The cohort analysis blog post series
- Cohort analyses for digital businesses: an overview
- Performing cohort analysis on web analytics data using SnowPlow
- Performing the cohort analysis described by Eric Ries in the Lean Startup
- On the wide variety of cohort analyses
- Approaches to measuring user engagement as part of cohort analysis
- Approaches to measuring customer value as part of cohort analysis
- Faking cohort analysis with Google Analytics
As part of our cohort analysis series, we have emphasized that there are a wide variety of different cohort analyses that are possaible, depending on the business question to be answered. To recap, just quickly, we can vary the cohort analysis by what metric we use to compare between cohorts, and by how we define our cohorts. We have written a post about comparing user engagement between different cohorts, and how this is valuable to especially to social networks, community sites and publishers. In this post, we look at comparing customer value, including customer lifetime value (CLV) between cohorts. We explain why this is important to all companies whose business models depend, at the end of the day, on monetizing users – including retailers, media companies and financial services companies. Lastly, we look at how to measure these values in SnowPlow, so that an appropriate cohort analysis can then be performed, as described in our previous blog post.

Weighing your customers' value






