What Is Daily Active Users?
Daily active users is the count of unique users who perform at least one qualifying action in your product on a given calendar day, and it is the foundational engagement metric for apps and platforms where daily use is part of the intended experience. Most teams export it from a product analytics tool as an event-level log that requires deduplication by user and day before the count is accurate.
See the exact steps to calculate DAU from a raw event export, how to define the qualifying action correctly, and how to compute the DAU/MAU ratio in a spreadsheet.
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Upload your spreadsheet.xlsx .xls .csv — free to try, no accountWhat this export contains
| user_id |
| event_date |
| event_name |
| session_id |
| platform |
| plan_type |
| country |
| device_type |
| event_count |
| cohort_month |
What usually goes wrong with it
Event-level exports count actions, not users
Product analytics exports produce one row per event, so a user who performs 10 actions on a day generates 10 rows — summing rows instead of distinct user_id values inflates the count by orders of magnitude.
DataMimi Datamimi counts distinct user_id values per event_date rather than row counts, ensuring each user is counted once per day regardless of event volume.
Qualifying action definition not consistent
If any event_name counts as active, users who trigger background or automated events appear active even on days they never opened the app — defining activity on a specific event type is critical to accuracy.
DataMimi It filters to qualifying event_name values only so background and automated events don't inflate the active user count.
Bot and test accounts inflate daily counts
Internal test accounts and automated integrations generate events daily without representing real user engagement — their user_ids appear in every day's count unless explicitly excluded.
DataMimi It applies an exclusion list of test account user_ids before calculating so internal users are removed from the daily count.
DAU/MAU ratio requires matching time windows
Calculating the stickiness ratio requires DAU averaged over the month and MAU for the same month — mismatching the windows by using a single day's DAU against monthly MAU produces a misleading ratio.
DataMimi It calculates the DAU/MAU ratio using the monthly average of daily DAU divided by monthly unique user count so both measures use consistent time windows.
Common questions
What is daily active users?
Daily active users (DAU) is the count of unique users who performed at least one qualifying action in the product on a specific calendar day, used to measure day-to-day product engagement.
What is a good DAU/MAU ratio?
A DAU/MAU ratio above 20% is generally considered good; consumer apps like social networks and messaging tools target 50%+ stickiness; B2B tools used for specific workflows may see 30–50%.
How do I calculate DAU from a product analytics export?
Group the event export by event_date; count distinct user_id values per day; the count per day is your DAU; average across the month for a monthly DAU figure to use in the stickiness ratio.
How is DAU different from sessions?
DAU counts unique users per day regardless of how many sessions they start; sessions counts each separate browsing or app session, so one user can contribute multiple sessions to the session count in one day.
How much does Datamimi cost?
Datamimi offers a Free plan at $0/month (40 credits, no credit card required), Lite at $9/month (400 credits), Starter at $24/month (1,500 credits, up to 3 simultaneous files), Pro at $59/month (5,000 credits with rollover), and Team at $199/month (20,000 credits, 5 users).
Try it with your own file
DataMimi reads the file you actually have — merged cells, headers below row one, totals pasted at the bottom — and shows which rows and columns every number came from.
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