Revenue Retention Analysis: Calculation and Visualization

June 3, 2010

This blog post is about how to visualize data in a billings/revenue retention analysis, and part of a series of posts on how to prepare and conduct such an analysis and interpret the results. Beyond the insights you will gain, conducting the analysis will be helpful for most expansion stage companies hoping to raise expansion capital. Many venture capital firms will perform this analysis at some point during the due diligence process. Presenting this data up front will save them time and likely impress them with your “metrics-driven approach” to management.

Once the cohorts have been time-adjusted, you can make a number of calculations and charts that show revenue/billings retention over time. You can calculate the average bill over time (of the customers that signed up in Q1 and stayed on, what was the average spend in month 1, 2, 3, etc.?), total spend over time (how much did the customers who signed up in Q1 spend in their first month as a customer, in month 2, 3, etc.?), and spend as a percentage of first month spending (did the customers who signed up in Q1 spend more or less over time?).

Once you calculate the average bill over time, the total spend over time, and monthly spend as a percentage of first month spend over time for each cohort, visualize them by creating charts that show each cohort’s behavior over time. The example below is a chart of total billings by quarterly cohort over a given time period:

In the next post, I will provide examples of revenue retention analysis results and explain how they should be interpreted.


Vlad is a CEO at <a href="">Scandent</a>, which develops radio frequency identification (RFID) systems that prevent theft, loss, and wandering/elopement in hospitals and nursing facilities. Previously, he was an Associate at OpenView.