Cohort Retention Table & Chart Generator
Enter the initial customer count for each acquisition-month cohort plus how many remain at M1 through M6, and compare retention curves across cohorts with a line chart and a summary table.
M6 cohort retention benchmark table
| Tier | M6 retention rate | Meaning |
|---|---|---|
| Excellent | 90% or higher | Top-tier stickiness typically seen in enterprise SaaS, with a curve that is nearly flat |
| Good | 80–89% | A healthy level indicating an effective customer success program |
| Fair | 70–79% | An average level commonly seen in SMB-focused SaaS |
| Poor | Below 70% | The curve is still trending downward, signaling a need to revisit onboarding and customer success |
Note: healthy benchmarks vary widely by customer segment (enterprise vs. SMB/self-serve). Use these figures only as a general guide.
What a cohort retention table shows
A cohort retention table groups your customers by when you acquired them and lays out how many of each group are still with you month after month. Enter the number of customers at acquisition (M0) and the number still active at M1 through M6 for each cohort, and this tool gives you the retention rate at every point, a curve for each cohort, and a verdict at M6. What it buys you over a single company-wide churn figure is the ability to separate out which intake of customers is leaving, and when.
One rule governs the input: the count at each point cannot exceed the point before it. If you want to account for customers who cancelled and later came back, subtract them and enter the net figure. The verdict is based on the M6 retention rate — 90% or above is Excellent, 80% or above Good, 70% or above Fair, and anything below that Poor. Because the healthy range depends heavily on your customer segment, read the gaps between cohorts rather than the absolute number.
How to build a cohort retention table
- Name the cohort and enter its starting size Give it a name that identifies the intake, such as "Acquired January 2026". M0 is the number of customers you had at that moment.
- Enter the survivors at M1 through M6 Work through each month in order, entering how many were still active. A figure larger than the previous month is rejected.
- Add more cohorts and line them up Use "Add cohort" to stack several intakes. Comparing the curve before and after a change is the point of the exercise — a single cohort on its own tells you very little.
- Read the shape of the curve A curve flattening out means customers are settling in; one still sloping downward means the leaking has not stopped. The M6 verdict is a shorthand for this.
Tips for getting more out of it
- Group customers acquired in the same period into a single cohort and track how many remain over time — this reveals stickiness patterns a single month's churn rate cannot show.
- Plotting several cohorts side by side lets you compare retention curves before and after a change, such as an onboarding improvement or a pricing update.
- A curve that flattens out around M3–M4 is a healthy sign that customers who stick around keep using the product long-term. A curve that keeps declining points to an ongoing churn driver worth investigating.
- Our Logo Churn Rate tool gives a single-period snapshot; use this tool instead when you want to compare retention trends over time.
Where cohort analysis earns its keep
Measuring whether onboarding changes worked
Put the cohorts from before and after the change side by side and look at the drop between M1 and M2. This is exactly the kind of movement a company-wide churn number hides.
Tracking the effect of a price change
If only the cohorts acquired after the new pricing fall away sharply, you have evidence that price and perceived value have drifted apart.
Comparing customer segments
Enter enterprise and SMB customers as separate cohorts and the difference in what counts as healthy becomes a number rather than an opinion.
Explaining the business to a board or an investor
A cohort table conveys the reality of retention far better than a single churn percentage, because improvements leave a visible mark in the shape of the curve.
Cohort analysis terms explained
- Cohort
- A group of customers acquired in the same period. The word comes from epidemiology, where it means a group sharing a common experience; in SaaS it almost always means the customers who signed up in a given month.
- Retention rate
- The share of a cohort still active at a given point. A 70% figure at M6 means seven of every ten customers are still with you six months after they arrived.
- M0 to M6
- A shorthand for months elapsed since acquisition, with M0 being the moment of acquisition itself. M6 is six months later.
- Churn
- The mirror image of retention — the share of customers who left. Saying retention is 70% and saying churn is 30% are the same statement.
- Resurrection
- A customer who cancelled and later signed up again. This tool assumes net survivors, so subtract returning customers before entering your figures.
- A flattening curve
- The point at which month-on-month losses stop and the line goes horizontal. It marks the core of customers who have genuinely settled in, and the higher it flattens, the steadier the business.
Frequently Asked Questions
Side Note — Why cohort analysis groups customers by acquisition period
Most churn and retention metrics widely used as SaaS KPIs are just a snapshot at a single point in time. But customers acquired at different times can show very different stickiness patterns going forward. For example, customers acquired after an onboarding flow was improved often retain better than the cohort acquired before that change. Cohort analysis emerged specifically to make this kind of "when were they acquired" difference visible.
The idea did not originate in SaaS at all — it traces back to epidemiology, where researchers track the survival rate of a group of people born in the same year. When the concept was carried over into business, "cohort" was redefined from "birth year" to "the month a customer signed up," and it became a standard visualization pattern in investor decks and product-improvement dashboards.
The phenomenon where a retention curve flattens out over time is called "cohort flattening," and it is one of the key things investors look for when evaluating a SaaS company. If a curve never flattens and keeps sliding downward, it means the moment new customer acquisition stops, the entire customer base starts shrinking — a signal often used to judge whether continued growth spending is justified.