How to forecast returning customers?
Estimating the number of returning customers is the most important part of revenue forecasting.
It is done in 3 steps:
1. Breaking down existing customers into more granular cohorts, since different cohorts have different behavior.
2. Projecting baseline of retention rate for each cohort, using historical trend for that cohort.
3. Applying any seasonal or ad-hoc corrections to the baseline, that have not been factored into the trend.
Let's understand it with an example:
Assume a SaaS company has 2,400 customers. The existing customers can be divided into three cohorts:
- 2023 cohort with 1,000 customers (expected retention rate from trend: 90%),
- 2022 cohort with 800 customers (expected retention rate: 85%), and
- 2021 cohort with 600 customers (expected retention rate: 80%).
To project the number of existing customers for Jan-2024, calculate the returning customers expected from each cohort:
- 2023 Cohort: 1,000 × 0.90 = 900
- 2022 Cohort: 800 × 0.85 = 680
- 2021 Cohort: 600 × 0.80 = 480
Total Returning Customers in Jan-2024 = 900 + 680 + 480 = 2,060
Note: We will go deeper into ways to calculate baseline rate from historical trends, and apply ad-hoc corrections, in the skill set on "Analytical Skills for Growth".