Analyze Daily Active Users Data from Product Analytics

When you analyze daily active users data from Amplitude, Mixpanel, Google Analytics 4, or your own event tracking, the exports arrive as one row per day with user counts, sometimes split by platform or feature, and you need to calculate rolling averages, stickiness ratios, and week-over-week changes that a basic spreadsheet makes tedious.

You can upload a DAU export and get rolling averages, platform breakdowns, and stickiness ratios in a clean table in under a minute, then download it or send it to your BI tool.

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Or start with

How do I calculate monthly active users from daily active users?What is a good DAU/MAU ratio?How do I compare daily active users week over week?How do I calculate stickiness from DAU data?How do I find which day of the week has the highest DAU?

What this export contains

date

daily_active_users

new_users

returning_users

platform

feature_name

dau_ios

dau_android

dau_web

churned_users

session_count

country

Handling platform or feature splits in DAU exports

Exports from Amplitude or Mixpanel often break DAU into separate columns per platform, feature, or user segment. You want total DAU and each slice as a percentage of that total. The tool sums the split columns into a total, calculates each as a percentage, and lets you filter to one platform or compare their trends without writing array formulas or making pivot tables that flatten the time series.

Filling gaps in daily data

If your export skips weekends or has missing days, rolling averages and week-over-week calculations break. The tool detects gaps in the date column and either fills them with zero, carries forward the last value, or interpolates, depending on what the metric means. Session-based DAU usually gets zero for missing days; user-state metrics like MAU carry forward.

What it costs

DataMimi is free to try without an account, and the free plan includes credits every month. Paid plans add more credits, more files per analysis and more seats; every feature, from dashboards to slide decks, is on every plan. See the pricing page for current prices.

Common questions

How do I calculate monthly active users from daily active users?

MAU is the count of unique users active in the last 28 or 30 days. If your export has one row per day with a daily_active_users column, you sum the most recent 28 or 30 rows, but only if each day lists unique users and your tool deduplicates across the window. Most exports do not, so MAU must come from the same analytics platform as a separate metric.

What is a good DAU/MAU ratio?

A DAU/MAU ratio above 0.2 or 20% means users return at least once a week on average. Social apps and daily tools often see 0.4 to 0.6. B2B products used weekly may sit at 0.15 to 0.25. The ratio matters less than whether it is stable or declining.

How do I compare daily active users week over week?

Subtract the DAU value from seven days ago and divide by that prior value to get a percentage change. If your export has gaps from weekends or missing data, the lookup fails unless you fill missing dates with zero or the last known value.

How do I calculate stickiness from DAU data?

Stickiness is DAU divided by MAU. It shows what fraction of your monthly users come back each day. You need both metrics in the same row, which means either your export includes a rolling MAU column or you calculate it as a 28-day or 30-day rolling sum of unique users.

How do I find which day of the week has the highest DAU?

Extract the day name from the date column using a formula like TEXT(date, "dddd"), then group by that day name and average the daily_active_users values. Weekdays usually beat weekends for work tools; weekends often win for consumer apps.

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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What DataMimi costs

Every plan does everything — slides, written reports, cleaned exports, dashboards. They differ in how much work they cover.

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40 credits a month

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$24 /month

1,500 credits a month

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$59 /month

5,000 credits a month

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