Cohort Retention Builder
Paste a flat list of customer, period, and revenue rows and get a full cohort retention triangle with retention curves and blended NRR. The analysis that takes an afternoon of pivot tables and array formulas, in one paste.
How do I build a cohort retention analysis?
Group customers by the period they first paid you, then track what that same group spends in each subsequent period. Divide each period's cohort revenue by that cohort's first-period revenue and you get the retention curve. Doing it properly in a spreadsheet means a pivot table, a triangular layout, and a set of array formulas that break whenever a customer skips a month, which is why most teams build it once, discover it is wrong, and go back to reporting blended churn instead.
How to use this tool
- 1
Paste a flat list
Three columns: customer, period, revenue. Straight out of your billing export, no pivoting, no sorting, no cleanup.
- 2
Read the triangle
Every cohort by first-purchase period, with retention percentage at each month of age and a colour scale on the whole grid.
- 3
Check the curve
Average retention by cohort age, plus blended net revenue retention, so you can see whether newer cohorts hold better than older ones.
Blended churn hides the trend that actually matters
A single churn number averages good cohorts with bad ones and tells you nothing about direction. Four things only a cohort view shows.
Whether the product is getting stickier
If cohorts acquired this year retain better at month six than cohorts from two years ago, the product or the onboarding improved. Blended churn cannot show this, because it mixes every cohort into one number.
Where the curve flattens
Most retention curves drop steeply then flatten. The month it flattens is your real retained base, and it is the only defensible input to a lifetime value calculation.
Whether growth is masking churn
Rapid new-customer acquisition holds total revenue up while the existing base erodes underneath. The cohort triangle separates the two; a revenue chart cannot.
Which acquisition period went wrong
A single bad cohort usually traces to something specific: a pricing experiment, a channel, a quarter when onboarding was understaffed. Blended metrics smear that signal across every period.
The cut this cannot make
This builds the triangle from what you paste. The questions that follow it: is this cohort worse because of the channel it came from, the price it paid, or the month it landed in: need the cohort joined to your CRM, your pricing history, and your support data. That join is a different project every time it is asked, and by the time it is built the question has usually moved on.
See how DataWyse answers thisQuestions finance teams ask about this tool
What format does the data need to be in?
Three columns: a customer identifier, a period label such as 2026-01, and a revenue amount. One row per customer per period. Extra columns are ignored, and rows can be in any order: the tool groups and sorts them for you.
What is the difference between cohort retention and churn rate?
Churn rate is a single number for a period, blending every customer regardless of when they joined. Cohort retention tracks each joining group separately over time, which shows whether retention is improving or deteriorating. Churn tells you what happened; cohorts tell you which direction you are heading.
Should cohorts be built on revenue or customer counts?
Revenue, for financial planning, because it captures expansion and contraction as well as outright loss. Customer-count cohorts are useful for product and onboarding questions. Revenue cohorts can exceed 100% retention when expansion outweighs churn; count-based cohorts cannot.
How many periods do I need for this to be useful?
At least six periods to see a curve shape, and twelve to say anything confident about where it flattens. With fewer than six you can still spot a badly performing cohort, but you cannot yet distinguish a steep early drop from a genuine long-term decline.
Why does my cohort retention exceed 100%?
Because existing customers expanded. Revenue-based cohort retention includes upsells and seat growth, so a cohort spending more this year than in its first year retains above 100%. That is the same effect that makes net revenue retention exceed 100%, and it is a good sign.
Is this tool really free?
Yes. No signup, no email required, no usage limit. It runs entirely in your browser: nothing you type is uploaded to a server or stored anywhere. We build these because the people who find them useful are the people who eventually need a financial analyst that works the same way.
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