Mar 14, 2026 · 13 min read
DAU, WAU, MAU Explained: What They Mean, How to Calculate Them, and What Good Looks Like
DAU, WAU, and MAU — daily, weekly, and monthly active users — are the core metrics for understanding whether people are actually using your product, and how often. They're simple in concept but surprisingly easy to measure incorrectly, and a bad definition can make a struggling product look healthy.
This guide covers what each metric means, how to calculate them, what the ratios tell you, and the definition decisions that determine whether your numbers are actually useful.
What Are DAU, WAU, and MAU?
All three metrics count unique users who were "active" in your product within a specific time window:
- DAU (Daily Active Users) — unique users active on a given calendar day
- WAU (Weekly Active Users) — unique users active at least once in the past 7 days
- MAU (Monthly Active Users) — unique users active at least once in the past 30 days
The word active is doing a lot of work in those definitions, and it's where most measurement problems begin. We'll get to that shortly.
Together, DAU, WAU, and MAU give you a layered view of engagement — not just how many users you have, but how frequently they're showing up. A product with 100,000 MAU and 5,000 DAU is telling a very different story than one with 100,000 MAU and 60,000 DAU.
The Formulas
DAU = Count of unique users who performed a qualifying action on a specific day
WAU = Count of unique users who performed a qualifying action in the last 7 days
MAU = Count of unique users who performed a qualifying action in the last 30 days
The formula is straightforward. The complexity is in "qualifying action" — which is a decision you have to make deliberately, not inherit from a default analytics setting.
How to Calculate DAU, WAU, and MAU
Step 1: Define what "active" means for your product
This is the most important decision you'll make, and it's not a technical one — it's a product one.
"Active" should mean a user did something that demonstrates real engagement with your product's core value. That's different for every product:
- For a project management tool, active might mean creating or updating a task, commenting on a project, or completing a workflow — not just logging in to check a notification.
- For a data analytics platform, active might mean running a query, viewing a dashboard, or creating a report.
- For a messaging app, active could reasonably be sending or receiving a message.
- For a billing or invoicing tool, active might be generating an invoice or reconciling a payment — something that only needs to happen once or twice a month.
A definition that's too loose (logging in, opening the app) inflates your numbers without telling you anything meaningful. A definition that's too strict (completing the entire core workflow) can make normal usage look like non-engagement. Aim for the action that most reliably signals "this person got value from the product today."
Step 2: Count unique users, not sessions or events
A user who opens your app five times in a day counts as 1 DAU, not 5. Deduplication by user ID within the time window is essential. If your analytics tool is counting sessions or events instead of unique users, your numbers will be inflated.
Step 3: Apply consistent time windows
DAU is typically a calendar day (midnight to midnight in a standardized timezone, usually UTC). WAU is a rolling 7-day window. MAU is a rolling 30-day window — not a calendar month, which would make February shorter than March and create artificial fluctuations.
A worked example
Say you have 6 users and the following activity log for the week of March 3–9:
| User | Mon | Tue | Wed | Thu | Fri | Sat | Sun |
|---|---|---|---|---|---|---|---|
| User A | ✓ | ✓ | — | ✓ | — | — | — |
| User B | — | — | ✓ | — | ✓ | — | — |
| User C | ✓ | — | — | — | — | — | — |
| User D | — | — | — | — | — | ✓ | ✓ |
| User E | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| User F | — | — | — | — | — | — | — |
DAU for Wednesday: User B + User E = 2 DAU
WAU for this week: Users A, B, C, D, E = 5 WAU (User F was inactive all week)
If this week were your MAU window: Same 5 users = 5 MAU (assuming no additional activity outside this week)
User E is a power user — active every day. User C barely qualifies — active once. Both count equally in MAU, which is why MAU alone doesn't tell you much about the quality of your user base.
DAU vs WAU vs MAU: When to Use Each
The right metric depends on how often your product is designed to be used.
Use DAU when your product is a daily habit
Social apps, messaging tools, news products, and mobile games are built for daily use. For these products, daily active users is the primary engagement signal. If people aren't coming back every day, the product isn't working as intended.
Instagram, Snapchat, and WhatsApp all live and die by DAU. Even a small daily decline in an absolute DAU number can signal an engagement problem worth investigating immediately.
Use WAU when your product has a weekly rhythm
Many productivity and collaboration tools fit a weekly cadence — people use them Monday through Friday but not on weekends. Measuring these products by DAU will show drops every Saturday and Sunday that aren't real engagement problems, they're just the natural usage pattern.
For a project management tool used during the workweek, WAU is often a cleaner signal than DAU. WAU smooths over the day-to-day noise while still giving you a more granular view than MAU.
WAU is also useful for products with irregular but frequent usage — a design tool someone uses several times a week but not necessarily every day.
Use MAU when your product is used periodically
Billing software, tax tools, HR platforms, and many B2B analytics products aren't meant to be used every day. Measuring them by DAU would make perfectly healthy usage look like abandonment.
If your product's core workflow naturally happens once or twice a month, MAU is your primary engagement metric. The question isn't "did they use it today?" — it's "did they come back this month?"
The DAU/MAU Ratio: What Is It and Why Does It Matter?
The DAU/MAU ratio — often called the stickiness ratio — tells you what fraction of your monthly users are active on any given day. It's calculated as:
DAU/MAU Ratio = DAU / MAU × 100
If your MAU is 50,000 and your average DAU is 10,000, your DAU/MAU ratio is 20%.
This ratio is one of the most useful single numbers for understanding engagement quality. A high MAU with a low DAU/MAU ratio means you have a lot of users who signed up or visited once this month but aren't coming back regularly. A high DAU/MAU ratio means your daily users represent a large share of your monthly base — strong habitual engagement.
What is a good DAU/MAU ratio?
There's no universal answer, but these are the ranges typically used as reference points:
| DAU/MAU Ratio | What it generally signals |
|---|---|
| 50%+ | Exceptional. Common in top social and messaging apps. |
| 20–50% | Strong. Most successful daily-use products land here. |
| 10–20% | Moderate. Common in B2B tools and weekly-use products. |
| Below 10% | Low for a daily-use product; could be fine for periodic tools. |
Facebook has historically reported a DAU/MAU ratio above 60%. Slack has reported ratios in the 40–50% range for active workspaces. Most B2B SaaS products are somewhere between 10–25%, and that's often entirely appropriate given how they're used.
The mistake is comparing your ratio to a benchmark from a different product category. A tax software company hitting 8% DAU/MAU isn't failing — people just don't file taxes every day.
WAU/MAU ratio
The WAU/MAU ratio works the same way but measures weekly engagement:
WAU/MAU Ratio = WAU / MAU × 100
A WAU/MAU ratio above 50% is generally considered healthy for most products. It means more than half of your monthly users were active at least once in any given week. For products with a clear weekly cadence, this is often more useful than the DAU/MAU ratio.
DAU/WAU ratio
Less commonly tracked, but useful for products where daily vs. weekly engagement is a meaningful distinction. A high DAU/WAU ratio (close to 100%) means most of your weekly users come back every day — very strong daily habit formation.
How to Define "Active" — Getting This Right
Since everything downstream depends on your active user definition, it's worth being deliberate about it. Here are the practical guidelines.
Don't use login as your active signal. Login tells you someone opened your product, not that they used it. A user who logs in and immediately closes the tab counts the same as one who spent two hours doing meaningful work. That's not a useful signal.
Do use a core action that reflects product value. Ask: "What would I expect an engaged user to do?" For most products, there's a small set of actions — 2 to 4 — that signal real usage. If a user did any of those, count them as active.
Keep the definition stable. Changing what counts as "active" mid-stream makes trend data meaningless. If you need to update the definition (which sometimes happens as a product evolves), document it and keep the old series intact so you can compare.
Exclude internal users and test accounts. Employees, QA accounts, and bot traffic shouldn't count toward active users. This is surprisingly common to miss, especially in early-stage products where the team uses the product heavily themselves.
Consider segment-specific definitions. For a product with both admin users and end users, you may want separate DAU/MAU tracking for each. An admin who logs in weekly to manage settings has different engagement patterns than an end user who should be using the product daily.
DAU/MAU in Different Product Contexts
Consumer apps
For consumer social, gaming, and entertainment products, DAU is the primary metric and 20–30% DAU/MAU is the baseline for "this product has achieved meaningful habit formation." The best consumer apps (messaging, social feeds) push well past 50%.
B2B SaaS
Enterprise and mid-market tools typically see lower DAU/MAU ratios (10–20%) that are entirely healthy given usage patterns. The more relevant signal is often which users are active and whether the product is being used in the core workflow it was designed for. A CRM where sales reps update deals daily is healthy at 20% DAU/MAU; the same number might be concerning for a team collaboration tool that's supposed to be the center of daily work.
Marketplaces and transactional products
For products where transactions happen infrequently by nature (real estate, B2B procurement, tax software), MAU is the right primary metric and DAU/MAU ratios will naturally be low. The useful question shifts from "how often are users coming back?" to "are they coming back when they need to?"
Common Mistakes When Tracking DAU, WAU, and MAU
1. Defining "active" as a login or page view This is the most widespread mistake. If your analytics platform's default is "session started," you may be counting every accidental tap or stale tab reload as an active user. Define active around a meaningful action.
2. Not deduplicating across the time window A user active on Monday, Wednesday, and Friday of the same week counts as 1 WAU, not 3. If your data pipeline is summing daily actives instead of taking a distinct count of user IDs across the window, your WAU and MAU will be inflated.
3. Comparing DAU/MAU across different product types Benchmarking your B2B analytics tool's DAU/MAU against a consumer social app is meaningless. The metric is only meaningful relative to your own product's intended usage cadence and your own historical trend.
4. Including bots, employees, and test accounts In early-stage products, internal usage can represent a surprisingly high share of total activity. Filter it out. Your active user metrics should reflect real customers getting value, not internal team members testing features.
5. Using calendar months for MAU February has 28 or 29 days; March has 31. If you're measuring MAU as "active users this calendar month," February will always look worse than March even if nothing changed. Use a rolling 30-day window instead.
6. Treating flat MAU as a neutral signal Flat MAU can mean stable retention — or it can mean new user acquisition is exactly offsetting churn, with your actual engaged user base quietly eroding. Break MAU down into new users, returning users, and resurrected users (churned users who came back) to understand what's actually happening.
Frequently Asked Questions (FAQs)
What does DAU mean?
DAU stands for Daily Active Users — the count of unique users who performed a meaningful action in your product on a given day. The exact definition of 'meaningful action' varies by product and should be deliberately chosen to reflect genuine engagement, not just presence.
What does WAU mean?
WAU stands for Weekly Active Users — unique users active at least once in the past 7 days. WAU is particularly useful for products with a natural weekly cadence, such as work tools primarily used on weekdays.
What does MAU mean?
MAU stands for Monthly Active Users — unique users active at least once in the past 30 days. It's the most commonly cited active user metric for consumer products and the baseline engagement figure most investors ask about.
What is a good DAU/MAU ratio?
For most products, 20–30% is a reasonable benchmark for 'this product has meaningful daily engagement.' Consumer social and messaging apps often achieve 50%+. B2B and enterprise tools typically land between 10–20%, which is often appropriate given their usage patterns. The most important comparison is against your own historical trend, not an external benchmark.
What is a good WAU/MAU ratio?
A WAU/MAU ratio above 50% is generally considered healthy — it means more than half your monthly users were active at some point in any given week. Products with a clear weekly usage rhythm should aim higher, toward 70–80%.
How is DAU/MAU different from stickiness?
They're the same thing — DAU/MAU ratio is what most people mean when they say 'stickiness' or the 'stickiness ratio.' Some products track a dedicated stickiness metric that looks at this ratio over time, but the underlying calculation is DAU ÷ MAU × 100.
Should I track DAU or MAU for a B2B SaaS product?
It depends on your product's intended usage frequency. If it's a daily workflow tool (project management, communication), track both and watch the DAU/MAU ratio. If it's a periodic tool (billing, reporting, compliance), MAU is the more meaningful primary metric. Start with MAU and add DAU tracking once you understand your product's natural usage cadence.
What's the difference between DAU and active users?
These terms are often used interchangeably. 'Active users' without a time qualifier typically means MAU in most product and growth contexts, but the term is ambiguous. DAU is specific — it always refers to the daily window. When in doubt, always specify the time window.
Summary
DAU, WAU, and MAU are only as useful as the definition of "active" you apply to them. Get that definition right — grounded in a meaningful product action, not just a login or page view — and these metrics become reliable signals of engagement health.
Once your definition is stable, the ratios matter as much as the absolute numbers. A growing MAU paired with a falling DAU/MAU ratio often means you're acquiring users who aren't sticking. A flat MAU with a rising DAU/MAU ratio means your existing users are becoming more engaged — often a better sign than raw growth.
Track all three in tandem. Compare them against your own history first, benchmarks second. And never change the definition mid-stream without acknowledging the break in your data.