Definition
Cohort analysis in email marketing groups subscribers based on a shared characteristic — typically the month they signed up — and tracks their engagement and behaviour over subsequent periods. This reveals how subscriber quality, retention, and value change over time in ways that aggregate metrics cannot show.
For example, aggregate open rate might appear stable at 20%, but cohort analysis could reveal that subscribers who joined last month open at 25% while subscribers from six months ago open at 12%. The stable aggregate number masks a decline in older cohort engagement.
Types of Email Cohorts
| Cohort Type | Grouping Basis | What It Reveals |
|---|---|---|
| Acquisition Cohort | Month or week of signup | How subscriber quality changes over time |
| Behavioural Cohort | Shared action (e.g. first purchase) | How behaviour after key events evolves |
| Campaign Cohort | Subscribers who received the same campaign | How the same message performs across segments |
| Channel Cohort | Acquisition source (e.g. organic vs paid) | Which channels deliver the best subscribers |
| Engagement Cohort | Engagement level at a point in time | How retention strategies affect different groups |
Key Metrics to Track by Cohort
- Open rate over time: Does engagement decline as the cohort ages?
- Click-through rate over time: Do subscribers click less the longer they are on your list?
- Retention rate: What percentage of subscribers are still engaged after 3, 6, 12 months?
- Revenue per subscriber: How does per-subscriber revenue change across cohorts?
- Churn rate: When do subscribers in each cohort tend to disengage?
How to Perform Cohort Analysis
- Define your cohorts: Choose a meaningful grouping based on your business questions
- Set your time periods: Weekly or monthly periods work best for most email programmes
- Choose your metrics: Focus on 2-3 key metrics per analysis
- Build a cohort table: Create a grid with cohorts as rows, time periods as columns, and metrics as values
- Look for patterns: Identify trends, anomalies, and significant differences between cohorts
Example
A cohort table for open rate by acquisition month might show:
| Month Joined | Month 1 | Month 2 | Month 3 | Month 6 |
|---|---|---|---|---|
| January | 45% | 28% | 22% | 14% |
| February | 42% | 26% | 20% | 12% |
| March | 47% | 30% | 24% | 16% |
This reveals that engagement declines predictably over time, but some cohorts (March) maintain slightly higher engagement, suggesting that acquisition source or messaging quality improved.
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Frequently Asked Questions
Regular reporting shows current period metrics for the entire list. Cohort analysis shows how specific groups behave over time. Regular reporting answers "what is our open rate this month?" Cohort analysis answers "how does open rate change as subscribers age?"
A good 6-month retention rate for email subscribers is 40-60% for active engagement. Rates vary significantly by industry and email type. Transactional subscribers retain better than newsletter subscribers because they have a recurring need.
Many email service providers include basic cohort reporting. For advanced analysis, export subscriber activity data to Google Analytics, Mixpanel, Amplitude, or a business intelligence tool like Tableau or Metabase.