Daily Active Users (DAU) vs. Monthly Active Users (MAU): What Engagement Really Looks Like

Your product has 10,000 monthly active users (MAU).

That sounds great. But here’s a question: How many use it daily?

1,000? 500? 100?

If it’s 1,000, your product is healthy. That’s a 10% DAU/MAU ratio.

If it’s 100, your product is sick. That’s a 1% DAU/MAU ratio.

Same MAU number. Completely different product health.

This is why DAU (Daily Active Users) matters more than MAU (Monthly Active Users).

Defining DAU and MAU

DAU: How many unique users logged in or took an action today?

MAU: How many unique users logged in or took an action this month?

Example:

Monday: 500 users active
Tuesday: 450 users active
Wednesday: 400 users active
Thursday: 350 users active
Friday: 300 users active
Saturday: 200 users active
Sunday: 150 users active

Daily average: 336 DAU

Over the month, maybe 5,000 unique users took at least one action.

MAU: 5,000

DAU: 336

The DAU/MAU ratio: 336 / 5,000 = 6.7%

Why DAU is More Predictive

DAU tells you about habit formation. Is your product something people use every day? Or once a month?

If your product is email, DAU/MAU should be high (50%+). People check email multiple times a day.

If your product is tax software, DAU/MAU should be low (2-5%). People only use it around tax season.

But within your category, higher DAU/MAU is better.

Email app:

DAU/MAU ratio of 60% = users check email almost daily (healthy)
DAU/MAU ratio of 30% = users check email a few times per week (declining habit)

Project management tool:

DAU/MAU ratio of 40% = daily active work happening (healthy)
DAU/MAU ratio of 15% = sporadic usage (declining engagement)

Analytics platform:

DAU/MAU ratio of 20% = checking dashboards a few times per week (healthy)
DAU/MAU ratio of 5% = checking dashboards occasionally (declining engagement)

Lower DAU/MAU doesn’t always mean unhealthy (depends on product), but declining DAU/MAU is always a warning sign.

Why MAU Hides Problems

MAU counts anyone who used your product at least once this month.

So if someone logged in on day 1 of the month and never again, they count toward MAU.

This creates a false sense of health.

Example:

Month 1: 10,000 MAU (all active throughout the month)
Month 2: 9,500 MAU (people churning slowly)

Looks like you’re retaining 95% of users.

But what if:

Month 1 MAU: 10,000, DAU average: 5,000 (users actively engaged)
Month 2 MAU: 9,500, DAU average: 2,000 (users logged in once, haven’t been back)

You lost 60% of daily active users while only “losing” 5% of MAU.

MAU hides the problem because it includes dormant users (logged in once, not coming back).

Calculating DAU/MAU Ratio

Healthy ratio by product type:

Social apps (Twitter, Instagram, TikTok): 60%+ DAU/MAU

People use these multiple times per day
Anything below 50% suggests declining engagement

Productivity tools (email, Slack, project management): 30-50% DAU/MAU

Used daily or several times per week
Anything below 20% suggests declining usage

Utility tools (banking, calendar, notes): 20-40% DAU/MAU

Used frequently but not necessarily daily
Anything below 10% suggests declining usage

Occasional-use tools (tax software, vacation booking): 2-10% DAU/MAU

Used infrequently but intensively during relevant periods
This is normal and expected

B2B SaaS: 20-40% DAU/MAU

Teams using tools daily but not all team members every day
Anything below 15% suggests declining adoption

Tracking DAU Over Time

DAU is more volatile than MAU (it changes daily), so track it as a rolling 7-day average:

Week	Mon	Tue	Wed	Thu	Fri	Sat	Sun	7-Day Avg
Week 1	500	450	400	350	300	200	150	336
Week 2	510	460	410	360	310	210	160	344
Week 3	520	470	420	370	320	220	170	355

7-day rolling average shows the trend more clearly than daily DAU (which bounces around).

The Stickiness Factor

DAU/MAU is sometimes called the Stickiness Index.

It measures how sticky (habit-forming) your product is.

High stickiness (60%+ DAU/MAU):

Users come back nearly every day
Product is essential or highly engaging
Strong network effects (FOMO if you don’t check)

Medium stickiness (30-50% DAU/MAU):

Users come back several times per week
Product is useful but not essential
Habit-forming but optional

Low stickiness (10-30% DAU/MAU):

Users come back once or twice per week
Product is helpful but not top-of-mind
Easy to forget about

Very low stickiness (<10% DAU/MAU):

Users barely come back
Product is solving a problem but not building a habit
High risk of churn

Why DAU Can Decline While MAU Stays Flat

This is the silent killer.

New users come in, bump up MAU. But existing users are using the product less frequently.

Example:

Month A:

New users: 500 (first month using product)
Existing users: 9,500 (been customers for months)
Total MAU: 10,000
DAU average: 5,000 (because existing users are active daily)
DAU/MAU: 50%

Month B:

New users: 500 (fresh cohort, driving up MAU)
Existing users: 9,000 (some churned, remaining ones using it less frequently)
Total MAU: 9,500
DAU average: 2,500 (because existing users are now using it weekly, not daily)
DAU/MAU: 26%

MAU went down 5%, but DAU went down 50%.

This signals a serious engagement problem.

But if you only track MAU, you think you’re fine (just lost a few users).

Diagnosing Declining DAU

If DAU is declining, investigate:

1. Did something change in the product?

New feature that broke something?
UI change that’s confusing?
Performance degradation (slow)?
Check error rates, load times, recent deployments.

2. Did something change in your user base?

Did you onboard a bunch of low-quality users (they came, didn’t stick)?
Did your acquisition strategy change to cheaper channels (lower-quality)?
Check DAU by cohort (when they signed up). Are new cohorts stickier or less sticky than old ones?

3. Did engagement naturally decline?

Are seasonal factors at play? (January might be different than December)
Did a major competitor launch? (users split attention)
Did a major news event distract users?
Check if decline is cohort-specific or universal.

4. Is this normal for your product type?

If you’re a tax software, DAU might be 0 in June-December (no activity until January)
If you’re a retail app, DAU might spike in November-December (holiday shopping)
Compare DAU today to same period last year, not last month.

Taking Action on DAU Insights

If DAU is high and stable: You’re doing great. Keep doing what you’re doing. Focus on retention and expansion.

If DAU is high but declining: You’re losing engagement. Investigate quickly before it compounds into churn.

If DAU is low but stable: You’re not a daily-use product. This might be normal. But consider: Can you increase frequency? (Notifications, new features, habit loops)

If DAU is low and declining: Red alert. Something is broken or users are leaving.

The DAU Lie: Inflated Active Users

Some products count “active” loosely:

“User opened an email” (even though they didn’t read anything)
“User viewed a push notification” (even though they swiped it away)
“User visited a page” (even though they bounced in 2 seconds)

This inflates DAU numbers but doesn’t reflect real engagement.

When reporting DAU, define it clearly:

“Active user = spent at least 2 minutes in the app” (intentional use)
“Active user = performed a core action (sent a message, created a task, etc.)” (meaningful use)

Don’t count passive metrics (viewed, clicked, saw notification). Count intentional actions.

The Takeaway

MAU tells you how many people could use your product.

DAU tells you how many people actually do.

DAU/MAU ratio (stickiness) predicts retention. High stickiness = sustainable. Low stickiness = at-risk.

If DAU is declining while MAU stays flat, you have an engagement problem brewing.

Track both, but focus more on DAU and DAU/MAU ratio.

We help you calculate DAU correctly, track it by cohort, understand your stickiness ratio, and diagnose engagement problems when DAU declines.