The Cold Start Problem: How to Start and Scale Network Effects

I argue that there are a trio of network effects: Engagement, Acquisition, and Economics.

Common themes emerge when you look at Slack’s strong network launch as well as the successes across marketplaces, social networks, developer platforms, and dozens of other categories. Many of them are counterintuitive: The networked product should be launched in its simplest possible form—not fully featured—so that it has a dead simple value propos

Pay attention to the ratios between each set of users—1000 to 500 to 250. This ratio is often called the viral factor, and in this case can be calculated at 0.5, because each cohort of users generates 0.5 of the next cohort.

Predating Uber, I had written and published nearly a thousand essays on topics like user growth, metrics, viral marketing—along the way, popularizing tech industry jargon like “growth hacking” and “viral loops.”

While these specific methods aren’t applicable to every networked product, there is an important idea at the core: any product that’s in a head-to-head race with competitors should track the outcomes—market share, active users, engagement, or otherwise—while they execute in the market, to put together cause and effect. A marketplace startup might m

The Economic Effect also can grow revenue by increasing conversion rates, by building features for the network as opposed to tools for the tool.

Rarely in network-effects-driven categories does a product win based on features—instead, it’s a combination of harnessing network effects and building a product experience that reinforces those advantages.

Cold Start Theory lays out a series of stages that every product team must traverse to fully harness the power of network effects. The curve represents the value of the network as it builds over time, and is shaped as an S-curve with a droop at the end. There are five primary stages: The Cold Start Problem Tipping Point Escape Velocity Hitting the

describe an approach that focuses on building an “atomic network”—that is, the smallest possible network that is stable and can grow on its own.