What a Good DAU/MAU Ratio Is, and Who Actually Measured It

What is the DAU/MAU ratio?

Product teams calculate the DAU/MAU ratio by dividing average daily active users by monthly active users for the same period and multiplying by 100. The result is a stickiness figure: the share of your monthly user base that shows up on an average day. Mixpanel describes a 20% result as one in five monthly users being active on a given day.

DAU/MAU ratio = (average DAU / MAU) x 100

Both inputs need a definition first. MAU counts unique people who performed a value action in a 30-day window, not visits, so start by separating pageviews, sessions and users in your reporting. Average DAU is the mean of the daily unique-user counts across that same window, not the DAU on the last day of the month.

How do you calculate the ratio on real numbers?

Take a product with 50,000 monthly active users and an average of 10,000 daily active users across a 30-day month. Ten thousand divided by fifty thousand is 0.20, a 20% DAU/MAU ratio. That same product measured on one strong Tuesday could show 14,000 DAU and report 28%, so the average matters more than any single day.

That last row is where most teams stop reading, and it misleads them.

Does a 20% ratio really mean six days a month?

A 20% ratio means six days per month only if every monthly active user behaves identically, and no real user base does. The mean is genuine: 10,000 daily users across 30 days produces 300,000 user-days, and 300,000 spread across 50,000 people averages six days each. The distribution behind that mean is unconstrained, so two very different products report the same 20%.

Run the other extreme on the same 300,000 user-days. Every monthly active user appears at least once by definition, so put the maximum possible number of people on a daily habit and give everyone else exactly one visit. The arithmetic lands at roughly 8,600 people using the product all 30 days alongside roughly 41,400 who opened it once and never came back. That is a hard core of about 17% of the base plus a long tail of one-time visitors, reporting the identical 20%.

Plot days-active per user as a histogram instead of trusting the average, and segment the two populations with cohort analysis before deciding what to build. Karl Wirth raised this objection in the comments on Fred Wilson's 2011 post, laying out both extremes side by side.

Where did the 20% and 50% benchmarks come from?

The numbers repeated in pitch decks trace to three published sources, each narrower than the version that gets quoted.

Fred Wilson published 30/10/10 on AVC on July 30, 2011, drawing on confidential metrics from Union Square Ventures portfolio and prospect companies. His claim: 30% of registered users or downloads use a service each month and 10% use it each day. Both figures are shares of registered users, not of each other, so the implied DAU/MAU is 10 divided by 30, or about 33%. Wilson added in the comments that the ratios apply to services at scale, not to early products.

Gainsight's essential guide chapter, The DAU/MAU Ratio: Tutorial and Examples, is the origin of the 40% figure for B2B SaaS. Gainsight frames it as an acceptable benchmark when weekends and holidays are ignored, which works out to a user being active on eight of twenty workdays. The same page puts the SaaS average at 13%, ecommerce at 9.8% and finance at 10.5%, and states that Facebook has a DAU/MAU ratio over 50%. The page carries no publication year, so treat every figure on it as undated.

The 50% threshold that circulates as an excellence bar is that Facebook observation restated without its subject, and one company's number is not a benchmark. As for the claim that 20% is good, no primary source we could reach publishes it as a threshold, so this page does not repeat it.

What are the current DAU/MAU benchmarks by industry?

Mixpanel published the most recent measured set on June 9, 2026, in Monthly active users: definition, formula, and 2026 benchmarks, drawn from its 2026 State of Digital Analytics report covering 3.7 trillion events across more than 12,000 companies in eight industries. The figures below are the 2025 stickiness ratios from that report.

Mixpanel states that B2B SaaS at 31% is lower than the older 40% heuristic, and that teams measuring themselves against 40% have held an unrealistic standard. It also flags AI products in North America at 21% because mature users accomplish more per session and return less, a case where a falling ratio is not a falling product.

When is the DAU/MAU ratio the wrong metric?

Stop tracking DAU/MAU when your product has no daily use case, because a metric that cannot move teaches you nothing. Gainsight names invoicing tools, talent marketplaces and infrequent ecommerce as categories where sporadic use is correct, and suggests WAU/MAU or MAU/QAU instead. Mixpanel makes the same argument for asynchronous and agent-driven products, where work happens while nobody is logged in and the daily count reads zero on a day that delivered real value.

The metric is also slow. Because the denominator looks back thirty days, a change you ship today takes weeks to register. Judge a release on seven-day retention rate instead, and check the churn rate formula on the same cohort to confirm that rising stickiness is not just a shrinking base.

How do you raise the ratio without gaming it?

Raise DAU/MAU by removing the friction that stops committed users from returning, not by pulling casual users back for a single visit. Gainsight makes the mechanical point that a generic "we have not seen you in a while" email raises MAU more than DAU and pushes the ratio down. Broad re-engagement campaigns therefore work against the number they are meant to move.

The higher-leverage work is diagnosing why the daily cohort is small. Flowsery records every user session, detects rage clicks, dead clicks, JavaScript errors, drop-offs and broken flows, and groups matching sessions into one issue ranked by how many users hit it, so you can see the breakage standing between a weekly user and a daily one. Its built-in web analytics covers real-time traffic, funnels, goals and user journeys alongside the replays. Read the ratio next to engagement rate and your product analytics funnels, never on its own.

Frequently Asked Questions

Is DAU/MAU the same as product stickiness?

Stickiness is the concept and DAU/MAU is the most common way to measure it. Gainsight and Mixpanel both use the two terms interchangeably in their guides. Other ratios measure the same idea on different clocks, such as WAU/MAU for weekly products and MAU/QAU for quarterly ones.

Can the DAU/MAU ratio exceed 100%?

No. Every daily active user sits inside the monthly active user total for the same window, so the numerator cannot exceed the denominator. Fred Wilson confirmed this nesting in the comments on his 2011 post when a reader asked whether the daily and monthly groups were separate. A ratio above 100% means your two counts use different user definitions or date ranges.

What DAU/MAU ratio should a B2B SaaS product target?

Mixpanel's June 2026 data puts B2B SaaS at 31% in North America and EMEA, 33% in APAC and 25% in LATAM, and says products between 25% and 35% are in line with the market. The older 40% figure comes from Gainsight's undated guide and assumes weekends are excluded. Pick the benchmark whose measurement window matches your own.

Why did our ratio drop after a successful launch?

A launch adds new users to MAU immediately while those users take weeks to build a daily habit, so the denominator grows before the numerator does. Commenters raised this growth-rate distortion on Wilson's 2011 post. Exclude accounts created in the current month, or read the ratio per signup cohort.

Does a low DAU/MAU ratio mean the product is failing?

Not by itself. Mixpanel's 2026 data shows fintech insurance at 16% in EMEA and ecommerce at 20% in North America, which reflects how rarely people need those products. A low ratio is a problem only when your business model depends on daily use. Judge it against your own vertical, not a cross-industry average.

How long a window should the average DAU cover?

Use the same window for both numbers, and use the mean of the daily counts instead of a single day. A 30-day window matched to the MAU definition stops a strong Tuesday from inflating the result. If your product has a weekday pattern, report the weekday and calendar versions separately.

How large was the dataset behind Mixpanel's 2026 DAU/MAU benchmarks?

Mixpanel's June 9, 2026 report draws on 3.7 trillion events from more than 12,000 companies across eight industries. The published figures are 2025 stickiness ratios broken out by region within each vertical. That scale is why the report now serves as the reference point over the older Gainsight and Wilson figures.

What should I track if my product has no daily use case?

Gainsight recommends WAU/MAU or MAU/QAU for categories like invoicing tools, talent marketplaces and infrequent ecommerce, where sporadic use is normal rather than a warning sign. Mixpanel makes the same point for asynchronous and agent-driven products, where work happens while nobody is logged in. Match the metric's window to how often a healthy user is expected to return.

Why would DAU/MAU fall for an AI product that just got better?

Mixpanel flags AI products in North America, at 21%, as a case where a falling ratio does not mean a failing product. Mature users accomplish more in a single session and need to return less often, so fewer daily visits can reflect efficiency rather than disengagement. Reading the ratio alone would hide that improvement.

Do re-engagement emails raise the DAU/MAU ratio?

A generic "we have not seen you in a while" email typically raises MAU more than DAU, according to Gainsight, so it pushes the ratio down instead of up. Broad re-engagement campaigns pull back casual users for a single visit, which inflates the monthly count without building a daily habit. Removing the friction that stops committed users from returning works better than a blanket win-back email.