Cohort analyses: How do you know if you're improving your product?One of the most important and yet tricky things to do is to determine whether your product is improving. Lots of startups use cohort analysis to inform these decisions -- essentially segment groups of users often based on when they joined the site. If the performance of the more recent groups look better (e.g. they are more engaged, spending more money, etc), you're improving. Though the concept is easy, there isn't a clear way to segment the cohorts. Moreover, when it comes to using cohort analysis to determine the lifetime value and churn of your customers, the math can start to get hairy. These articles provide different perspectives on how to tactically run good cohort analyses. Get your spreadsheets ready to rumble!
Enjoy,
Elizabeth
 | So while funnels are a great visualization tool, funnels alone are not enough. The analytics tools today work well for micro-optimization experiments (such as landing page conversion) but fall short for macro-pivot experiments. The answer is to couple funnels with cohorts. |
Considering there are services designed specifically for user engagement tracking and customer cohort analysis, it may seem a little odd that we’re going to focus on the one that isn’t. As it turns out, there are good reasons to consider Google Analytics for cohort analysis. |
 | I put in these particular elements because I did a study of the reasons people cancel at WP Engine, and these are the main reasons for cancellation. We log every cancellation – spending time running after folks to wring out the cause — so we can deduce exactly what we can do to prevent it in future. (Of course you should do this too and get your own data.) |
Many social games do their cohort analysis on a daily or weekly basis, whereas some ecommerce companies whose purchases are less frequent may do their cohort analysis on a quarterly basis. This will dictate how long you have to collect data before you have enough data to project forward. |
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