Strategy
Cohort Analysis
A practical product method for comparing user groups, tracking retention, and understanding behavioural change over time.
How to use cohort analysis to compare user groups, understand retention and engagement, and measure the impact of changes over time.
What it is
glossaryCohort AnalysisCohort analysis groups users based on shared characteristics to analyse how those groups behave over time.Open glossary term is a quantitative UX and product method used to group users based on shared characteristics and track their glossaryBehaviourBehaviour refers to how users interact with a system, including actions, patterns, and responses.Open glossary term over time.
A cohort might be users who signed up in the same week, used a glossaryFeatureA feature is a specific piece of functionality within a product that delivers value to users. It represents something users can do or experience as part of the overall product.Open glossary term for the first time, or came from a specific glossaryChannelA channel is a source or pathway through which users arrive at a product, such as search, social media, paid ads, or direct traffic.Open glossary term.
Instead of looking at all users as one group, glossaryCohort AnalysisCohort analysis groups users based on shared characteristics to analyse how those groups behave over time.Open glossary term shows how glossaryBehaviourBehaviour refers to how users interact with a system, including actions, patterns, and responses.Open glossary term changes across different groups and over time.
The goal is to understand glossaryRetentionRetention measures how well a product keeps users over time by continuing to deliver value. It is a key indicator of product success and long-term viability.Open glossary term, glossaryEngagementEngagement refers to how users interact with a product, content, or experience, including actions like clicks, time spent, and interactions.Open glossary term, and the impact of changes on different user segments.
Cohort analysis is useful when averages hide important differences between user groups.
When to use it
Use this method when time and glossaryBehaviour PatternA behaviour pattern is a repeated way in which users interact with a product or system.Open glossary term matter.
It is most useful when:
It is less useful when:
Cohort analysis is often used alongside feature usage analysis and funnel analysis to provide deeper insight into behaviour over time.
Key takeaway
Use cohort analysis when you need to understand how behaviour evolves across meaningful groups, not just across the total user base.
How to run it
Set up properly
Be clear on how cohorts are defined, what glossaryBehaviourBehaviour refers to how users interact with a system, including actions, patterns, and responses.Open glossary term you are tracking, and over what period. A cohort is a group sharing a starting characteristic, most often when they joined.
Choose the cohort definition to answer a question. Grouping by signup month is conventional; grouping by glossaryAcquisitionAcquisition is the process of attracting new users or customers to a product, service, or platform.Open glossary term glossaryChannelA channel is a source or pathway through which users arrive at a product, such as search, social media, paid ads, or direct traffic.Open glossary term or first action is frequently more useful.
Run the method
glossaryCohort AnalysisCohort analysis groups users based on shared characteristics to analyse how those groups behave over time.Open glossary term separates change in your product from change in your audience. Without it, an improving average can hide every recent cohort performing worse than the last.
- Group users by a shared starting characteristic, and keep the definition fixed for the whole analysis.
- Track each cohort forward through time from its own start point, not against the calendar.
- Measure the metric that matters (glossaryRetentionRetention measures how well a product keeps users over time by continuing to deliver value. It is a key indicator of product success and long-term viability.Open glossary term, glossaryEngagementEngagement refers to how users interact with a product, content, or experience, including actions like clicks, time spent, and interactions.Open glossary term, glossaryConversionA conversion is any action a user takes that aligns with a defined goal, such as making a purchase, signing up, or completing a task.Open glossary term) consistently across cohorts.
- Compare cohorts against each other. The comparison is the method; a single cohort is just a chart.
- Identify where trends shift, and line those points up against what you shipped or changed.
Read down the cohorts as well as across. Improvement within a cohort over time and decline between successive cohorts are different findings with opposite implications.
Capture and make sense of it
The value comes from separating product change from audience change. Look across the glossaryDataData is raw, uninterpreted information collected and stored so it can be analysed, processed, or used to inform decisions. On its own it carries no meaning; context and interpretation are what make it useful.Open glossary term to identify:
- How glossaryBehaviourBehaviour refers to how users interact with a system, including actions, patterns, and responses.Open glossary term develops within a cohort over time
- Whether newer cohorts perform better or worse than older ones
- Points where the trend shifted, and what changed then
- Cohorts that behave unusually, which often marks a glossaryChannelA channel is a source or pathway through which users arrive at a product, such as search, social media, paid ads, or direct traffic.Open glossary term problem
Use this to understand whether things are genuinely improving. Aggregate metrics are the most reliable way to be wrong about that.
What to look for
Focus on:
Where it goes wrong
Most issues come from:
If cohorts are not meaningful, the glossaryInsightAn insight is a meaningful understanding that explains why something is happening and what it means.Open glossary term will not be either.
What you get from it
Done properly, this method gives you:
Key takeaway
It helps you see how behaviour evolves, not just what is happening now.
Get in touch
If this sounds like something you need, we can help you understand how different users behave over time and what drives retention.
No guesswork. No assumptions. Just clear insight you can act on.
FAQ
Common questions
A few practical answers to the questions that usually come up around this method.
What is cohort analysis in UX?
Cohort analysis is a method used to group users and track their behaviour over time.
When should you use cohort analysis?
Use it when analysing retention, engagement, or the impact of changes across different user groups.
What is a cohort?
A cohort is a group of users who share a common characteristic, such as sign-up date or behaviour.
How does cohort analysis improve products?
It helps identify trends, measure impact, and understand long-term behaviour.
What tools are used for cohort analysis?
Product analytics platforms such as Amplitude, Mixpanel or PostHog have cohort views built in, and GA4 covers simpler cases. Anything bespoke (cohorts defined by attributes those tools do not hold) usually ends up as SQL against the warehouse.
Quick take
If you want to understand how different groups of users behave over time, use cohort analysis.
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