Cold Start Problem
Andrew Chen’s recent book, “The Cold Start Problem”, explores the topic of network effects in great detail. Here is how he defines a “network effect”:
The network effect can be defined by breaking the term into its constituent parts—the “network” and the “effect.”
The “network” is defined by people who use the product to interact with each other. For AT&T’s telephone network, it literally consisted of the wiring that spanned between homes. In the digital age, for YouTube, the network is defined by software. It is the content uploaded by creators and the viewers that watch them—and the software platform sits in the middle, making recommendations, organizing the video with tags, recommendations, and feeds—so that the right videos are shown to the right consumers. We love using networks when the right people are on them, whether that means marketplace sellers who list the right products and services, app developers who are building our favorite games, or our favorite celebrities, writers, and friends. In turn, they participate in the network because we and millions of other consumers are on them. It’s circular, because after all, they need an audience and a customer base, too.
The “effect” part of the network effect describes how value increases as more people start using the product. Sometimes the increasing value manifests as higher engagement, or faster growth. But another way is to think about it as a contrast—at its beginning, YouTube didn’t have any videos, and neither viewers nor creators would find it valuable. But today, YouTube has nearly 2 billion active users watching a billion minutes of video per day, and this in turn creates engagement between creators and viewers, viewers and each other, and so on. People stay on the network and use it more, because other people are also using it more.
Given these definitions, how do you tell if a product has a network effect, and, if yes, how strong is it? The questions to ask are simple: First, does the product have a network? Does it connect people with each other, whether for commerce, collaboration, communication, or something else at the core of the experience? And second, does the ability to attract new users, or to become stickier, or to monetize, become even stronger as its network grows larger? Does the user face a Cold Start Problem where retention is low when there’s no other users?
Here is how he describes the Cold Start Problem: “Most new networks fail. If a new video-sharing app launches and doesn’t have a wide selection of content early on, users won’t stick around. The same is true for marketplaces, social networks, and all the other variations of consumer (and even B2B) products—if users don’t find who or what they want, they’ll churn. This leads to a self-reinforcing destructive loop. In other words, in most cases the network effects that startups love so much actually hurt them. I call these “anti-network effects” because these dynamics are downright destructive—especially in the early stage as a company is getting off the ground. Solving the Cold Start Problem requires getting all the right users and content on the same network at the same time—which is difficult to execute in a launch.”
The graphic below from the book shows the stages of the Cold Start framework:
Let’s keep the ideas about Network Effects in mind as we think about the two problems: Attention Recession and Voter Aggregation.
