# DAU/MAU ratio

The DAU/MAU ratio is a product's average daily active users divided by its monthly active users. It shows what share of the people who use a product in a month come back on a typical day, which makes it a common measure of habit and stickiness.

## What are DAU and MAU?

DAU (daily active users) is the number of unique users who were active on a given day. MAU (monthly active users) is the number of unique users who were active at least once in a month, usually a rolling 30 days.

Both depend entirely on what "active" means. A login or a page view inflates them. A key action that delivers value (sent an invoice, edited a document, approved a request) makes them worth tracking. Use the same definition for both, or the ratio means nothing.

## How do you calculate the DAU/MAU ratio?

Average your DAU over the same 30 days your MAU covers, then divide.

`DAU/MAU ratio = average daily active users ÷ monthly active users`

Worked example: over 30 days, an average of 2,000 people are active each day, and 10,000 different people are active at least once. The ratio is 2,000 ÷ 10,000 = 0.2, or 20%. Multiply by the days in the window to read it another way: 0.2 × 30 means the typical monthly user is active about six days a month.

Three rules keep it honest:

- **Average DAU across the window.** A single day's DAU swings with weekdays, holidays and launches.
- **Count unique users.** Someone active ten times in a day is one daily active user.
- **Match cadence.** If the product is meant for weekly use, use WAU/MAU instead. A weekly planning tool will always show a low DAU/MAU ratio, and that is fine.

What counts as a good DAU/MAU ratio depends on how often the job comes up. Messaging and collaboration products used all day sit high. Reporting, payroll or procurement tools used weekly or monthly sit low and can still be healthy. Rather than chasing an outside number, compare the ratio by cohort, plan and role against your own history.

## What does the DAU/MAU ratio hide?

It's a ratio, so the denominator moves it as much as the numerator does:

- **Acquisition pushes it down.** A big sign-up month adds new monthly users who aren't daily yet. The ratio falls even if nothing got worse.
- **Churn can push it up.** When light users leave, the remaining base is more active, and the ratio rises while the business shrinks.
- **Averages hide the shape.** Five thousand users active every day and five thousand active once a month look almost the same as ten thousand users active half the time. Plot how many days each user was active in the month to see which you have.
- **It says nothing about outcomes.** A user who came back daily because they couldn't finish a task counts the same as one who got their work done.

That last gap is about intent: what users came to do, and whether they did it. When users can ask an in-product agent for what they want, the request and its outcome are both recorded. Foldspace pairs product analytics (retention and funnels) with Conversational Analytics, which [shows the intent behind each request](https://docs.foldspace.ai/whats-new/conversational-analytics/) to the Product Agent, in the user's words, and whether the conversation was resolved, unresolved or escalated. For the users who asked the agent, a daily return then reads as work getting done or work getting stuck.

## Learn more

- [Product Analytics](/platform/product-analytics)