[idoh]

Definitely an interesting article and one worth reading. I work a lot on viral growth and I'd like to add a counterpoint that the growth of apps is so complicated that it is basically impossible to model in a useful way.

I've found that even if I make no changes to an app, the retention and virals fluctuate quite a bit for no apparent reason, and the fluctuations are big enough that it makes long term forecasting really more of guesswork than anything else.

Also, there are second order effects that are hard to model as well. For instance, improving virals can improve retention (user A invites friend B, user A stays for longer because their friend uses it).

I've gone through the process of modeling a couple apps, and it quickly gets to a point where the relationships become circular and small variations cause exponential differences down the line.

It is important to make informed decisions about virals and retention, but I don't think such a model is the way to do it. I think it is more important to think about optionality and decision making in opaque environments rather than trying to model the unmodelable.