Viral growth models for social media and open source
How many people come to your site only matters when you have consistency. Otherwise the metrics skew your perspective
Metrics tend to play a middling role after a social-media company is established. With a few notable exceptions, most sites hit a peak then flatten out. The same can be said for open-source projects. There are peaks, but really what you want is consistency in the numbers. Hyper-growth is not sustainable and you will eventually saturate the addressable market.
One of the things open-source projects tout is their number of downloads. Download metrics are often very flawed but can help tell the story of how big the market potential is. Social-media companies talk about their number of registered users. Neither talks much about retained users unless the metrics are very impressive.
-Invite (download)
-Test drive (installation)
-Adoption
-Retention
Andrew Chen, who originally created the model, had these eye-opening (and very logical) conclusions:
-Early on, the growth of the curve is carried by the invitations.
-However, over time the invitations start to slow down as you hit network saturation.
-The retention coefficient affects your system by creating a "lagging indicator" on your acquisition--if you have good retention, even as your invites slow down, you won't feel it as much.
-If your retention sucks, then look out: The new invites can't sustain the growth, and you end up with a rather dire "shark fin."
-Things look great at first, but if you can't retain users long-term, then you don't have a business.
My top three takeaways:
-You need adoption, but retention matters more.
-Consistency in adoption will lead to higher degree of retention (statistically, the spikes are most likely anomalies and will skew your perspective.
-It's very easy to jump the shark.
Disclosure: Jeremy Liew works for Lightspeed Venture Partners, an investor in my company.