A quick math rule for user retention
Sunday, March 16th, 2008Here’s a quick math lesson that highlights the importance of super-strong network effects and near perfect retention for any long-term web business.
In high school, you probably learned the 68-95-99.7 rule for percent of the normal curve within 1, 2, and 3 standard deviations of the mean respectively.
A similar rule for web retention is what I will call the 92-96-97.3 rule. Having month-to-month user retention of 92%, 96%, and 97.3% will get you on average 1, 2, and 3 user-years respectively per user that ever signs up on the site.
Okay, in English? If each month you lose 8% of your existing users (92% retention) from the previous month, the average use will stay for 12 months. If you can hold just 4% more of your users (96% retention), then they will stick around for 2 years. If you can hold only 1.3% more than that (97.3% retention), they will be in for 3 years.
It’s easy to think of retention percentages in the 90’s as good. It just feels good. But over the course of time, products in the low-to-mid 90’s will fade super-fast, and ones only slightly more sticky will do much, much better. Single percentage points here are mission critical, that’s why attention to detail and rigorous analytics become so important on the web.
*Note on math:Just in case anyone is wondering about the math, consider the function y = (R)^x, where R is the monthly retention coefficient. The area under the curve from 0 -> infinity represents the user-months the site will get out of each registered unique. So if you do the integral out, you will see -1/ln(R) user-months on average per registered unique for any retention cofficient R where 0
