The network effect describes the power that the platform’s users and agents have on the platform’s success. The network effect is strong when more users or agents beyond the critical mass continues to equate to greater value for the company.
For example, the more users Facebook has, the more advertisers it can attract and the more value the company can wring from its platform, ad infinitum. On the other hand, XBox’s users are drawn to its platform based on a few “hits,” making XBox’s network effect weak. In other words, XBox doesn’t gain more users proportional to more game titles and vice versa.
Network clustering describes the constellation of markets, or clusters of connected users, within a platform. Some platforms lend themselves to geographical clustering — think Craigslist, where users mostly trade goods/services with others in their area, or Uber, where users seek rides from drivers in their proximity. Other platforms represent one giant cluster — think Twitter, where anyone can exchange content with anyone, regardless of their geographical location.
Here’s why it matters. The degree of a platform’s network clustering significantly impacts a platform’s vulnerability to disruption. Consider this: to disrupt Twitter, you would have to launch a worldwide product and convince millions of users to get on board in order to deliver an approximate value
Multihoming is the phenomenon where a person comparison shops or consults across multiple platforms to choose the best deal. This happens on both the user side (a traveler searches for a rental on Airbnb and VRBO) and the agent side (a rental is listed on both Airbnb and VRBO). Some platforms lend themselves to this — rideshare, travel booking — and some don’t.
For platforms that deal in recurring transactions (i.e. the gig economy, like Thumbtack), platforms can be at risk of disintermediation, the phenomenon where users and agents find each other through the platform, but then conduct business off the platform.
Network bridging happens when a single company operates in multiple markets, thus harnessing the value of interaction data from its users across multiple areas. Think Amazon, which now knits together knowledge about its users’ behavior from grocery stores (Whole Foods), video streaming (Prime Video), live streaming (Twitch), and much much more. This not only benefits the company, which learns from user behavior, but it can also provide value for the user by centralizing or connecting a variety of services through a single access point.