SaaS Cohort Analysis
Aggregate churn can look healthy while your most recent cohort quietly falls apart. Paste an aggregated cohort table — customers or MRR by start month — and see retention by cohort age as a heatmap, curves, and a straight answer on whether newer cohorts are doing better or worse. No signup required.
How It Works
1
Choose customers or revenue
Logo retention asks what share of the customers who joined are still here. Revenue retention asks what share of the MRR they brought is still being billed — and with expansion included it can pass 100%.
2
Enter one row per start month
What each cohort started with, then what was left one month later, two months later, and so on. Type it in or paste it straight from a spreadsheet. Aggregated totals only — no customer records, ever.
3
Read the pattern, not the number
A retention heatmap, per-cohort curves, weighted month-3/6/12 figures, and a plain reading of whether newer cohorts are retaining better or worse than older ones — plus a CSV export. Nothing is stored and no signup is required.
Your cohort table
One row per start month. Enter how many customers that cohort started with, then what was left at each month after — leave the months a cohort has not reached blank.
Months to show
| Cohort | Started | M1 | M2 | M3 | M4 | M5 | M6 | Remove cohort |
|---|---|---|---|---|---|---|---|---|
Retention heatmap
Each row is a cohort; each column is how many months after that cohort started. Every cell shows its own number, so the table reads without relying on colour.
| Cohort | Started | M0 | M1 | M2 | M3 | M4 | M5 | M6 |
|---|---|---|---|---|---|---|---|---|
| 2025-08 | 120 | 100% | 87% | 79% | 74% | 70% | 67% | 64% |
| 2025-09 | 135 | 100% | 88% | 81% | 76% | 73% | 70% | — |
| 2025-10 | 148 | 100% | 90% | 84% | 80% | 76% | — | — |
| 2025-11 | 162 | 100% | 91% | 86% | 83% | — | — | — |
| 2025-12 | 155 | 100% | 92% | 88% | — | — | — | — |
| 2026-01 | 180 | 100% | 93% | — | — | — | — | — |
| Weighted | 900 | 100% | 91% | 84% | 79% | 73% | 68% | 64% |
The diagnosis
What the newer cohorts are doing against the older ones
At month 5, newer cohorts retain 69.6% of their customers against 66.7% for older ones — 3.0% better. What you changed since the older cohorts signed up is working.
78.6%
64.2%
—
The full working
Logo retention (month n) = Customers still active at month n ÷ Customers at month 0 Weighted retention (month n) = Σ customers still active at month n ÷ Σ customers at month 0, across every cohort that has reached month n
Retention curves
Each cohort as it ages, against the weighted average
Key Insights
Aggregate churn blends every cohort into one number, so a deteriorating recent cohort can hide behind a large, well-retained older one for months. The column comparison above is what surfaces it.
Logo retention counts customers equally. Run the same table on revenue to see whether the customers leaving were the small ones or the ones that mattered — and check net revenue retention for the expansion side.
Retention sets how long a customer is worth paying to acquire. Feed the curve into lifetime value and CAC payback before you decide the acquisition spend was working.
Cohorts that hold their revenue are cohorts a lender will underwrite.
Retention by cohort is the clearest evidence that recurring revenue is durable. Turn it into capital without giving up equity.
How to Do Cohort Analysis for SaaS
The SaaS Cohort Retention Formula
Retention (month n) = Value still active at month n ÷ Value at month 0
Always divided by the cohort's starting size — never by the previous month
A cohort is every customer who started in the same period, usually a month. Cohort analysis follows each of those groups separately as it ages, so month 3 for a cohort that signed in January and month 3 for a cohort that signed in June sit in the same column and can be compared directly.
Worked example: 120 customers signed up in August, and 89 of them were still customers three months later. Month-3 logo retention for that cohort is 89 ÷ 120 = 74.2%. If the November cohort of 162 customers has 134 left at month 3, that is 82.7% — 8.5 points better at the same age. The two cohorts are at different points in calendar time, but at the same point in customer life, which is the only comparison that means anything.
The single most common mistake is dividing by the previous month instead of the cohort start. That gives you a month-over-month survival rate, not retention, and chaining those rates hides exactly the deterioration cohort analysis exists to expose.
Logo Cohorts vs Revenue Cohorts
The same table answers two different questions depending on what you put in the cells, and healthy businesses routinely look different in each.
| Logo cohorts | Revenue cohorts | |
|---|---|---|
| What is in the cell | Customers still active | MRR still being billed |
| Can exceed 100% | No — a cohort is a closed group | Yes, once expansion is included |
| Answers | Is the product holding people? | Is the revenue durable? |
| Blind spot | Treats a $50 and a $5,000 account the same | A few large accounts can mask heavy small-customer churn |
Run both. Revenue retention comfortably above logo retention means your larger accounts are the ones staying and expanding — good for durability, but a concentration risk worth naming. The reverse means you are keeping customers while losing the revenue they used to spend, which usually shows up as downgrades before it shows up as churn. The aggregate version of the revenue view is net revenue retention, and the aggregate version of the logo view is your churn rate.
How to Read a Retention Heatmap
Read down a column, not across a row. A column holds every cohort at the same age, so differences between them are differences in the cohorts themselves — who you acquired, what you onboarded them into, what the product did for them. Reading across a row only tells you that customers leave over time, which you already knew.
A steep month-1 drop that then flattens is an onboarding or expectation problem, not a product problem. The customers who make it past the first month behave well; the ones who leave never got started. Fix activation before you spend more on acquisition.
A curve that never flattens means there is no retained core. Every cohort eventually goes to zero, and growth is a treadmill that gets more expensive with every month of scale.
Later columns getting worse for newer cohorts is the finding that matters most and the one aggregate churn hides longest — a large, well-retained older cohort can carry the blended number for months while everything you signed this quarter falls away.
A single anomalous row is usually a pricing change, a discount campaign, or a channel experiment that ran in that month. Annotate it rather than averaging it away.
Mistakes That Distort SaaS Cohort Analysis
- 1.
Judging a cohort before it has aged.A cohort that is two months old has two months of data. Putting it in the same conversation as a twelve-month cohort's month-12 number is comparing different questions — which is why the last few cells of a cohort table are always empty, and should be.
- 2.
Averaging cohorts of wildly different sizes. A simple mean lets a 6-customer cohort move the curve as much as a 600-customer one. Weight by cohort size — this tool does, and the weighted row is usually the one worth quoting.
- 3.
Mixing self-serve and enterprise in one cohort. They retain on completely different curves, and blending them produces a shape neither segment actually has. Run the table once per motion if the two are material.
- 4.
Counting trials, or counting win-backs into the original cohort. A cohort should be customers who started paying in that month. A returning customer starts a new cohort — folding them back into the old one is what produces logo retention above 100%, which cannot happen.
- 5.
Reading a two-point difference as a trend. With small cohorts, a couple of percentage points is one or two customers. Look for a direction that holds across several consecutive cohorts before you act on it.
How Cohort Retention Affects Your Funding Options
Retention is the part of a SaaS business that underwriting actually rests on. A lender advancing capital against recurring revenue is making one judgment: will that revenue still be there over the repayment term. Aggregate churn is a weak answer to that question because it is backward-looking and blended. A cohort table is a much stronger one, because it shows whether the revenue you are signing today behaves like the revenue that has already proven durable.
It also changes what the capital is worth taking for. If cohorts are holding and CAC payback lands inside the retained life you can see in the curve, spending more on acquisition compounds. If newer cohorts are deteriorating, funding acquisition simply buys more of a leak — and the honest move is to fix retention before raising anything at all. Feed the curve into lifetime value and check the result against what you pay to acquire before deciding.
For founders who would rather not sell equity to fund that growth, non-dilutive SaaS financing prices the same retention as borrowing capacity instead of as a multiple. Founderpath funds bootstrapped SaaS companies from $10K MRR against recurring revenue, repaid from revenue — no equity, no board seats. The cohort table you just built is close to the evidence that conversation runs on.
Related SaaS Calculators
Cohort retention sets the ceiling on almost every other SaaS number. These calculators work on the aggregate versions of the same questions.
Financial Health
Profit and Loss Statement Template — Build a P&L and export it to Excel, Google Sheets or PDF
SaaS Chart of Accounts Template — Generate a SaaS-specific chart of accounts and export it to Excel or Google Sheets
Burn Rate Calculator — Calculate net burn rate, cash runway, and burn multiple
ARR Calculator — Calculate annual recurring revenue from monthly subscriptions and annual contracts
MRR Calculator — Break down new, expansion, contraction, and churned MRR
Churn Rate Calculator — Measure customer and revenue churn with annualized projections
NRR Calculator — Track net revenue retention and gross revenue retention rates
SaaS Quick Ratio Calculator — Measure growth efficiency — MRR gained for every dollar lost to churn
Growth Rate Calculator — Calculate MoM, YoY, and CAGR growth rates from revenue data
Break-Even Calculator — Find the units and revenue needed to cover all costs and reach profitability
EBITDA Margin Calculator — Calculate EBITDA margin and benchmark against SaaS and industry norms
SaaS Runway Calculator — See how many months of cash you have left and model scenarios to extend it
SaaS Financial Model Template — Forecast MRR, ARR, burn, and runway over 24 months with scenario comparison and CSV export
SaaS ROI Calculator — Decide whether a hire, campaign, or tool returns more than it costs
SaaS Proration Calculator — Work out what a mid-cycle upgrade, downgrade, or cancellation costs
SaaS Debt Capacity Calculator — See how much debt your recurring revenue can safely carry, and what limits it
Customer Metrics
CAC Calculator — Measure customer acquisition cost and LTV:CAC ratio
LTV Calculator — Calculate customer lifetime value, lifespan, and LTV:CAC ratio
Payback Period Calculator — Calculate how long it takes to recover customer acquisition costs
Viral Coefficient Calculator — Measure your K-factor and model viral growth scenarios
SaaS Magic Number Calculator — Measure sales efficiency — net-new ARR per dollar of S&M spend
Pricing & Valuation
Markup Calculator — Calculate markup percentage, selling price, profit, and gross margin
Equity Dilution Calculator — Model how funding rounds affect founder ownership over time
SaaS Valuation Calculator — Estimate your company value using ARR multiples and growth-rate benchmarks
Revenue Multiple Calculator — See what ARR multiple your growth rate, NRR, and gross margin justify
Rule of 40 Calculator — Score your growth-plus-profitability against the Rule of 40 benchmark
Retention is the argument. Your cohort table is the evidence.
Founderpath turns durable recurring revenue into capital — without dilution.
A cohort that still bills 80% of its revenue a year after signing is not a growth story, it is an underwriting file. Equity investors price that as a multiple; a revenue-based lender prices it as capacity. If your cohorts hold, you can raise against them and keep every point of ownership the retention earned you.
Connect your billing data and the cohort behaviour you just charted becomes the underwriting file — no forecast to defend, no board deck to build.
Cohorts that hold are the hardest thing in SaaS to build. Selling equity to fund growth hands away a permanent share of them; revenue-based financing costs a known amount and ends when it is repaid.
Up to $5M against recurring revenue from $10K MRR, repaid from revenue. As retention and MRR improve, so does what you can draw.
Frequently Asked Questions
Always divide by the cohort's starting size, never by the previous month. Example: 120 customers signed up in August and 89 were still customers three months later, so month-3 retention is 89 ÷ 120 = 74.2%. Dividing by the previous month instead gives a month-over-month survival rate, which chains together in a way that hides exactly the deterioration cohort analysis exists to expose.
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