How can you use cohort analysis to improve your SaaS revenue forecasts?

1 Step 1: Define your cohorts

To begin, you must define your cohorts based on criteria that are pertinent to your business model and objectives. For instance, customers can be segmented by the month or quarter they signed up, the plan or tier they subscribed to, the source or channel they originated from, the feature or product they used, and the action or event they completed. Combining these criteria can create more granular cohorts, like customers who signed up in Q1 2020 from organic sources and used the email marketing feature. The more precise your cohorts are, the more accurate and applicable your analysis will be.

2 Step 2: Track your metrics

The next step is to track the metrics that measure the performance and behavior of your cohorts over time. Common metrics for SaaS revenue forecasting include customer lifetime value, retention rate, churn rate, expansion revenue, and contraction revenue. Tools like Google Analytics, Mixpanel, or Amplitude can be used to track these metrics for each cohort and compare them across different time periods, such as monthly, quarterly, or annually. Tracking these metrics is essential for understanding the health of your business and making informed decisions about how to grow your SaaS company.

3 Step 3: Analyze your trends

The third step is to analyze the trends and patterns that emerge from your cohort data. Visualizations such as tables, charts, or graphs can be used to display metrics and show how they change over time. For instance, a cohort retention table can be used to observe how many customers from each cohort remain active and paying after each month, while a cohort revenue chart can be used to track the revenue generated by each cohort over their lifetime. By analyzing your trends, questions such as which cohorts have the highest or lowest CLV, retention rate, churn rate, expansion revenue, or contraction revenue? How do these metrics vary by cohort size, plan, source, feature, or action? How long does it take for each cohort to reach their break-even point? And how do these metrics change over time as cohorts mature and evolve? can all be answered.

4 Step 4: Improve your forecasts

The final step is to use your cohort analysis to improve your SaaS revenue forecasts. By utilizing historical data and trends, you can project future revenue based on customer acquisition, retention, churn, expansion, and contraction. Furthermore, you can use cohort analysis to identify and prioritize areas for improvement. This includes optimizing customer acquisition to target the most profitable and loyal cohorts, improving customer retention to reduce churn and increase loyalty, enhancing customer expansion to upsell and cross-sell more value and benefits, and minimizing customer contraction to prevent downgrades and cancellations. Ultimately, by using cohort analysis to improve your SaaS revenue forecasts, you can make informed decisions that will help you grow your business and achieve your goals.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?