You can no longer just build something great and market it well. People will copy you and erode your profits. AI has changed the game.
Out of the very few potential defensibilities, Network effects tend to be the most common successful moat for tech products.
Network effects happen when EACH NEW USER noticeably makes the product MORE VALUABLE.
The bigger the difference each user makes to your product, the stronger the network effects.
There are two common types of network effects:
A. direct value when used socially (e.g. communications, social activities)
B. indirect value with more users (e.g. data network effects, efficient marketplaces, platforms, standardisation)
And a lot of misconceptions:
1. Viral growth and network effects are often confused, but are different mechanisms. Viral growth is about speed of scaling (finding low CAC). Network effects are about the product becoming more valuable (high engagement, retention).
2. You don't need both, but having both is great. A product that has inherent virality, where it spreads from one user to another as a direct consequence of use, naturally has network effects.
3. On the flip side, not every product with scale has network effects (for example Angry Birds).
4. You would think you need huge scale for network effects to start working. But in the early days, before you have reached true scale, you can still make your network effects effective by targeting small clusters of people within niches. Targeting a broader audience produces weaker network effects. (e.g. Facebook did this well but Threads didn’t. Retention dropped significantly after launch)
5. If you remember one thing it should be: people come for the tool, stay for the network.You'll know you're doing it right if engagement increases as your user base grows.
Facebook found that users who only connected with a few friends on the platform churned, but those who made 7 friends in 10 days came back significantly more frequently.
Uber and ChatGPT have weaker, less-direct network effects. They can't fully rely on these weaker network effects, but they definitely help.
Facebook found that users who only connected with a few friends on the platform churned, but those who made 7 friends in 10 days came back significantly more frequently.
Uber and ChatGPT have weaker, less-direct network effects. They can't fully rely on these weaker network effects, but they definitely help.
Network effects are not just a competitive advantage.
Users are disincentivised to switch to lower-value competitors, forming a barrier to exit.Competitors struggle to compete as with extra value you can charge higher prices and monetize more effectively, forming a barrier to entry.
Ultimately they protect you from competitors eating away at your margins and market share.
Why is it so effective? People don’t want to switch to an inferior choice. The psychological concept of ‘Anticipated regret’ explains that when thinking about switching, it’s common to feel an element of fear about what could go wrong.
This fear keeps us doing what we’re already doing. That's why an innovative product often needs to be 10X better to make switching the obvious choice.
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