Analyze User Retention Data from CSV or Excel Export
User retention exports contain timestamped events per user ID, typically from analytics platforms like Mixpanel, Amplitude, or your database. The file shows who came back and when, but to analyze user retention data you must calculate cohort retention percentages or identify your Day 7 drop-off by grouping thousands of rows by signup date and activity date.
Upload your user activity export and get cohort retention tables, churn lists, and DAU/MAU trends without writing grouping formulas or pivot table workarounds.
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Upload your spreadsheet.xlsx .xls .csv — free to try, no accountWhat this export contains
| user_id |
| event_timestamp |
| event_date |
| signup_date |
| event_name |
| session_id |
| first_seen |
| last_seen |
| days_since_signup |
| cohort_month |
| is_active |
| platform |
Handling Unix timestamps and timezone offsets
Some exports store event_timestamp as Unix epoch seconds (1704067200) instead of readable dates. Convert these in Excel with =(A2/86400)+DATE(1970,1,1), adjusting for your timezone offset. If timestamps include milliseconds, divide by 86400000 instead. Retention calculations require consistent date truncation—users active at 11:58 PM and 12:02 AM should count as active on two different days, which means converting timestamps to dates before grouping.
Defining your active user threshold
An 'active' user might mean any event, or specific events like completing a core action. Exports often include event_name columns with dozens of event types (page_view, button_click, purchase). Decide which events count as meaningful activity for your product. Retention calculated from all events will be higher than retention calculated from only purchase or content_created events, and both numbers are valid for different questions.
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Common questions
How do I analyze user retention data from a CSV export?
Group users by signup date into cohorts, then count how many returned in each time period after signup (Day 1, Day 7, Day 30). Calculate retention rate by dividing active users by cohort size for each period. The export gives you raw event timestamps and user IDs, but you must create the grouping logic that counts distinct users per cohort per time window.
How do I calculate Day 7 retention from user activity logs?
Group users by signup date, then count how many had at least one event between Day 7 and Day 8 after signup. Divide that count by the cohort size. The formula requires matching each user's signup date to their event dates, filtering for the 24-hour window, and handling users with no Day 7 activity.
What is the difference between retention rate and churn rate?
Retention rate is the percentage of users from a cohort still active after a time period. Churn rate is the percentage who stopped using the product. If 60% of users are retained at Day 30, then 40% have churned. Both measure the same behavior from opposite directions.
How do I create a cohort retention table in Excel?
You need a matrix where each row is a signup cohort and each column is a time period (Week 0, Week 1, etc.). Calculate this by grouping users into cohorts, then for each cohort and each week, count distinct users active and divide by cohort size. Pivot tables cannot produce this layout directly because it requires two levels of date grouping.
What does DAU/MAU ratio tell me about my product?
Daily Active Users divided by Monthly Active Users shows how often your monthly users return. A ratio of 0.5 means the average monthly user is active 15 days per month. Products with daily habits (social media, messaging) target 0.6 or higher. Products used weekly might see 0.2 to 0.3.
Why do my retention percentages exceed 100%?
This happens when your export counts the same user multiple times in one cohort, usually because signup_date varies by row instead of being fixed per user. Filter the export to one row per user with their earliest signup_date, or use DISTINCTCOUNT formulas that deduplicate user_id before calculating percentages.
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