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ECECH AppPrecision calculator

Measure DAU/MAU App Stickiness

Compare average daily active users with the monthly active audience using the same activity definition.
average DAU
unique MAU

Average daily activity / monthly audience

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Inputs modeled

2 user counts

10% more average DAU

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Comparison basis

Same period

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How the calculation works

Average daily users12,000 DAUMonthly audience50,000 unique MAUDaily stickiness24%Keep the app, identity definition and calendar window consistent.

How to Use This Tool

Average DAU divided by monthly active users gives a simple stickiness ratio. Keep the app, identity definition and calendar window consistent.

Why App DAU/MAU needs more than a raw total

DAU and MAU must use the same identity and activity definition; mixing devices with accounts invalidates the ratio. Use the ratio to compare recurring daily activity against monthly reach. It is an engagement metric, not a retention rate or a stand-alone product quality score.

Entered Average daily active usersSame input plus 10%compare
App DAU/MAU changes average daily active users alone for the secondary result, leaving every other entered value fixed.

The exact App DAU/MAU formula

DAU/MAU stickiness equals average daily active users divided by monthly unique active users × 100. The visible fields are Average daily active users and Monthly active users. Match the app, identity definition and calendar window. Average DAU should not exceed monthly unique users when both measures use a consistent definition.

Interpreting dau/mau stickiness

Compare the same app, identity definition and calendar window; do not treat this ratio as retention. The ten-percent comparison is deliberately narrow: it tests the influence of daily active users and is neither a forecast nor a confidence interval. Preserve the values used, their dates and the resulting decision so a later reviewer can reproduce why App DAU/MAU supported the choice.

What this App DAU/MAU model leaves out

The ratio is not retention, does not reveal visit frequency distribution and can be distorted by seasonality. DAU must remain less than or equal to MAU under the same definition. That is where App DAU/MAU stops being trustworthy. If an excluded factor could reverse dau/mau stickiness, extend the model explicitly or use the authoritative account system instead of hiding the factor inside an unexplained adjustment.

Evidence and independent verification

The reference reviewed for App DAU/MAU is Apple Developer — App Store Connect Analytics. Apple Developer — App Store Connect Analytics supports the named definition or rule but does not supply private values for dau/mau stickiness. Before acting on the result, reconcile the worked example with the relevant dashboard, invoice, export or measurement.

Private, reproducible calculation

App DAU/MAU runs its arithmetic in the current browser tab and requests no login or API key. That keeps the App DAU/MAU inputs away from the site's calculation server, while leaving the user responsible for detecting stale data or a changed platform rule. When an assumption changes, reopen Apple Developer — App Store Connect Analytics and rerun the saved App DAU/MAU scenario.

Sources & assumptions

Tool Spec v2 · verified 2026-08-22. Platform rules and fees can change; the editable inputs remain authoritative for your account.

Official references

Model assumptions

  • Every input covers the same reporting period or cohort.
  • The ratio is not retention, does not reveal visit frequency distribution and can be distorted by seasonality. DAU must remain less than or equal to MAU under the same definition.
  • The calculator uses only the visible fields and does not fetch account data.
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Frequently Asked Questions

What exactly does App DAU/MAU return?
App DAU/MAU returns dau/mau stickiness from the displayed formula: DAU/MAU stickiness equals average daily active users divided by monthly unique active users × 100. No hidden account field participates in this result.
Which input should I verify first for App DAU/MAU?
Start App DAU/MAU with Average daily active users. Growth in monthly users can hide weakening everyday utility when daily engagement is never normalized against the larger base. Confirm the remaining App DAU/MAU fields use the same scope and reporting window.
What does the Average daily active users sensitivity result mean?
It raises daily active users by ten percent while holding the other fields fixed. Compare the same app, identity definition and calendar window; do not treat this ratio as retention. It is not a probability or forecast.
When should I reject the App DAU/MAU result?
Reject or extend the model when this limitation matters: The ratio is not retention, does not reveal visit frequency distribution and can be distorted by seasonality. DAU must remain less than or equal to MAU under the same definition.
Which evidence was reviewed for App DAU/MAU?
App DAU/MAU cites Apple Developer — App Store Connect Analytics for the current definition; use your own source system for the account-specific values behind dau/mau stickiness.
Where does App DAU/MAU process my inputs?
The calculation for dau/mau stickiness runs in browser JavaScript and requests no account credential or calculation API.

What people usually need next

Picked by hand, not by algorithm.

💻App Retained UsersStickiness is broad engagement; inspect a fixed install cohort next.

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