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, nfx are the #1 way to create defensibility in the digital world. Companies with the strongest types of nfx built into their core business model tend to win, and win big.
Our three-year study, which we released recently, shows that nfx 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 nfx 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 nfx, 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 nfx, so most founders don’t even recognize different types of nfx when they see them, much less understand their complex inner workings.
Below we present our network effects map and accompanying manual. It’s an ever-evolving effort, and we’re continually making changes and updates. So far we’ve identified 13 types of network effects, each with their own playbook. This manual is intended to be a starting point for discussion around nfx. In addition to reading this manual, we encourage you to check out the companion resources:
https://www.youtube.com/watch?v=aoeal3ljnqw
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 nfx are created equal — some are stronger and tend to produce more value than others.