Recent battles for platform market share have shown that some technology platforms are better than others. More specifically, some platforms seem both more durable and more lucrative than others due to important characteristics of the platform and its users. Social media and online auction platforms demonstrate the “winner-takes-all” narrative, with one dominant platform — and its sponsoring company — capturing the majority of users from the competition. However, in other platform-mediated markets, many competing platforms seem to persist.
In other cases, platforms like Amazon have risen to dominance in their markets because of conventional scale and scope advantages, not because they relied on direct user interactions. These cases suggest that successful platform strategy is not just about the size or structure of the platform, but also the specific nature of interactions among users.
Traditionally, when we think of “network effects,” we’re focusing on the value we get from other users on a given platform. For instance, I get more value from Facebook or Skype when others use the same platform, because I want to be able to interact with family members, friends, and colleagues. These dynamics form the basis of a winner-takes-all narrative.
Yet while network effects exist across a wide spectrum of markets, they play out differently across different contexts and use cases. For example, for users of online auction sites, a consumer will almost certainly be drawn to the platform with the largest current user base, as the brunt of value comes from the ability to sell to or buy from a large network of users. Similarly, in deciding which video game console platform to join, a person may evaluate which platform currently seems most popular in the marketplace, as part of the fun is the opportunity to interact with other users. However, the same person might also give equal weight to criteria outside of the user base, such as the availability of a particular game title or the quality of graphics on the console.
These seemingly subtle differences in the strength or intensity of network effects have important implications for optimal platform strategies. At a basic level, the fundamental distinction in platform-based markets is no longer whether there are network effects or not, but rather the extent and type of network value that can be created and leveraged by platform companies.
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In moving beyond the “more is better” conceptualization of network effects, three basic questions can inform the relative value of network interaction for a given platform:
Are there cross-side network effects? The basic premise of network effects is that products and services become more valuable with a larger user network. These dynamics can often be seen with communication-based platforms — take the earlier example of Skype, or the rise of WhatsApp, where more users mean more interactions and more value. Yet many platforms involve multiple user “sides,” whereby the platform acts as an intermediary between distinct user groups or organizations that couldn’t easily interact otherwise. For example, the rise of the Keurig single-serving coffee maker was partially driven by the availability of coffee brands from a variety of producers, which consumers could enjoy using their Keurig. Similarly, job seekers care more about the ability to reach hiring companies on a career search site than about the sheer number of other job seekers. In many cases, the ability to interact with another side of the platform — another group of participants or a specific provider of a complementary good — is a stronger rationale for joining the platform than the total number of users per se.
Are there local network effects? For many platforms, users care less about the total size of the user network than the presence of a few key participants nearby. For example, in ride-hailing platforms, users derive greater value from the availability of potential drivers in their immediate geographic area than from the total size of the driver network nationwide. Similarly, users of matchmaking sites or short-term accommodation platforms place a premium on a stronger network of local participants rather than the total number of users globally; eHarmony’s early strategy of rejecting less serious applicants relied on the assumption that users would appreciate a smaller yet higher-quality local network of potential partners. Recent startups such as Lime are balancing these dynamics in the dockless bike-sharing market, as users derive value primarily from the local availability of a reliable bicycle, but likely care little about bicycles’ availability outside their metropolitan area.
Are there informational or “meta” network effects? Many companies have been able to leverage their user networks beyond the conventional approach of enabling direct user-to-user interaction. For example, most Amazon users don’t benefit from direct network effects in the conventional sense, in that transactions by individual users rarely add direct value to other users’ consumption. However, the ability to review products (and each other) has created an informational or “meta” network effect for consumers. In this case, the value of a network doesn’t manifest through direct transactions, but rather via greater availability of information about previous transactions in the network, or about the user network itself. Travel review sites such as TripAdvisor offer similar value propositions, as users receive value from an aggregate of information from a network of providers, rather than direct transactions with other network users.
Network Size Is Only One Dimension of Platform Value
For certain platforms — particularly those focused on direct communication or interaction — companies with the largest user networks will offer significant value for consumers. Yet for a vast array of other platform-mediated markets, from crowdfunding to health care exchanges, characteristics other than total network size may hold the key to competitive advantage; platform users may place equal or greater weight on the ability to access specific participants on the other side of the platform, a local or higher-quality subset of platform users, or information about the network or its participants. As the authors of Platform Revolution note, the ability to build and leverage these drivers of network value may create opportunities for platform business models even outside of digital settings, such as McCormick’s FlavorPrint platform, which incorporated user-generated flavor profiles and recipes to augment its core food seasoning business.
As platform business models continue to gain traction across a wide array of settings, understanding the unique characteristics of platform-mediated markets is a vital prerequisite for setting effective strategies. While “winner-takes-all” stories offer an attractive option for companies competing for platform dominance, the reality is that building a successful platform strategy is more nuanced than building the largest network of users.
The competitive advantage that comes with a large user base may cause a company to miss out on more complex patterns of network interaction and value. Conversely, there may be opportunities for companies to create or enhance network value for their users via localized transactions among a smaller but stronger user network, or through the creation of meta network effects through information exchange. Seemingly small differences in the ways that consumers derive value from a cohort of other users can have significant impacts on platform competition. This offers forward-looking companies opportunities to bring platform business models to new markets.