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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteDAU tells you how many unique users performed a defined action in a day; cohort retention shows what share of a starting group returns later; wallet activity describes either what people do inside an app or what addresses do on a blockchain. These measures are related, but they are not interchangeable. A crypto app should report them separately, define each event and identity rule, and avoid treating on-chain transactions as proof that someone returned to its app.
How the three metrics differ
| Measure | What it counts | Question it answers | Main limitation |
|---|---|---|---|
| DAU | Unique users who perform a specified action during one daily interval. | How many users were active today under this definition? | A daily count does not show whether users return over time. Results depend on the event and identity rules. |
| Cohort retention | Members of a defined starting group who meet a return-event condition, measured against the eligible cohort. | Which users return, when, and after which starting behavior? | The cohort start, return event, interval, and calculation method all affect the result. |
| Wallet activity | In-app events or blockchain activity, which may be counted as users, addresses, sessions, or transactions. | Are people using wallet features, or are blockchain addresses transacting? | An address is not necessarily a person or a user of a particular app. |
Amplitude defines active users by logged events in a selected interval, while Mixpanel notes that teams must decide what “user” and “action” mean for their product. Amplitude’s definitions and Mixpanel’s DAU explainer both point to the need for an explicit definition.
What DAU can—and cannot—tell you
DAU is an interval count, not a loyalty measure. It can rise while retention stays weak if new users keep arriving but relatively few existing users come back. Conversely, a smaller app can have strong retention even if its DAU is modest. Read DAU alongside acquisition and retention rather than as a standalone verdict on product health.
Define the active event
Separate deliberate, user-visible actions from automatic events that may fire without meaningful engagement. For example, an app could report a broad activity measure based on opening the app and a narrower measure based on a core wallet action. These are proposed event choices, not a universal standard. Name the event behind every DAU figure; “active” by itself is too vague for comparison.
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Define the identity rule
Specify how unique users are deduplicated across devices, accounts, and wallets. A person with multiple devices or wallet addresses may otherwise be counted more than once, while an address count may not correspond to a count of people. Disclose any identity resolution used so readers can understand what the number represents.
How to set up a meaningful retention comparison
Retention needs both a start condition and a return condition. Amplitude describes retention as how often users return over a time frame, but the result depends on which users qualify at the start and which later behavior counts as a return.
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Choose the cohort start event
Possible starts include first app use, account creation, wallet setup, or a first successful transaction. These answer different questions: a first-use cohort measures return after initial exposure, while a first-transaction cohort measures return after a deeper activation milestone. Label the start event, and do not compare cohorts with different starts as if they were equivalent.
Choose the return event
A return might mean opening the app, viewing a balance, initiating a send, or completing a transaction. A balance view is not the same level of engagement as a completed transaction, so choose the action that matches the question being asked and state it clearly. Amplitude’s retention FAQ explains retention calculations and the distinction between return methods.
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Choose the retention method and time basis
“Return On” counts users who return in a particular interval. “Return On or After” counts users who return in that interval or any later one. A user who misses an early interval but returns later can therefore appear differently under the two methods. Calendar-day windows and rolling 24-hour windows also produce different results; timezone choices matter when assigning events to calendar dates. Amplitude documents these options in its guides to interpreting retention analysis and time in retention analysis.
Keep app wallet events separate from on-chain activity
In-app wallet analytics can track product events such as wallet creation or import, viewing an asset, starting a receive or send flow, completing a transaction, or returning to the app. The exact event set should reflect the product and distinguish an attempted action from a completed one.
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On-chain analytics instead observes blockchain-level activity, such as transactions associated with addresses. Cohort analysis can be applied to blockchain data, as shown in the study “Deciphering Bitcoin Blockchain Data by Cohort Analysis”. But a chain event alone does not establish that an identifiable person reopened a particular app: the measurement unit is an address or transaction, not necessarily an app user. Keep app and chain metrics in distinct series unless there is a defensible, privacy-conscious identity link. Amplitude describes its product analytics as event-based in its overview of the platform.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical measurement plan for a crypto app
- Write down the events. Separate user-visible actions from automatic events; distinguish attempts from successful completions where that matters.
- Publish the active-user definition. State the event, daily interval, timezone, and rule for deduplicating people across devices, accounts, and wallets.
- Choose the cohort start deliberately. Use a stated milestone such as first app use, wallet setup, or first successful transaction, depending on the question.
- Name the return event and method. Say whether return means an app open, a wallet action, or another event, and whether the chart uses “Return On” or “Return On or After.”
- Keep measurement layers distinct. Report in-app events and on-chain activity separately unless identity can be linked reliably and appropriately.
- Segment only comparable groups. Acquisition channel, onboarding path, geography, and wallet setup can be useful cuts, but instrumentation and cohort definitions must be consistent enough for the comparison to mean something.
How to interpret a change without overclaiming
If DAU rises while retention falls, check whether acquisition increased, whether the daily activity event is broad, and whether return behavior weakened. If retention changes after an instrumentation update, first check whether the start event, return event, timezone, or calculation method changed. When comparing wallet activity with retention, verify whether the series counts app users, addresses, transactions, or sessions; matching trends do not by themselves prove that the same people generated both.
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The sources cited here explain measurement methods, not a representative current benchmark for crypto-app retention. There is no supported universal “good” retention rate to apply across crypto apps from these sources. Compare like-for-like cohorts within the product and state the event, interval, and identity definitions beside the figures.
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