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.
Tips
- 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.
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.