Net Revenue Retention by Cohort

The average hides the trend

Cohort NRR tracks retention for one dated group of customers over time, which is the only way to see whether recent business is as good as older business. A blended net revenue retention figure is a weighted average across every customer you have. Mature accounts with years of seat growth sit in the same number as accounts signed last quarter. When the recent cohorts weaken, the mature base absorbs the damage for several quarters before the blended number moves, and by then the cause is a year old.

How to build the view

Group customers by the month or quarter they first closed. For each cohort, record starting recurring revenue, then for every month after, record the same cohort's recurring revenue including upsell, cross-sell, and usage growth, net of churn and downgrades. Divide the later figure by the starting figure. Plot the cohorts as rows and the months since signing as columns.

The result reads two ways. Reading across a row shows how one cohort develops. Reading down a column compares every cohort at the same age, which is the comparison that exposes deterioration.

Reconcile it to the waterfall

Cohort curves only hold up if the underlying movement is categorized consistently. ORM builds a monthly reconciling waterfall that runs from Beginning ARR to Ending ARR, with contraction split into Churned Customer ARR, Churned Product ARR, and Product Decrease ARR, and expansion split into New Customer ARR, New Product ARR, and Increase Product ARR. Beginning ARR for each month equals the prior month's Ending ARR, which forces the movements to tie out.

Cohort analysis inherits that structure. Without it, an account that swaps one product for another can register as both churn and expansion, and the cohort curve moves for accounting reasons rather than customer reasons.

What to do with the curve

Three decisions depend on it. Pricing and packaging changes should be tested against the cohorts that signed after the change, not against the blended base. Ideal customer profile decisions should be made on cohort curves segmented by firmographic, since the segment that expands is rarely the segment that closes fastest. Forecasting the base should use the cohort curve for accounts at that tenure rather than one company-wide retention assumption. That last point matters most for revenue forecasting, because a company with a heavy recent-cohort mix and a declining curve will forecast expansion it does not get.