As an online business owner, you hope that engagement increases over time, leading to a longer period of retention. This is rarely the case, though. The majority of web applications see a gradual decrease in user engagement, eventually leading to churn. Your goal then is to stretch out the length of engagement as long as possible. The best way to measure this is through cohort analysis.

Put simply, cohort analysis is used to test whether certain groups of users, based on the conversion date, are active and engaging longer (or shorter) than other groups.

The ultimate goal is to test not only how users within each cohort engaged within your app over time, but to also compare and contrast different cohorts with one another. It’s quite often the case that even subtle changes in your application’s feature set will change user engagement, positively or negatively. If the latter, you want to know this as soon as possible to prevent further churn.

That said, let’s look at how to source and cleanse your data in order to begin analysis.

如何用cohort analysis提高用户留存率？

用户增长陷入停滞，很多产品都在面临这个头疼的问题。随着人口红利和流量红利的萎缩，获取新用户的成本越来越高。相比之下，通过确立增长指标快速试验迭代的“增长黑客”来激活用户，或许是实现用户增长的有效方法。为什么我们的产品会留不住用户呢？

Cohort Analysis在投资人必用的监测公司运营状况的指标中排名第一，使用它可以穿越数据的骗局，看到公司运营的真相。