Glossary: Cohort Analysis
Cohort analysis groups users or wallets by a shared starting event, trait, or behavior, then compares retention, revenue, activity, or conversion over a common elapsed-time horizon.
What is Cohort Analysis?
Cohort analysis groups users or wallets by a shared starting event, trait, or behavior, then compares how those groups change over a common elapsed-time horizon. Unlike a segment, which describes who matches a rule now, a cohort usually preserves membership so teams can measure retention, revenue, activity, or conversion over time.
Cohort Analysis Explained
Cohort analysis means studying groups of people who have something in common.
For example, one group might be users who signed up in January. Another group might be users who signed up in February.
Instead of mixing everyone together, cohort analysis compares each group separately.
This helps teams see whether newer users are staying longer, leaving faster, spending more, or behaving differently than older users.
What Cohort Analysis Means For
Audience | Use Case |
|---|---|
Product teams | Understand how different user groups adopt features, stay active, or drop off over time. |
Growth teams | Compare users from different campaigns, channels, or signup periods to find higher-quality acquisition sources. |
Founders and analysts | Measure retention, churn, revenue, and user behavior by group instead of relying only on overall averages. |
Examples
A SaaS company compares users who signed up in January, February, and March to see which group has the best 30-day retention.
A crypto protocol tracks wallets that made their first deposit during a rewards campaign and compares them with wallets acquired organically.
A marketplace studies buyers who joined through referrals versus paid ads to see which group makes more repeat purchases.
A product team analyzes users who adopted a new feature in their first week and checks whether they remain active longer than users who did not.
Wallet-level cohort examples
Wallet cohorts can be based on acquisition date, first qualifying action, campaign, product behavior, value band, or lifecycle stage. Examples include wallets first seen in the same week, wallets acquired by one partner, wallets that used a specific feature, and wallets that entered a high-value tier during a selected month.
Cohorts and segments answer different questions
Use a cohort to compare groups from a shared origin across elapsed time. Use a segment to filter the current audience by properties or behavior. A useful analysis may start with a fixed acquisition cohort, then break its results down by wallet segment without changing who belongs to the original cohort.
Related reading
Explore retention analytics, Wallet Cohort, Retention Rate, Cohort Retention Curve, and the DeFi cohort analysis guide.
FAQs
What is a cohort?
A cohort is a group of users who share a common trait, event, or time period.
What is cohort analysis used for?
Cohort analysis is used to compare how different user groups behave over time.
Why is cohort analysis important?
It helps teams see patterns that overall averages can hide.
What is an example of a cohort?
Users who signed up in the same month or came from the same campaign are examples of cohorts.
Is cohort analysis only for retention?
No. It can also study revenue, churn, feature adoption, purchases, and engagement.
Related Terms
A/B Testing
An experiment that compares two versions of a page, feature, or campaign to see which performs better.
Account Abstraction
Account abstraction is an approach that turns blockchain accounts into programmable smart contract wallets, enabling features like gasless transactions, social recovery, session keys, and paying fees in any token.
Activation Rate
Activation rate is the percentage of new users or wallets that complete a key activation milestone, such as a first transaction, out of all users who signed up or connected within a given period.
Active Users
Active users are distinct users, accounts, visitors, wallets, or wallet clusters that complete a defined meaningful action during a specified period; the chosen identity unit and activity rule determine the result.
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