecosystem

  • More so, as announced, a new model of the ecommerce app JioMart is soon going to be launched. If these app services are combined with Facebook and WhatsApp, and their 400 million Indian users and their data, the field is wide open to present a giant digital ecosystem. So much so, that this deal can result in India’s first globally competitive national champion digital firm.
  • By playing a technology-based intermediation role, the resulting Super App will decrease search cost for the users for any services that they want to avail of. A recurring theme of technology-enabled marketplaces has been the creation of greater economies of scale — cost advantages that business enterprises get as the amount they produce or transact grows. A Super App will enable the same, thus reducing costs for business that transact through the app.
  • The network effects of the Super App are also very high, thus, increasing user loyalty and increasing the switching cost. This leads to a winner-takes-most, resulting in monopolisation or anti-competitive arrangements in the digital space. Excessive market power can potentially threaten consumer welfare.
  • Thus, a close regulatory oversight and aggressive market power assessment are needed to avoid anti-competitive practices such as predatory pricing, cartelisation, and abuse of dominance. Noting, however, that it is not the dominance itself, but its abuse that is a problem.
  • For this, both Competition Commission of India (CCI) and the Telecom Regulatory Authority of India (TRAI) are working together. They will inter alia propose ex-ante measures/conditions so that the chances of such abusive practices are limited.
  • Although, with the presence of retail giants like Amazon and Flipkart, it is more likely that there will be intense competition in the retail sector. Similarly, various streaming services, such as Netflix and Amazon Prime, which have made deep inroads into Indian audiences, will be able to compete with Jio’s streaming and content businesses.
  • The biggest threat seems to be on the telecom players like Airtel and Idea-Vodafone, which can further loose subscribers due to various bundled services provided by the Super App. Thus, it is likely that there will be further stress in the telecom sector, which could lead to ouster of existing players. If this happens, it would be a serious competition problem in the telecom sector.
  • The above-said ex-ante measures could also include the introduction of platform-to-business (P2B) regulation that could ensure platform neutrality on the part of the supper app. This can ensure non-discriminatory treatment to all the business attached to such a platform.
  • This is also necessary because the foreign direct investment (FDI) rules, which tend to ensure platform neutrality on the part of e-commerce platform dealing in multi-brand retail, will not be applicable to the domestic giant that is emerging. If such P2B regulation is not introduced, the same will not only result in clear-cut policy discrimination between foreign and national platforms, but can also harm small online suppliers on the platform.

Net Neutrality

  • Another important issue with the Super App is its effect on Net Neutrality. Under zero rating, a mobile operator or telecom service provider (TSP) could provide access to a portfolio of content and applications provided by a set of Content and Application Providers (CAPs) free of any bandwidth charge to the end user, while access to other content and applications would be charged differently. Evidently, the TSP’s cost of providing services within the free portfolio would be subsidised by the CAPs.
  • The possibility of such differential pricing by the TSP would enable a CAP with deep pockets to get preferential access to the TSP’s subscribers, violating the principle of net neutrality. Though this has been accepted in some countries, for instance the Philippines, the TRAI has issued prohibition of discriminatory tariff notification and disallowed such schemes since 2016. With the close partnership between a TSP and CAP, in this case, there is a possibility of a variation of zero rating emerging and the regulator has to watch out for the same.
  • Along the same lines, there can also be prioritisation of traffic of those apps and services provided through the Super App. TRAI, through its recommendations and later enacted by DoT, prohibited unreasonable traffic management practices that differentiates native apps vis-à-vis other apps that are not provided through the Super App.
  • While in the short run, consumers and users may boost the emergence of a swadeshi giant and may also enjoy more freebies from the Jio Super App, in the long run this may lead to a highly monopolistic digital ecosystem that would greatly influence consumer behaviour and could also be a threat to the democratic political process.
  • While the government has the requisite regulatory tools in place, this acquisition warrants a re-visit of the competition and Net Neutrality regulation to make sure that consumer and industry welfare are ethically preserved.

From pipes to platforms: Leveraging the network effect

  • network effects, which when a company gets them right, make platforms super successful — and faster than anything the business world has ever seen. How can network operators benefit from network effects and create new value?
  • Look at the table below and the first thing that shocks is how fast these platform-based companies grew, especially when compared to their venerable ‘counterparts’. No wonder so many long-established businesses are reeling.
  • The world’s biggest five companies by market capitalization are all platform companies. Apple, Alphabet (Google’s parent), Microsoft, Amazon and Facebook have displaced the oil companies and banks that held the top slots for decades.
  • How do successful platforms grow so fast? Through network effects, which every business needs to understand and foster. This is how it works: the more people are on your network the more valuable the business and the more effective you are.

What’s going on?

  • In the pipeline model, there is little in the way of network effects. Instead there is a supply chain, from raw materials to distribution. At every stage someone is paid for their contribution, and the value accrues as the process progresses. The sale price has to be bigger than the overall cost for everyone to make their margins, but there is little in the way of the network effect.
  • The platform model collapses that process, creating what Parker calls a triangular platform (see graphic), whereby the platform provides a marketplace for interchanges between producers and consumers. It removes pain points for both and enables all kinds of companies to create new services and value — and especially small ones that could never afford the resources and upfront capital costs on their own.
  • YouTube and Apple are both great examples of this. YouTube offers tools to help producers upload videos easily and quickly. On the consumption side, there is search, matching, filtering, playing and sharing. The platform deals with all the different standards and devices, to create markets that didn’t previously exist and run various business models on one platform.
  • In January 2017, Apple stated that in the previous year, app developers collectively earned over $20 billion. On average, the company gets about 30 percent of that as revenue share.
“The platform provides a marketplace for interchanges between producers and consumers. It removes pain points for both and enables all kinds of companies to create new services and value.”
“Platforms drop transaction costs like a rock. Whereas you used to need an army of lawyers to get anything done, now it’s plug and play.”

Who can play?

  • Can any product or service become the basis of a platform business? If a firm can either use information or community to add value to what it sells, then there is the potential to create a platform. This means there is a huge amount of opportunity for a lot of companies.
It’s [already] a $4 trillion market. Today, no telco operates like this, yet we have all the assets and capabilities to do so.

8 things to consider

Telcos inherently understand the network effect — the more people are on your network or you can connect to someone else via partners, the more valuable your business and the more effective you are. We created a global network for telegraphy then phone calls more than a century ago, we can replicate this for digital services. Here’s how.

  • Forget Facebook: The B2C market is largely done, we need to look towards the internet of things, smart cities and medical technologies — the B2B side. That is an $80 trillion global economy that is rapidly digitizing and the B2C stuff is an itty-bitty side show by comparison. There is huge opportunity to be there first.
  • Don’t customize, configure: Be modular is the approach TM Forum enshrines in all its assets and activities. The mantra is build open, standardized, reconfigurable systems and avoid customization. Many telcos are moving towards this ideal to reduce costs, risk and time to market, and increase their business agility while leveraging assets.
  • Gain global reach: Telcos can exploit that modularity to scale by partnering with other telcos to gain geographical reach if everyone uses open APIs. Put the complexity behind the scenes and have something that’s easy to attach to and pass data between.
  • Look outside: Shift attention from inside to outside the company because that’s where your users and partners are who create transactions, which is how you monetize your network. To have an external focus you must have a community strategy.
  • Cherish your community: Design architecture to regulate participation — troublemakers are a fact of life, but control points in the analytics can detect them and prevent them driving others away. Put another way, promote positive interactions among partners in a multi-sided market.
  • Design your business model carefully, around all your customers: Don’t introduce too many adverts, for instance. That killed MySpace stone dead because it spoiled the user experience. And don’t introduce too many onerous steps to access the platform and services, it will repel users.
  • Resource orchestration, not control: In the platform world, not everything is counted nor appears on the balance sheet. Resources need orchestration as the aim is to provide a market for excess capacity that previously could not be traded. The question is, “How can we lower transaction costs so that the capacity we’ve got sitting on our balance sheet can find a market?…It’s not about locking everything down, it’s about opening it up, which is a completely different mindset.”
  • And finally: Move from focusing just on serving that one end customer…and bargaining against a supply chain, [instead] look at the customer as an inside user and treat them as such. Thinking in terms of a dollar in the supply side’s pocket is one less in yours doesn’t work — it becomes meaningless. Rather invest in their ability to produce because that drives transactions, which is how you monetize your network.

Reverse Network Effects: Why Today’s Social Networks Can Fail As They Grow Larger

  • Network effects are the holy grail for Internet startups looking for venture-scale returns. On a platform with network effects, the value to a user increases as more users use it. Facebook, Twitter, LinkedIn, YouTube, Skype, WhatsApp and many others benefit from this dynamic.
  • In an age when more than a billion people connect over a network and new networks reach multi-billion dollar valuations with a handful of employees, one is tempted to believe that online networks are almost fail-proof. But as online networks grow to a size never seen before, many question their sustainability and believe that they are becoming too large to be useful.
  • To explore the future of online networks, it’s important to note how network effects correlate with value and the factors that make these network effects work in reverse.

Network Effects and Value

  • There is a strong correlation between scale and value in businesses with network effects. Greater scale leads to greater value for users, which in turn attracts other users and further increases scale. This rich-becomes-richer dynamic allows networks to scale rapidly once network effects set in.
  • There are three sources of value created on networks: Connection, Content and Clout.

Connection: Networks allow users to discover and/or connect with other users. As more users join the network, there is greater value for every individual user. Skype and WhatsApp become more useful as a user’s connections increase. and LinkedIn become more useful as more users come on board.

Content: Users discover and consume content created by other users on the network. As more users come on board, the corpus of content scales, leading to greater value for the user base. Content platforms like YouTube, Flickr and Quora, as well as marketplaces like AirBnB and Etsy becomes more useful as the number of creators and the volume of content increase.

Clout: Some networks have power users, who enjoy influence and clout on the network. Follower counts (Twitter), leaderboards (Foursquare) and reputation platforms (Yahoo Answers) are used to separate power users from the rest. On networks like Twitter, the larger the network, the larger is the following that a power user can develop.

Across these three drivers, a network with greater scale provides greater value in the form of:

  1. More prospective connections for the user
  2. A larger corpus of potentially relevant content
  3. Access to a larger base of potential followers (greater clout), for power users

On most networks, value for users is created through more than one of these three sources. Facebook, for example, started with a value proposition centered around connection, but the introduction of the news feed has made content a central driver of value. In recent times, the addition of the subscribers feature has added clout for some Facebook users as well.

Why Network Effects Work in Reverse

One would expect that the bigger the network, the more value users derive from it.

However, as networks scale, the value for users may drop for several reasons:

  1. Connection: New users joining the online community may lower the quality of interactions and increase noise/spam through unsolicited connection requests.
  2. Content: The network may fail to manage the abundance of content created on it and may fail to scale the curation of content created and the personalization of the content served to users.
  3. Clout: The network may get inadvertently biased towards early users and promote them over users who join later.

Just as network effects create a rich-becomes-richer cycle leading to rapid growth of the network, reverse network effects can work in the opposite direction, leading to users quitting the network in droves. Friendster, MySpace and Orkut bear testimony to the destructive power that reverse network effects wield.

Reverse Network Effects: Connection

  • Connection-first networks (dating websites like and networking communities like LinkedIn) build value by connecting people.
  • These networks may suffer from reverse network effects as they scale if new users joining the network lower the value for existing users. To prevent this, an appropriate level of friction needs to be created, either at the point of access or when users try to connect with other users.
  • On dating sites, women often complain of online stalking, as the community grows, and abandon the site. Sites like CupidCurated have tried to solve this problem by curating the men that enter the system, in a manner similar to restricted access at a singles bar.
  • LinkedIn creates friction by preventing users from communicating with distant connections. This ensures that users do not receive unsolicited messages. This also allows LinkedIn to offer frictionless access (OpenMail) as a premium value proposition.
  • ChatRoulette, in contrast, anonymously connects users over a video chat without needing to login. This lack of friction led to ChatRoulette’s stellar growth but also led to reverse network effects as anonymous naked hairy men took to the network, thus increasing noise and driving genuine users away from it.
  • Dating sites, as well as social networks like Orkut, have imploded in a similar manner after reaching scale, owing to noise created by fake profiles.
  • In general, networks of connection scale well when they create appropriate barriers to access on the network.

Reverse Network Effects: Content

  • On content networks like YouTube or Flickr, a larger network is likely to have more content creators, leading to more content for the user to consume. Networks like Facebook and Twitter, in addition to being networks of connections, are also networks of content.
  • Most networks of content have low friction in content creation to encourage activity from users and reach critical mass faster. To ensure that the content is relevant and valuable, the network needs strong content curation and personalization of the user experience.
  • Reverse network effects set in if the content curation systems don’t scale well. As more producers create more content, the relevance of the content served to consumers on the network shouldn’t decrease.


  • Content networks create a curation mechanism through a combination of moderation, algorithms and community-driven tools (voting, rating, reporting etc. ). Voting on YouTube, flagging a post on Facebook and rating on Yelp are examples of curation tools.
  • Curation mechanisms often break down as the volume of content increases. When curation algorithms and moderation processes do not scale, noise on the system increases. This leads to reverse network effects and users abandoning the system.
  • Quora has a very strong curation mechanism in place and benefits from a tech-savvy early user base. As Quora scales, many worry that less sophisticated users, entering the system, may increase noise leading to a rapid depletion of value for existing users. It remains to be seen whether its curation can scale as the network opens up to a broader user base.


  • Content networks need a personalized consumption experience for users, that serves them relevant content.
  • An example is the news feed on Facebook or Quora or the recommendation system on YouTube.
  • Inability to maintain relevance of the consumption experience, with scale, may create reverse network effects.
  • The user experience on Facebook is centered around the News Feed. However, Facebook’s frictionless sharing and cluttered news feed may lead to lower relevance for users as the network scales. Several factors contribute to this:
  1. When a user adds friends indiscriminately, her news feed becomes cluttered with irrelevant posts.
  2. Noise is further increased when marketers and app developers get access to the news feed.
  3. When networks like Facebook and Twitter implement monetization models like Promoted Posts/Tweets, the signal to noise ratio suffers further as promoted content is less relevant than organic content.

Networks of content are constantly faced with the risk of reverse network effects as they scale. The poor signal-to-noise ratio in the news feed, not the size of the overall network, is Facebook’s weakest link as the network scales.

Reverse Network Effects: Clout

  • Networks of clout have a system of differentiating power users from the rest. Twitter, Quora and Quibb have baked in clout through the one-sided follower model. Active users vie for greater glory while using the network.
  • Networks of clout tend to be biased against users joining in late. Clout is a consequence of content that the user creates and early users get more time to create content and develop a following.
  • This is, ironically, aggravated by focusing on a high signal-to-noise ratio. Twitter recommends super users to prospective followers as these users are likely to create better content. Hence, the platform itself helps separate the power users from the rest.
  • Users who join later find it more difficult to develop a following and may stop using the network. These networks need a mechanism to ensure new users have equal access and exposure to the community to develop network clout. 500px, for example, differentiates Top creations from Upcoming creations to expose recent activity (often from undiscovered users) to the community.

Reverse network effects often cause a large and thriving network to implode. As a network scales, it’s ability to maintain a high signal-to-noise ratio is the leading indicator of its usefulness. Networks can, in fact, scale very well and prevent reverse network effects from setting in if they have

  1. Appropriate level of friction in network access and usage, that prevents abuse
  2. A strong curation system that scales well with the size of the network
  3. A highly relevant and personalized user experience
  4. A democratic model for users to build influence

Networks that have excelled in the above have scaled well. In a world where networks are reaching unprecedented scale, a keen focus on maintaining a high signal-to-noise ratio will enable them to remain valuable and effective as they grow.

16 Ways to Measure Network Effects

  • Network effects are one of the most important dynamics in software and marketplace businesses. But they’re often spoken of in a binary way: either you have them, or you don’t. In practice, most companies’ network effects are much more complex, falling along a spectrum of different types and strengths. They’re also dynamic and evolve as product, users, and competition changes.
  • For founders, it’s important to understand the nature of your company’s network effects — including deciding on the set of metrics that help you understand what’s working or not. So, building on previous metrics lists , we’ve compiled a list dedicated to measuring and teasing apart network effects in particular. We share them below, divided into 5 main categories to measure network effects: acquisition, competitors, engagement, marketplace, and economics-related metrics.
  • Every single network effect business is different depending on the particular product, audience, and environment, so there’s no-one-size-fits-all list of measures. In general, however, for two-sided marketplaces matching supply and demand, pay special attention to the marketplace and unit economics sections; for social networks (including workplace ones), what matters most is engagement and activity. In the end though, it all comes down to the very definition of network effects: whether your product becomes more valuable as more people use it. Because only then can you go about creating and growing that value for users, and for your business.

Acquisition-Related Metrics

- #1 Organic vs. paid users
What percentage of your new users are organic?

  • In a business with network effects, the share of organic users relative to paid users (the ones you spend to acquire) should increase over time. This is because as the network grows and becomes more valuable for users to join, more users should want to join on their own.
  • For companies with direct-side network effects (also called demand-side increasing returns), such as Facebook, the organic share will grow as people get their friends to join the platform — because their own experiences also improve as a result. For two-sided marketplaces such as Airbnb, eBay, and others, the organic share of new users grows as more suppliers (housing, sellers) and buyers want to join the network to get access — because of the potential revenue and variety of choice there.
  • To be clear, this doesn’t mean that paid acquisition is a bad thing; many companies including the likes of Facebook and Uber spend money to acquire new users, especially in new markets. But any company seeking to grow a sustainable business will reduce their share of paid acquisition once they reach a critical mass of users. Bottom line: as any network grows larger and its value to users grows, it should become less dependent on paid acquisition.
  • But there is a second layer of subtlety here, which is defining the relevant denominator of users for which the organic portion should be expanding. The right answer depends on the product and the use case: a company that has local network effects — for instance, for finding home-service providers nearby vs. globally — will show increasing organic new users, but only on a geography-by-geography basis. For small social networks designed to be used within a specific setting (like a school), the % organic should increase at the atomic unit of that particular network (i.e., the school).

- #2 Sources of traffic
As the network grows, how much traffic/transactions on the network are generated internally, arising from the network itself vs. from external sources?

  • Just as valuable networks should organically draw more users, valuable networks should also become a destination — where users want to spend more time on the platform (or marketplace).
  • Measuring traffic sources is one way to help tease this apart, by separating — and tracking — how much traffic or transactions on the network is direct vs. arises from external sources. More traffic coming directly suggests users are finding the network more valuable over time as it grows.
  • A useful example to think about here is OpenTable, an online restaurant reservation company; initially, the typical user flow through the then-small network would be: outside research or discovery of a restaurant > decide on a restaurant > go to that restaurant’s website > book a reservation through their OpenTable widget
  • As OpenTable’s network grew, it became more useful to users, since users could see the availability of every participating restaurant, vs. a specific restaurant through its own website. The share of direct traffic increased as users started their discovery process on OpenTable: research or discover restaurant on OpenTable > decide on a restaurant > skip the restaurant’s website and book a reservation directly on OpenTable
  • A similar example is Medium: as the network grew and there was more content to read and more writers to follow, a greater percentage of read time originated from within the Medium site. These are also both classic examples of “come for the tool, stay for the network” type businesses.

- #3 Time series of paid CAC
How much do you need to spend to acquire supply?

  • While paid CAC (customer acquisition cost) should theoretically decline over time in a business once the network effects “flywheel” starts accelerating, in reality, this also depends on a number of other factors: the competitiveness of marketing channels like Facebook, where prices can increase with more demand from more advertisers; the availability of substitute products; viral loops; and so on.
  • For example, with ridesharing, there are a variety of substitutes available to drivers — the more constrained side of the market — which has made it more expensive over time to acquire that supply. But with a company like OpenTable, which aggregated demand onto a single platform, it became cheaper to acquire restaurants over time.
  • By the way: it’s common to confuse network effects with virality, but the two concepts are different. Network effect businesses refer to increasing value of the product/service with each incremental user. And while network effect businesses often have a large viral growth component, which can impact CAC, the two concepts are not the same. Viral growth (users inviting other users) can exist in a non-network effect business. So, companies that are great at viral growth but don’t have network effects can grow quickly but flame out just as fast.

Competitor-Related Metrics

- #4 Prevalence of multi-tenanting
How many of your users also use other similar services? How many users are active on similar services?

  • It’s important to understand whether your users are also using similar services, including related services where the functionality may not be exactly the same.
  • We’ve often observed that if a company is able to replicate a network, it can also layer on functionality that can obviate the need for another product. Even if it doesn’t wipe out the target company, such multi-tenanting can reduce usage and compress margins for all competitors. A marketplace for dog walkers and pet owners, for example, has the opportunity to move into pet health or food or other adjacent products, given it has built a network of pet owners from the core business. Facebook developed ephemeral Stories and added this feature into their various apps, including Instagram, in turn stymying the growth of Snapchat.
  • Measuring such multi-tenanting can be tricky — it might mean polling your users and asking whether they use another service; digging deeper into churn or declines in usage (and figuring out whether those users are moving to a different service); or simply brute-force searching for users’ profiles on other platforms! But once you see how many users are multi-tenanting, there are ways to shore up your product so users are less tempted to go somewhere else. In ride-sharing, for example (which had high multi-tenanting on both sides), companies rolled out subscriptions on the rider side and bonuses on the driver side to boost retention and reduce usage of competitors’ services.
  • Finally, even if you have a good sense of the overlap between your user base with another service’s, it’s important to consider how active they are: are they merely maintaining a profile, or actively using it? Having a LinkedIn profile is ubiquitous among professionals, but knowing if those users are active or not is important to know for a new startup trying to create a professional services network, so they could target areas where those users are not served well by the current product. This is a common strategy for networks to “Trojan Horse” their way into building a competing network from the underserved segment of the market first.

- #5 Switching or multi-homing costs
How easy is it for users to join a new (and even a non-existent) network? How much value can users get as a new user from joining a different network?

  • Beyond the availability of substitutes, how easy it is for users of one network to sign up and complete the onboarding process for a competing network?
  • The friction involved in signing up and becoming an active user varies from product to product. Products that have an onboarding process that requires high upfront investment may find it challenging to activate prospective new users — but it also serves as a moat against competitors, because once those users are active, they’re less likely to multi-tenant. Looking at the landscape of online personal styling services, a Stitch Fix customer for instance may find it tedious to try out a different service because of the upfront investment in explaining her preferences to a new stylist; inputting information around her taste and sizing; calibrating various styles received and returned; and so on.
  • Conversely, if a product has a lower activation energy required of new users, it can more easily wedge its way into a market by getting users to multi-tenant and switch over: Because Uber already had millions’ of users’ credit card information for ride-sharing purposes, a user who was previously using another food delivery network could easily start using Uber Eats without much friction.
  • Another important consideration here is how much value can users get at the beginning when they join a new network — what’s the user experience with a cold start? For Facebook, even though users can easily join other social networks, their data, content, and networks are all on Facebook, so there’s high switching costs to inviting their network and rebuilding their social graph. On the other hand, for job listing marketplaces, an employer can easily upload their hiring specs to multiple sites and start receiving candidate applications from the get-go.
  • Distilling switching or multi-homing costs into a quantifiable metric can be tricky, and any metric will be quite specific to that exact business and market. Potential metrics could be the time required to complete a competitor’s onboarding flow; or the ease of getting to the minimum threshold or “magic number” for a product to be useful (e.g. 10 friends for Facebook); and so on.

Engagement-related Metrics

- #6 User retention cohorts
Is your user retention improving for newer cohorts?

  • The classic definition of a network effect is that the value of a product or service to a user increases with the number of other users using the same product or service. This increase in user value should therefore be reflected in user retention cohorts: newer cohorts (who experience a product when the network is larger and more useful) should have better retention for any given time period than older cohorts that joined when the network was smaller.
  • However, theory often differs from reality here, and we often see businesses that have declining cohort retention over time. This is because a major confounding factor to consider when evaluating user retention (metrics #6-8 on this list) is that the oldest user cohorts — especially for social network/community-based products — tend to be early adopters who are the most “ideal customers” for a product/service. Those early, often highly motivated users naturally translate into better retention cohorts for the oldest customers, rather than the newest.
  • Other circumstances can also change the analysis of this metric: the presence of a competitor; network effects that are hyperlocal and thus “reset” for new users in every new geography; or even negative network effects, where value to users actually decreases at a certain threshold (perhaps due to crowding or contaminants in the network).

- #7 Core action retention cohorts
Is retention, as defined by users taking a core action for the product, improving for newer cohorts?

  • Digging deeper into the engagement funnel, you want to see if more users are taking the “core action” of your product. The core action can be one that actually corresponds to users deriving value from your product, and/or something that maps closely to your business model.
  • For instance, if the core action of Nextdoor is users posting content on neighborhood newsfeeds, then as the network density grows, they should expect to see improving retention as anchored on this core action. This core action retention is more telling of network effects than just measuring top-level logins or app opens.

- #8 Dollar retention & paid user retention cohorts
Are newer cohorts retaining better on a dollar basis, for every given time period, than older cohorts?

  • Subscription and paid products need to pay attention to dollar retention and paid user retention. New user cohorts should be better retained — in terms of cohort revenue — than older cohorts. Why? Because paying for a product indicates how much users value that product, a product with network effects — which becomes more valuable over time — should have increasing dollar retention and paid user retention among newer cohorts.
  • For instance, as the network coverage of Angie’s List — a home services directory — improves, we’d expect to see that new user subscriber cohorts are better retained, both in terms of dollar retention as well as the number of users who remain subscribed, given the greater utility of the site.

- #9 Retention by location/geography
Are participants in the oldest markets — for businesses with local network effects — better retained, than those in newer markets?

  • For local network effect businesses, the network effects exist on a per-market basis, and “resets” for new geographies. For users in Charlotte, for example, the presence of more babysitters available in New York City doesn’t impact the user experience; but having more babysitters available locally does improve the usefulness of the network there.
  • As each geography matures and builds network density, retention should improve in those markets. Thus, the oldest or most established markets tend to have better retention than newer markets. We see this in practice in data shared by almost every local network effect business.

- #10 Power user curves (aka L7 & L30 charts)
Are users shifting to the right side of the power user curve? In other words, are they becoming more engaged over time?

  • Power users drive some of the most successful companies, by contributing a ton of value to the network. While DAU/MAU — dividing daily active users by monthly active users — is a common metric for measuring engagement, it has its shortcomings, and power user curves provide a more nuanced way to understand user engagement.
  • In short, power user curves (commonly called L30 charts for 30 days of use, or L7 charts for 7 days of use) are histograms of users’ engagement, showing the total number of days users were active in doing a particular action in a given timeframe. In analyzing network effect businesses, seeing how often users take a specific action on a cohort basis allows you to see whether a product is really gaining utility with more users — aka the network effect. If a product is indeed more valuable with more users, then that should be reflected in a growing share of users shifting to higher-frequency engagement buckets, or a more right leaning power user curve, over time.

Marketplace Metrics

- #11 Match rate (aka utilization rate, success rate, etc.)
How successfully can the two sides of the marketplace find each other?

  • The job of any marketplace is to facilitate the matching of supply with demand. It’s therefore important to measure your successful “match rate” — the rate at which buyers can find sellers, and vice versa. How to define this metric depends on the unique business.

Match rates examples for particular businesses include:

  • Driver utilization time for ridesharing — what % of the time are drivers driving around with a passenger, vs. empty?
  • How often are employers actually filling their posted role in job marketplaces? And how often are job seekers finding jobs?

A related metric is to measure “zeros”, or unsuccessful matches. For ridesharing, what percentage of users open the app but don’t end up requesting a ride? Those “zeros” could be due to too long of a wait time, surge pricing, or something else — all instances the marketplace was unable to clear demand. Marketplace operators should identify reasons why matches don’t happen and take steps to remove or reduce these blockers through growing and incentivizing the more constrained side of the marketplace, improving product design, and other mechanisms.

  • This metric is also closely related to the concept of multi-tenanting described above. If match rate is low, then users will naturally be incentivized to go elsewhere and use other products. For instance, it’s common for employers to post their job listings on a variety of sites — their own website, LinkedIn, Indeed, as well as other networks — simply because no single network has a high enough match rate. If there’s even incremental revenue potential or even just minimum utility, multi-tenanting will take place; just think about all of the delivery marketplace stickers you see in any given restaurant’s window!

- #12 Market depth
Is there enough supply and does it fit users’ needs?

  • The concept of “offer depth” or market depth originated from financial markets, where it’s defined as the market’s ability to sustain relatively large orders without price movements. The higher the number of buy and sell orders at each price, the greater the depth of the market.
  • For consumer marketplaces, it’s important to measure market depth because it directly impacts the user experience. For heterogeneous supply marketplaces (where each supplier is different), market depth determines whether users will be able to find a match. When users open products like OfferUp or Airbnb, how many listings will they see, and how likely will they be to find an item they want to buy or home they want to rent? For homogenous supply marketplaces, marketdepth impacts ease of use. When users open Lime, how many bikes/scooters will they see near them? The greater the market depth, the easier (and less user effort required, in terms of walking) it is to use Lime.
  • One of the primary jobs of any marketplace business is to reduce search costs — making it easy for participants to find and match with the other side. Failing to do this can result in a marketplace with negative network effects, where too much supply actually causes challenges in discovery. As consumers, we experience this as decision fatigue, or a paradox of choice. Conversion rates could fall in this scenario.
  • A note on heterogeneous vs. homogeneous supply: “homogeneous supply” marketplaces typically hit an asymptote in network effects, where the value to users eventually plateaus with greater market depth. For instance, if there were 6 Lime scooters on a city block near me, this is no more valuable than if there were only 4 or 5 scooters available for me to use in my vicinity — user value is unchanged despite the addition of more supply. On the other hand, for heterogeneous marketplaces, there is no asymptote because every node on the supply side is different and potentially can add greater value. In the Airbnb example, a user’s tastes may be quite specific, so every additional listing on the platform is useful to see.

- #13 Time to find a match (or inventory turnover, or days to turn)
How long does it take for supply and demand to match?

  • Typically, marketplaces have a curve for match rate, where over a long time horizon, a greater share of inventory clears. For product marketplaces, this is commonly referred to as inventory turnover.
  • The inverse is days to turn, and this metric is more applicable for more traditional marketplaces, where the matching happens via users opting in — one side creates a listing and the other responds — in contrast to on-demand marketplaces, which do matching in a centralized, algorithmic (and less visible to users) way.
  • For instance, for job marketplaces, how long does it take an employer to find an employee? How long does it take to receive the first application? For P2P marketplaces, how long does it take for each side to engage in a transaction? For Thumbtack, how long does it take users to receive the first quote? How long does it take on OfferUp for a seller to sell their product?

- #14 Concentration or fragmentation of supply and demand
How concentrated is the marketplace on the supply and demand sides?

  • Marketplaces where there is greater fragmentation on the supply and demand sides are more valuable and defensible. This means no participants on the demand or supply sides disproportionately account for a high share of transactions, which makes the business more sustainable and diversified. If demand or supply is too concentrated on a marketplace, there’s risk that a large buyer or seller can take a large share of transactions with them if they decide to leave the platform.
  • There’s also greater value when a marketplace aggregates fragmented goods or providers, as those would otherwise have been more difficult to discover and access. This is basically like taking the advantages of a long tail (more variety and niches) and making it as easy to find as the head of the tail (beyond just popular hits).
  • Marketplaces can gauge concentration by measuring the % of GMV the top X sellers or buyers account for (e.g. the share of GMV each grocery chain contributes, in the case of Instacart).

Economics-Related Metrics

- #15 Pricing power
How much are you able to charge for your product? What would your customers be willing to pay to stay on the network?

  • As participants receive greater value from the network, they are willing to pay more to have access to network, in the form of subscriptions, listing fees, take rates, or other monetization mechanisms.
  • Over the lifetime of a network effects business, the business can evolve from not being monetized at all, or potentially even subsidizing demand or supply; to turning on monetization; to having the ability to increase prices with minimal churn on either side.

- #16 Unit economics
How is the business doing, basically?

  • Improved network effects often appear in improved unit economics over time. This is a result of declining incentives that businesses need to offer to different sides of the market, lower share of paid users, and overall improvement in pricing power.
  • For businesses with local network effects, the impact of network effects should show up in unit economics over time, on a market-by-market basis. This is because in a given market, CAC should decrease and the organic share of users should grow over time. For businesses like Thumbtack or Instacart, which have network effects at the local level, tracking the unit economics over time per market is helpful because you’ll see the relationship between market age, network density, and profitability.

How to build a super app

  • There are 2 ways to build a super app: 1. Start with a core product with high engagement and then build more use cases
  • Classic demand side economies of scale where value of the product improves with each new user added to the network
  • Example. Wechat started with chat whose value increases with each new user in the network. Once they had critical mass of users the focus moved to monetisation of those users. Soon businesses got listed on Wechat and then with their We Chat Pay they started doing C2C payments and later e-commerce. Both users and business (two stakeholders needed for become a platform) was already there. All it was to start facilitating transactions
  • But note the main difference between Wechat and something like Paytm. Paytm also had demand side supply of scale because the more users they had using the Paytm wallet the more useful the product was for its users. You need a critical mass of users to drive C2C transactions and businesses + users to drive B2C transactions
  • You need a critical mass of users to drive C2C transactions and businesses + users to drive B2C transactions
  • And post demonetisation everyone was doing Paytm Karo. It was/is the most popular wallet in the country
  • They were always doing a huge volume of transactions thanks to mobile recharges. But they needed other avenues to boost GMV
  • Soon came e-commerce (paytm mall, flights bookings and what not), and a bank (paytm bank)
  • And it became a payments super app
  • But what is the difference between Paytm vs Wechat?
  • The network effect as well as switching cost is far higher for users in Wechat. Inspite of so many new chat products launching in China Wechat is still the most dominant one. You have your entire network on Wechat, your chat history, their moments product is a social network in itself. It has the entire product suite of Whatsapp + Facebook combined + more
  • You as a user can move away from Facebook but maybe not Whatsapp
  • Hence we feel it is Whatsapp and Google Pay which will be the dominant players in payments in India (at least for C2C)
  • Money transfer to your existing bank account is a far better experience than using a wallet. And opening new bank accounts is a pain
  • How hard it is to move away from Paytm?
  • Not much. Transaction history is something which is not as important as your content (historical chat, posts, groups etc)
  • If your network moves to another payments app there is no need too keep using the old payments app.
  • The other use cases of the Paytm super app?
  • Paytm mall is is far far behind Amazon & Flipkart and we don’t ever see it competing with them.
  • Paytm Chat? Not sure. Have never seen anyone use it

Chat is sticky. Payments is not 2. The second way to build a super app is to have supply side economy of scale like Uber, Gojek, Lyft, Swiggy

  • Uber does not have pure network effects in the traditional sense like Swiggy does. Each new user (rider or driver) helps improve the unit economics/utilization but does not create a lock in like traditional networks.

The difference between Uber and Swiggy:

  • For you as a user you don’t care if your friend Mohanlal uses Uber or not. Or if Mohan or Kishan is driving your Uber
  • Sure more drivers help reduce wait time and improve unit economics but diversity in supply does not matter to you
  • Compare this with Uber Eats or a Swiggy. Each new restaurant on the platform does matter to the user because diversity of restaurants lead to more choices for the user and if you want to order from somewhere: The price, time to delivery matters but so does number of food options

More restaurants -> More choices for users More restaurants -> More competition amongst restaurants -> Willingness to do promotions on Swiggy’s platform -> Better prices for users

  • So you have traditional network effects and also see prices go down because of competition between supply
  • Drivers in Uber don’t compete for bids and undercut them. Restaurants in Swiggy do
  • Hence a subscription product works too. Because restaurants split the discounts cost
  • Now comes the hard part.
  • Improving 1) LTV of users 2) Utilisation of drivers
  • Swiggy has been killing it on the first front. Amazing consumer products to drive up usage (orders/week): Swiggy Pop, Swiggy Super, Swiggy Daily
  • Swiggy’s CEO first goal should be to replace the Cook of every middle class Indian restaurant
  • But more orders also means burning more money because of incentives given to the drivers. And that burn is not sustainable as we have seen in Uber’s case

So what do you do?

  • Improve utilisation of drivers by building more use cases for customers and thereby improving unit economics.

Soon you will see Swiggy doing:

1. Ride sharing

2. Milk, vegetable delivery with a daily subscription product to increase daily orders

3. Delivery with higher delivery fee

4. Swiggy daily (replace cook and mess system for couples and students)

The Network Effects Manual: 13 Different Network Effects (and counting)

  • PayPal. Microsoft. Facebook. Uber. Twitter. Salesforce. These are some of the most impactful and significant companies in the world.
  • Each one is very different in a lot of ways, but there’s a single property that defines them all and lies behind their success.

That property is network effects.

  • As we’ve said, network effects are the #1 way to create defensibility in the digital world. Companies with the strongest types of network effects built into their core business model tend to win, and win big.
  • Network effects are responsible for 70% of the value created by tech companies since the Internet became a thing in 1994. Even though they are only a minority of companies, companies with network effects end up creating the lion’s share of the value.
  • For Founders looking to build truly impactful companies, few areas of expertise are more valuable.
  • Still, because very little has been written about network effects, misconceptions abound. Many people talk about them, but few understand the hidden complexities: what they really are, how they work, the many different types, and how to build and maintain them. Moreover, very few companies want to share their valuable playbooks around network effects, so most founders don’t even recognize different types of network effects when they see them, much less understand their complex inner workings.

Today we present the Network Effects Map and accompanying manual for the first time. It’s an ever-evolving effort, and we’re continually making changes and updates. We’ve identified 13 types, each with their own complex playbook. This manual is a starting point for discussion around network effects, and for understanding those playbooks.

Network Effects basics

  • As you probably know, the simplified definition of network effects is that they occur when a company’s product or service becomes more valuable as usage increases.
  • By this definition, network effects seem deceptively straightforward. But when you take a closer look, you start to notice that different types of networks are very different in how they behave. As a result, not all network effects are created equal — some are stronger and tend to produce more value than others.
  • Network effects are one of the four remaining defensibilities in the digital age, including brand, embedding, and scale. Of the four, network effects are by far the strongest. To date, we’ve identified 13 distinct types of network effects that fall under five broader categories.
  • In the map below, we’ve depicted the various network effects types (labeled) and categories (organized by color), with the strongest and simplest network effects at the center of the map. The other three defensibilities are also shown on the right.

We developed this map as an exercise over the years to help bring greater clarity to the subject. But before we dive in, there are a few things we should point out:

  1. The map we’ve laid out here isn’t meant to be taken as an incontrovertible truth — it’s a beginning point for discussion and understanding. It’s one of our evolving methods to help Founders recognize and make use of powerful forces to build great companies. Because for Founders looking to build a strong competitive moat, the ability to identify and understand network effects is invaluable.
  2. Network effects are not viral effects. Network effects are about creating defensibility, and viral effects are about getting new users for free. They have totally different objectives and playbooks.
  3. You’ll often see the same companies have several network effects at play simultaneously, meaning that the different nfx types are not mutually exclusive. They are like colors, and your company is like a work of art. It helps to be familiar with the full palette as you paint.

With that said, let’s turn to the Map itself. Below each of the various network effects on the Network Effects Map are described, with relevant examples.

Direct Network Effects

  • The 1st broad category of network effects, shown in blue on the Network Effects Map, are direct network effects. The strongest, simplest network effects are direct: increased usage of a product leads to a direct increase in the value of that product to its users.
  • The direct network effect was the first ever to be noticed, back in 1908. The Chairman of AT&T at the time, Theodore Vail, noticed how hard it was for other phone companies to compete with AT&T once they had more customers in a given locale. He pointed this out in his annual report to shareholders, writing that:
  • “Two exchange systems in the same community, cannot be… a permanency. No one has use for two telephone connections if he can reach all with whom he desires connection through one.”
  • Vail noticed that the value of AT&T was mostly based on their network, not their phone technology. At the time, it was a revolutionary insight. It showed that even if a new telephone was clearly superior to their old phone on a technical level, no one would want the new telephone if they couldn’t use it to call their friends and family.
  • In other words, a better product wouldn’t come close to making up the lost value of the network. A new entrant would have to achieve a comparable network effect to realistically produce a comparable amount of value for its users. In Vail’s words:
  • A telephone — without a connection at the other end of the line — is not even a toy or a scientific instrument. It is one of the most useless things in the world. Its value depends on the connection with the other telephone — and increases with the number of connections.
  • Below are the full texts of the relevant pages of that 1908 annual report. You’ll notice that Vail never uses the phrase “network effects”, although that’s the concept he’s describing. The term itself would only emerge later.
‍‍Excerpts from the AT&T 1908 Annual Report
  • 72 years after Vail first described direct network effects, the father of the Ethernet standard, Robert Metcalfe, took the concept a step further by proposing that the value of a network is proportional to the number of connected users squared (N2). This is now known as Metcalfe’s Law.
  • The diagram below illustrates the basic concept of a direct network as described by Metcalfe’s Law:
  • Each node in a digital network is connected to every other node, as represented by the diagram above. Every additional node that joins a direct network adds a new connection for all the existing nodes, so the number of new connections (network density) increases as a square of the number of nodes (N2). Since the value of a network is proportional to its density, each additional node adds to the network value at a geometric rate.
  • In 2001, an MIT computer scientist named David Reed went even further, declaring that Metcalfe’s law actually understated the value of a network. He pointed out that within a larger network, smaller, tighter networks can form: for example, the football team within a high school network; siblings within a family network; tennis players within a co-worker network.
  • Such connections, and the potential to join other subgroups, cement people’s commitment to the overall network in deeper ways that the overall size and connection density of the network would imply by themselves. Because of this, Reed believed that the true value of a network increases exponentially (2^N) in proportion to the number of users, much faster even than what Metcalfe’s Law described. We now call this Reed’s Law.
  • The details of these laws can be debated academically, but for Founders, they provide a tangible way to conceptualize an operational truism — network effects are powerful. They are a law of nature.
  • Within the broader category of direct nfx, there are many different types. So far, we’ve identified five: physical, protocol, personal utility, personal, and market network.

Physical (Direct)

  • Physical Direct network effects are direct network effects tied to physical nodes (e.g. telephones or cable boxes) and physical links (e.g. wires in the ground). This is the most defensible network effect type because it not only has a direct network effect, but it also lends itself to the addition of other defensibilities; namely, scale effects and embedding. Competing with a company that has Physical Network Effects requires a large upfront investment of capital and physical constraints.
  • The diagram above depicts the shape of a physical network, with the nodes representing utility terminals like landline phones, train stations, or water faucets, and the connections between nodes representing physical infrastructure like landlines, train tracks, or water pipes.
  • Roads, trains, electricity, sewage, natural gas, cable and broadband internet are examples of businesses with physical direct network effects. In fact, most Physical Networks are utilities: winner-take-all markets that develop into monopolies and end up being nationalized.
  • The best evidence for the strong defensibility of Physical Networks is that so many of them have poor or substandard services, and yet continue to lead the market. Think of Comcast and Verizon. Why do they have the lowest customer satisfaction in the US? Because they can get away with it at no risk to their bottom line. No one can compete with them. Who could spend the money to lay all that cable? And with no competitors, frustrated customers have nowhere to turn.

Protocol (Direct)

  • A Protocol Network Effect arises when a communications or computational standard is declared and all nodes and node creators can plug into the network using that protocol. Bitcoin and Ethereum are recent examples of protocol networks. The protocol setter can be either an individual company, a group of companies, or a panel.
  • Protocol networks coalesce around communication and computational standards, which form the basis for the links between nodes (e.g. Bitcoin miners and Bitcoin wallets).
  • Ethernet is another, more traditional, example of a Protocol Network Effect. When Robert Metcalfe founded 3Com, he persuaded DEC, Intel, and Xerox to adopt Ethernet as a standard protocol for local computer networks, with a standard speed of 10 megabits per second, 48-bit addresses, and a global 16-bit Ethertype-type field. Competing proprietary protocols existed, but as Ethernet pulled away and began to capture more and more market share, Ethernet-compatible products flooded the market. This increased the value of Ethernet at a compounding rate and decreased the value of competitors, regardless of their relative performance. Soon, ethernet ports became standard features of all modern computers.
  • Once a protocol has been adopted it is extremely difficult to replace. Note how the fax protocol is still in use, or the TCP/IP protocol (even though other, better protocols now exist for those purposes).
  • It’s also true that the protocol creator doesn’t typically capture most of the value from the development of the network, as they normally do with other direct nfx.
  • This distribution of value in a Protocol Network can be shifted if the protocol creator can maintain ownership of a significant percentage of the tokens within a token-enabled network, or maintain central control over addressing, identity, wallets, naming, or prioritization and still get the network to adopt the protocol.
  • The success of such an adoption strategy is often less about technology and more about marketing, social engineering, and choice of market niche. That’s why VHS beat Betamax, even though Betamax was arguably a better standard. It’s also part of why Bitcoin has taken off as a virtual store of value, when it is more costly to operate and no more useful than many other virtual currencies that preceded it.

Personal Utility (Direct)

  • Personal Utility Networks have two distinguishing qualities. The first is that users’ personal identities are tied to the network in question, often with usernames tied to their real name as with Facebook Messenger. The second is that they are essential to the personal or professional lives of users on a daily basis.
  • In the diagram above, the nodes are represented by the chat bubbles of people (nodes) connected by personal utility services (links). The nodes of a personal utility network are tied to the real-life identity of the people using it, and the network is especially dense because it has many local sub-groupings. This brings Reed’s Law into effect, so the value of Personal Utility Networks could increase at a rate of up to 2^N.
  • People use Personal Utility Networks to communicate and interact with their own personal networks, so not being online or being part of the network has a steep downside. Opting out would become a significant impediment in daily life and could greatly harm people’s important personal or work relationships.

Personal (Direct)

  • Personal network effects are in play when a person’s identity or reputation is tied to a product. Often people on a Personal Network are influenced to join by people they might know in real life. If people you know from the real world are all using the same product to house their identity and reputation, there’s a large value add (to you) if you join the network yourself.
  • Personal Networks involve personal identity and reputation, connecting the persona of each user with other user personas. Each additional node represents both an additional potential audience member as well as an additional content producer for all the other nodes.
  • Personal Networks differ from Personal Utility Networks in two main ways. As explained in the previous section, Personal Utility Networks are typically used for things that need to get done. There is a substantial amount of practical utility to the user. Second, Personal Utility Networks are typically more for private communication, rather than public communication. Personal Networks are less vital. You can stop using them and your life won’t alter that much. Networks like Facebook or Twitter or Linkedin (when you’re not job hunting) aren’t usually essential for your day-to-day life.
  • However, Personal Networks are still very strong. You aren’t running to join another friend network or professional network now that you have FB and LinkedIn. It’s also true you could stop using both and be fine on a daily basis.
  • There’s a difference between sending an IM to your significant other telling them to not miss picking up your Mom at the airport and posting a status update about your Mom visiting on social media. In both cases, your own identity is tied to the communication and your audience is your personal connections. But one is a private need-to-have and the other is a public nice-to-have.
  • The Personal Network Effect arises from the interpersonal, tribal impulse to build connections with others. It’s this impulse that compels people to join and stick with a network (e.g. Facebook, LinkedIn, or a religion) because their friends/co-workers/neighbors are also part of that network. A user’s “social graph” in a personal network are usually closely mapped to their in-the-flesh relationships.

Market Networks (Direct)

  • A Market Network combines the identity and communication aspects of a Personal Network with the transactions focus and purpose that typify a marketplace. Usually, Market Networks start by enhancing a network of professionals that already exists offline. We consider Market Networks to be a form of direct network effects because the relationship between nodes is direct, as shown below:

-‍ Market Networks are very different from 2-Sided Marketplaces, although the two are often confused. Most people think companies like HoneyBook and Houzz are marketplaces, but they’re not. In reality, they’re Market Networks, which combine the main elements of both Personal Direct Networks and 2-Sided Marketplaces, as well as being many-sided as opposed to 2-sided — often with the addition of a dedicated SaaS workflow software.

2-Sided Network Effects

  • The 2nd broad category of network effects, 2-sided network effects, are often called “indirect network effects” in academic literature. However, we think this is misleading since 2-sided networks can involve both direct and indirect network effects.
  • Instead, the real distinguishing characteristic of a 2-sided network is that there are two different classes of users: supply-side and demand-side users. They each come to the network for different reasons, and they produce complementary value for the other side.
  • It’s relatively simple to see how each new supply-side user in a 2-sided network directly increases the value of the network for demand-side users, and vice versa. For instance, each new seller (supply-side user) on a 2-sided marketplace like eBay directly adds value for buyers (demand-side users) by increasing the supply and variety of goods. Likewise, every additional buyer is a new potential customer for sellers.
  • It’s more complicated when we look at how same-side users interact. Most of the time, users on the same side subtract value directly from each other. For instance, core sellers on eBay create more competition for other sellers. More Uber passengers at rush hour mean surge pricing. Both are examples of negative direct same-side network effects.
  • At the same time, indirect benefits usually end up outweighing those direct negatives. The fact that there are many sellers in the marketplace attracts the buyers to be there in the first place. And that is ultimately more valuable for the sellers, even if they have to sell at more efficient prices. The same is typically true on the buyer side.
  • This positive indirect effect of 2-sided networks has been discovered and rediscovered throughout history. In the late 1600s, for instance, all the violin makers moved to work and sell their violins on the same street in Venice. Although the proximity of the competing violin vendors drove down prices, it was worth it for the suppliers as a group because it was more important for them that people in the market for violins would take their business to that particular street, not some other street in some other city.
  • In the 1980s, malls in the US discovered the same thing. By aggregating competing sellers in one location, sellers were able to get much more business than others that were spread out, making it practical for competitors to co-locate.
  • What we’re seeing now with the preponderance of online 2-Sided Networks is the same effect, but with software instead of a physical location.
  • Note also that there are cases of positive direct same-side network effects, where more same-side users add value to each other. These are very powerful and should be sought out as you design your products. This is the case with Microsoft OS, one of the most enduring 2-sided network effects products the world has seen. Microsoft OS users benefit other users because they can share files more easily with co-workers and friends. This is a positive direct same-side network effect (adding to the core 2-sided network effect) that is typical of operating systems.
  • At present, we’ve identified three types of 2-sided network effects: marketplace, platform, and asymptotic.

Marketplace (2-Sided)

  • The two sides of a marketplace are buyers and sellers. Successful 2-Sided Marketplaces like Craigslist are very difficult to disrupt. To break them apart you must have a better value proposition for both parties simultaneously, or else nobody moves. Customers are there for the vendors, and vendors are there for the customers. One won’t leave without the other.
  • 2-Sided Marketplaces have two sets of nodes, as shown above. One set are supply-side users, the other are demand-side users. They provide direct value for each other through the marketplace, which is an intermediary represented by the central node in the diagram.
  • With a 2-Sided Marketplace, the network is what provides the majority of the value, not the app or website itself — which explains why marketplaces products like eBay and Craigslist can afford to look essentially unchanged after 16 years.
  • But there’s one big weakness in marketplace defensibility, which arises from the phenomenon of “multi-tenanting”. People can sell their products on eBay and Etsy at the same time. Landlords can list their apartments on Craigslist and Trulia, and renters can check both marketplaces to browse for inventory. It’s hard to lock out competition from new entrants when the members of your network can use competing networks as well as yours without a penalty. The goal of the marketplace is thus to design the product/service to add so much value or “lock-in”, particularly on the supply side, that members won’t be tempted to multi-tenant.
  • Further, marketplaces come in more shapes than we might think. Media companies, for example, are essentially 2-Sided Marketplaces. Audiences (supply) come to the marketplace and sell their attention for content experiences. Advertisers (demand) on the other side buy the attention of the audiences. The greater the audience of a media company, the more likely advertisers will be to spend any money on that media company at all, and then the more money they will be willing to pay the company when they do. “Sellers” i.e. readers/viewers have a direct positive network effect for “buyers”, i.e. advertisers. And vice versa, because (in theory) more advertising revenue gives a media company the resources to produce better content.

Platform (2-Sided)

  • What we call 2-Sided Platform network effects are similar to 2-Sided Marketplace network effects, in that they have two sides with very different interests that directly benefit each other. The difference is that the supply side actually engineers products that are only available on the platform. The supply side has to do work to integrate to the platform. The products created and sold by the suppliers are a function of the platform, not independent of it.
  • 2-sided platforms have supply-side nodes (developers) and demand-side nodes (users), which create value for each other through the intermediary of the platform itself (central node). The platform itself also provides significant value for both sides.
  • Microsoft OS, iOS, and Android are prime examples of products that have achieved this type of nfx. Xbox, PlayStation, and Wii are also examples, although they’re slightly different.
  • Another difference platforms have from marketplace network effects is that, compared to online marketplaces, the features and benefits of the platform itself can play a greater role in the utility of a platform relative to the network. People buy iPhones and thus iOS for the brand, design, technical features, and performance of the phone as much as they do for the app ecosystem. People might buy Xbox and PlayStation consoles for the graphics and performance of the system as much as they do for the library of available games. This in contrast with marketplaces, where the product itself comes in at a very distant second compared to the value of the network.
  • How a platform is sold can also matter a great deal to how well adopted it becomes by both sides. For instance, Microsoft has an army of salespeople who sell their platform to large corporate clients, and they often give the platform away for free to universities so graduates learn to standardize on that platform.
  • One vulnerable point for platforms is that, just like with marketplaces, both sides of platforms can also multi-tenant. App developers can create versions of their app for both iOS and Android. Game developers can syndicate their games to PlayStation as well as Xbox. Likewise with the other side — gamers can own a PS4 and an Xbox One simultaneously, and people can own both a Dell and a Macbook. However, the pricing makes this more prohibitive than with online marketplaces, where multi-tenanting is usually free. So from that standpoint, platforms often have a leg up.

Asymptotic Marketplace (2-Sided)

  • Of course, no two 2-Sided Marketplaces are exactly the same. One way they can significantly differ is in the “value curve.” This refers to how fast the value to the demand side increases as supply increases, and how strong the nfx get when critical mass is reached.
  • The “Value Curve” diagram below illustrates the supply and demand curves for three subcategories of marketplace nfx..
  • The straight line (orange) in the middle is what you would expect with Craigslist or eBay, where generally, the growth of the supply side produces value to the demand-side at a relatively proportional rate. Marketplaces like this get very strong over time.
  • The “Value Curve” diagram illustrates it below.
  • The lower curve (yellow) is what you saw with OpenTable, where the value is delayed. OpenTable had to grow the supply-side of restaurants to a very high level before there was any value to the demand-side. Once that critical mass was achieved, however, the network effect became very powerful.
  • The third subcategory of marketplace network effects, illustrated by the red curve on the graph above, is what we call Asymptotic Marketplace network effects. It has the inverse properties of OpenTable’s delayed value curve. The initial supply quickly adds value to the demand side, but soon the value of increased supply starts to diminish.
  • The most famous examples of an Asymptotic Marketplace are ridesharing companies like Uber and Lyft, as we wrote about in this Uber case study. Up to a point, more drivers benefit riders because of reduced wait times. But beyond a certain point, the value to the rider steeply diminishes. Waiting 4 minutes for a ride as opposed to 8 minutes is a huge difference. But 2 minutes instead of 4 minutes? The value of increased supply diminishes drastically around the 4-minute mark.
  • Asymptotic Marketplaces are more vulnerable to competition than other marketplaces for this reason. If Uber has 1000 drivers in a certain area, a competitor might be able to provide comparable service with half as many.
  • Adding to this vulnerability, Asymptotic Marketplaces can be very susceptible to multi-tenanting. Many people use both Lyft and Uber to get around, depending on which one has lower pricing and faster waits at any given time. On the supply side, many drivers use both Uber and Lyft, depending on pricing and wait times.

Data Network Effects

  • When a product’s value increases with more data, and when additional usage of that product yields data, then you have a Data Network Effect. This is the 3rd broad category of network effects.
With a data network, each node (user) feeds useful data to the central database. As the aggregated data accretes, the value of the data for each user also grows.


  • Data network effects tend to be weaker than many people — particularly venture capitalists — often want to believe: having more data doesn’t necessarily translate to value, and gathering more useful data isn’t always easy even if data is central to the product.
  • Data can increase product value in different ways. If data is really central to the way the product benefits users, then the data nfx of that product has the potential to be very powerful. If data is only marginal to the product, the Data nfx won’t matter much. When Netflix recommends a show to you, the algorithm is basing that recommendation on user viewing data. But Netflix’s discovery function is marginal; its real value comes from the inventory of tv shows, movies and documentaries. So Netflix only has a marginal Data Network Effect.
  • Likewise, the relationship between product usage and the amount of useful new data gathered can be asymmetrical. Yelp has a Data Network Effect because a greater number of reviews for a greater number of restaurants makes the product more valuable. But its network effect is weakened by the fact that only a small percentage of users produce the data; most people read from the Yelp database but don’t write to it.
  • At the same time, Yelp is also a good example of a common weakness in Data network effects. Its Data network effects are asymptotic. The 5th review adds a lot more value than the 30th. Past a certain low level, more reviews on a restaurant don’t increase the value to you, the user. (Breadth of reviews, on the other hand, is very helpful and leads to solid network effects, which is why Yelp is still so prevalent.)
  • If a product has no relationship between increased usage and more useful data production, then there is no network effect; it’s merely a scale effect. Credit reporting agencies like Experian have a scale effect because even though more data makes their credit scores more valuable (i.e. accurate), usage of the product by consumers doesn’t naturally increase the amount of data they have.
  • Data network effects are easy to confuse with the data advantages that come from scale. Large companies have more data by definition. The question is, does that data create meaningful value for customers/users? And if so, does increased usage lead to more useful data?
  • A good example of a service with a strong Data Network Effect is Waze. Not only does nearly everyone consuming data on Waze also contribute useful data, but because the data is consumed in real time, the dataset needs to be continuously updated. So the larger the network, the more accurate that data will be at any instant for any given road. More data continues to produce value almost indefinitely, so there’s less of an asymptotic data nfx with Waze than almost any other service we can think of.
  • Data network effects are possibly the most complicated network effects category. There are as many different data network effects as there are ways to use data. We’ll be mapping out data network effects in greater detail in the future.

Tech Performance Network Effects

  • When the technical performance of a product directly improves with increased numbers of users, it has Tech Performance network effects. This is the 4th broad category of network effects. For networks with Tech Performance network effects, the more devices or users on a network, the better the underlying technology works. This makes the product/service become faster, cheaper or easier.
‍‍Networks with tech performance become better (faster, cheaper, or easier to use) the bigger they get. As more nodes (devices) join the network, the performance of the whole improves.
  • Consider peer-to-peer file sharing services like BitTorrent, or VPN providers like Hola, or object finding mesh networks like Tile. These services get faster for all users the more nodes are on the network. Every person downloading a file from BitTorrent is also seeding files to the network. The more people who have a Tile app installed, the greater the chances that you can locate something you lost since every phone on the network is constantly scanning for tiles. Skype also claims that the more people using Skype, the better the video streaming quality (it’s not clear if this true, but it’s the right idea for them to have).
  • Tech Performance Network Effects are different from technological advances, and we would argue they are superior. Technological advantages have a short half-life and aren’t very defensible anymore. If you’re the first to come out with a technology, the rate of innovation ensures that it won’t be long until the competition either copies your technology or develops it themselves. But with Tech Performance nfx, your product gets a runaway advantage for being the first out of the gate. You don’t have to fight to keep your head start. Your lead tends to lengthen, not decrease, over time.
  • The other common point of confusion with Tech Performance nfx is to assume its presence when increased usage produces revenue that can then be re-applied to produce more tech advances, driving even more usage. If a performance improvement comes from an increased volume of revenue or data … it might be a good thing to have… but it’s not tech performance nfx.

”Social” Network Effects

  • The 5th and last broad category of network effects are what we’ve called “social” network effects. They work through psychology and the interactions between people.
  • Here’s how we think they work.
  • Networks are nodes and links. With a landline telephone system, it’s easy to see the physical phones and wires connecting them.
  • However, there is an unseen network among people, where our physical bodies are the nodes, and our words and behaviors with each other are the connections. These are the original networks, if you will.
  • Like digital network effects, these social nfx can help create more value in your product for users the more people use it. People add value to each other by influencing them to think or feel differently. By providing triggers and confidence to use your product. By reinforcing their choice to continue using your product.
  • Social network effects are usually the hardest to deploy for long-term defensibility. However, if you can successfully get various forms of psychology on your side against a competitor, they can represent a significant advantage.
  • Now you may be asking yourself “Aren’t these social network effects kind of like brand defensibility?” And you would be partially right. There certainly are similarities. They have to do with language and psychology. But we think there are important differences as well, which is why we’ve broken them out into a separate category.
  • To date, we’ve identified three main types of social network effects: language, belief, and bandwagon effects. That number could easily expand, since human psychology is complex and there are many kinds of social interactions that work very differently, and we continue to look for new types.

Language (Social)

  • In any human network, language is the main intermediary. It’s the protocol that all the nodes in a network use to interface with each other. For instance, the English language is a serviceable language, but it’s a lot more valuable considering that there are 1.5 billion people who speak it. That’s more than 15 times as many people who speak German. So even though speaking English doesn’t make you 15 times better at communicating than speaking German, the value to speakers is much higher as a result of the network.
  • That’s why, throughout history, language has displayed a “winner-take-most” tendency. People in the same political, social and economic units tend to coalesce around one language.
  • This concept extends to the jargon and vernacular of specific groups, from nations to corporations, teens to hipsters, economists to Google employees. As jargon gets adopted by more and more people, it becomes more valuable to all the other users.
  • Startups can use the network effects of language to take advantage of that winner-take-most effect in at least two ways: first, in creating business category language; and second, in naming a company or product.
  • With the first, if a Founder can help create a name for a business category and then be known as #1 in that category, it gives them solid language nfx. Miller Beer did this in 1975 when they created the “lite beer” category. The same thing happened 1995 with the creation of the web “portals” category, which Yahoo! benefited from since it was leading the category at that time. We’ve seen this same language network effect recently with the creation of the “cryptocurrency” category. Bitcoin, being seen as #1, benefited the most: it still accounts for nearly 40% of all the market capitalization despite their being 100s of competing cryptocurrencies.
  • In all these cases, the #1 lost its crown eventually, which is why Language nfx are considered less strong than others. Nevertheless, for many years, their competitors would certainly complain about the unfair advantage of the company with Language Network Effects they wished they had themselves.
  • The second way companies typically take advantage of Language network effects is with company and product naming.
  • For instance, when “Googling” something became synonymous with searching for something on the Internet, it was a huge advantage for Google. The language itself became an impediment to using a competitor. When someone asks you to Google something, it’s both socially awkward and mentally jarring to pull out your phone and start using Bing.
  • It’s similar when someone says “grab an uber.” They’re giving you a social cue to use Uber, not Lyft. (BTW, entering the vernacular as a noun is probably not as powerful as entering as a verb. It would likely be better for Uber if more people said, “I’m going to uber over there,” which some already do, but If I were Uber, I would encourage that usage as best I could).
  • Another example: back in the day, to “xerox” something mean to photocopy it.
  • Getting people to verbally use your company name is a big advantage, but it’s very tricky to do. Your company name has to be memorable and catchy enough to do this, and that’s why getting the name right is so crucial.

Belief (Social)

The 13th network effect on our current Map is belief. The belief network effect is something you can best see with gold, Bitcoin and religion. It’s a direct network effects.

  • Homo Sapiens is a pack animal. We want to be in the “in group” and be accepted by others. Sharing common beliefs is a critical part of that. If people believe in something, others are more likely to stick with it and believe in it, too. As a result, there are big social consequences for not believing the things your friends believe, and perhaps worse consequences for ceasing to believe in what they believe. This is one factor that makes people stick with group thoughts, making them very resilient to contradictory information.
  • Most importantly, beliefs become more valuable to believers the more people believe.
  • Look at gold. Why is it valuable? You can’t eat it or sleep on it. It’s pretty, but lots of things are pretty. It has some industrial uses, but not that many. It’s valuable because — after we were done believing salt was valuable — people decided to believe gold was valuable instead. And for 5,000+ years, it has always stayed valuable. The past gives us confidence that everyone will continue to hold this belief in the future. That belief strengthens over time.
  • Ipso facto, gold is valuable because we believe it’s valuable.
  • Belief network effects are like sand. In small quantities, sand dissipates in a breeze. But if you layer enough sand down on top of itself, it becomes hard as stone.
  • The same is true of Bitcoin. The more people believe it’s valuable, the more valuable it gets for everyone. And we’re seeing that same “sand layering” with Bitcoin now. The more times its price crashes and then bounces back, the more people will believe it has value. And then when you layer some Ethereum “sand” on top of it, and the “sand” of the thousands of other cryptocurrencies in existence — all denominated in Bitcoin on the exchanges — the Bitcoin sand gets progressively more stable as a result of growing Belief nfx. What was once fluid and intangible transforms to something closer to rock.

Bandwagon (Social)

  • Bandwagoning happens when social pressure to join a network causes people to feel they don’t want to be left out.
  • One good example is Slack. In tech circles, it’s commonly felt that you don’t have a modern company unless your teams are using Slack. In our opinion, Slack’s notoriety and valuation have exceeded the utility of the product because it’s become somewhat of a movement in the tech industry, and developed a strong Bandwagon network effects.
  • Bandwagon network effects typically arise when a network first begins aggregating, when people are jumping on early. When people started to use Google back in 1998, there was a general feeling that “the cool kids” were using Google (they had been using Alta Vista before that). If you didn’t use Google, you were left out. Other nfx have since taken over for Google to provide them their core defensibility, so they’re no longer reliant on that initial Bandwagon nfx, but it certainly was there at the beginning.
  • One company that has made Bandwagon network effects a core expertise is Apple. Every year, with a carefully scripted performance, they re-manufacture buzz and FOMO with their new product demos and launches. This has been extremely effective. These days, if you show up at a meeting in Silicon Valley with an IBM clone instead of an Apple computer, it’s a sign you’re not part of the tribe. You’re seen as an outsider if you don’t use a Mac.
  • This can be frustrating for competitors who feel they have better products, but can’t beat Apple for reasons that remain hidden to them. Apple’s success goes beyond “branding.” It relies on successfully triggering the psychological need to be part of the cool crowd, to join the movement.
  • This video from 2010 is a hilarious depiction of the frustration and confusion competitors have about the mechanisms behind Apple’s dominance, and here’s a 2017 Samsung ad campaign which is a cry into the same void: trying to tell consumers it’s time to “grow up” from their childish, emotional attachment to the iPhone given the Samsung makes a “better” product. But what they’re missing is that the value to the user is not just the sum of the product features, not just a function if it’s aggregated utility. It includes the value of the network derived from other product users, and the social value of the bandwagon it lets them join.
  • Here’s a video which does a good job explaining Bandwagon network effects. Derek Sivers captures the essence of bandwagon psychology when he says “they will be part of the in-crowd if they hurry.” He then goes on to deftly explain that “the rest [join since they] prefer to stay part of the crowd, because eventually they would be ridiculed for not joining.” The whole video bears watching.
  • Students of network effects will correctly note that Bandwagon Effects can go too far. If too many people join a movement, sometimes the early adopters will abandon it because the group has become too mainstream. That’s why you typically see the Bandwagon network effects at the beginning of products. Smart Founders will navigate that transition from bandwagon to other network effects to maintain long-lasting defensibility.

The power of network effects

  • We explained earlier the Network Effects Map is meant to be a discussion starter on the true nature of network effects, not a last and final word on the subject. Network effects are a complex phenomenon that look simple on the surface.
  • With this manual, we’re trying to communicate the importance, variety, and complexity of network effects. Top Founders will benefit from a deeper understanding of network effects which will translate to better practical business decisions. In the end, defensibility is what will define the success of your business. More than anything else, network effects are the key to that success.
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