Unit economics
Grade product stickiness from your DAU-to-MAU ratio.
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- Claude, via MCP
How do you calculate DAU/MAU stickiness?
Stickiness = daily active users ÷ monthly active users. 1,800 daily users out of 6,000 monthly users is 30%, meaning the average monthly user is active about 9 days a month. This tool treats 50%+ as daily use, 20% to 49% as sticky, 10% to 19% as occasional and under 10% as rarely used.
A 30% DAU/MAU means users come back roughly 9 days a month, a genuine habit. Sticky products churn far less and expand more easily, because they’re embedded in the daily workflow.
DAU/MAU above ~20% signals a habitual product; 50%+ is elite (daily-use tools). Not every product should be daily-use, judge against your category’s natural frequency.
About this calculator
Retention starts leaking long before a customer cancels, it starts the moment they stop opening the product. The DAU/MAU ratio is the earliest read on that, and this grader turns your daily and monthly active user counts into a stickiness percentage, an implied "days used per month" figure, and a plain verdict on whether you've built a daily utility or an idle tab.
How to use it
- Enter daily active users (DAU), unique users active on a typical day.
- Enter monthly active users (MAU), unique users active at least once in the trailing month.
- Read the stickiness ratio (DAU/MAU), the implied average days used per month, and the verdict band.
Methodology
Stickiness is DAU divided by MAU, expressed as a percentage, the standard DAU/MAU engagement ratio used across consumer and B2B SaaS products alike. Implied days used per month is that ratio applied to a 30-day month, a rough translation of the percentage into a usage-frequency figure that's easier to reason about intuitively.
The tool bands stickiness into four tiers: 50%+ is graded "Daily utility" (elite, daily-use-tool territory), 20-49% is "Sticky" (a genuine habit), 10-19% is "Occasional" (a caution zone), and under 10% is "Idle tab" (users rarely return), reflecting commonly cited industry ranges where 20%+ signals habitual usage and 50%+ marks best-in-class daily tools.
This is a point-in-time snapshot based on whatever DAU and MAU figures you enter, it doesn't track the trend over time or segment by user cohort or account. A rising or falling stickiness trend, or a wide gap between power users and the long tail, matters as much as the single blended number.
DAU/MAU is a usage-frequency metric, not a retention or revenue metric on its own. A high ratio correlates with lower churn and easier expansion in most SaaS products, but it doesn't directly measure either, pair it with churn and expansion metrics for the full retention picture.
DAU/MAU and implied days of use
Stickiness = DAU ÷ MAU Implied days used per month = Stickiness × 30 Band: 50%+ daily utility, 20 to 49% sticky, 10 to 19% occasional, under 10% idle
- DAU
- Average daily active users over the month.
- MAU
- Unique users active at least once in the month.
- Active
- A meaningful action in the product, not just a login, defined the same way for both numbers.
Use average DAU across the month, not a single day. The right level depends on the product: a chat tool should be used daily, a monthly reporting tool should not. Compare your ratio with how often the job the product does actually happens, and track the trend rather than one month.
Worked example: 1,800 DAU and 6,000 MAU
A B2B workflow product has 6,000 users active in the month and an average of 1,800 active each day.
- Stickiness = 1,800 ÷ 6,000 = 30%.
- Implied days used per month = 30% × 30 = 9 days.
- Band: 30% is "sticky", a regular habit.
- If the product is meant for daily work, 9 days suggests many users touch it only two or three times a week.
For a daily workflow tool, look for the segment using it daily and what they do differently, then guide other users there. For accounts, low usage often comes before downgrades; see the seat utilisation risk assessor and the renewals pipeline health grader.
What is a good DAU/MAU ratio?
Good depends on how often the job happens:
- Daily jobs (messaging, sales calls, support): aim high; 50% or more means the product is part of the day.
- Weekly jobs (reporting, planning): 20% to 30% can be healthy.
- Monthly jobs (billing, payroll): low DAU/MAU is normal; use weekly or monthly active rates instead.
The tool's bands are working thresholds. The most useful comparison is your own trend and the gap between your best and average accounts.
Product engagement in India vs the US
Indian B2B users often work across WhatsApp, email and several tools, so a product that sends updates into WhatsApp can drive engagement without daily logins. Count actions taken from notifications as activity if they matter to the product's value.
US SaaS products often report DAU/MAU to investors as a sign of habit. Higher stickiness usually supports lower churn and easier expansion, but it is not a revenue metric on its own; pair it with the net revenue retention forecaster.
Common DAU/MAU mistakes
- Counting logins or background activity as active use.
- Using one day's DAU instead of a monthly average.
- Setting a daily-use target for a product meant for weekly or monthly jobs.
- Looking at the blended ratio without segmenting by account or role.
- Treating high engagement as proof of value without checking retention and revenue.
FAQ
This tool treats 20% and above as sticky (a genuine habit) and 50%+ as elite, daily-utility territory. Below 10% is flagged as an "idle tab" signal, most users only open the product rarely. The right target still depends heavily on your product category.
No. A payroll tool or an annual tax product has a naturally low, and perfectly healthy, usage frequency; nobody should be opening it daily. Judge your ratio against what's natural for your category's use case, not against a universal daily-use benchmark.
Usage frequency is one of the earliest predictive signals of churn, it typically declines well before a cancellation or non-renewal happens. Catching a stickiness drop early gives customer success time to intervene, whereas waiting for a churn or renewal signal is often too late.
It's the stickiness percentage applied to a standard 30-day month, so 25% stickiness implies roughly 7.5 days of use per month. It's a simplified translation for intuition, not a measured count of actual login days per individual user.
Weekly active users divided by monthly active users, or the share of accounts active each week.
Find the actions that bring users back, make them easier to reach, and use notifications that lead to a useful action rather than just a visit.
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