The percentage of your monthly active users who return on an average day, calculated as average DAU divided by MAU — a direct measure of how habitual your product has become.
Stickiness = (average daily active users ÷ monthly active users) × 100
In June your app had 1,800 unique monthly active users. Summing daily active users across all 30 days gives 13,500, so average DAU = 13,500 ÷ 30 = 450.
(450 ÷ 1,800) × 100 = 25% stickiness — the average user is active 1 day in 4, about 7–8 days per month
Stickiness answers a question raw user counts cannot: of everyone who used your product this month, how many make it part of their daily routine? A ratio of 20% means the average monthly active user shows up on roughly 6 days out of 30. It measures habit formation, not audience size — a product can grow MAU rapidly while stickiness quietly collapses, which is growth papering over an engagement problem.
The most common mistake is taking DAU from a single day, usually a strong one, instead of averaging daily active users across the full month. That flatters the ratio and hides weekday/weekend swings. The second is counting logins or app opens as "active". Define activity as a genuine value action (created an invoice, ran a report, sent a message) and use the same definition for both numbers, or the ratio is meaningless.
Every product has a natural ceiling set by its usage cadence. A B2B tool used only on working days tops out around 71% (22 working days ÷ 31) even with perfect attendance, so comparing yourself to WhatsApp is pointless. Low stickiness is not automatically bad either: an invoicing or tax product used once a month can be extremely healthy at 10%. If your intended cadence is weekly, measure WAU/MAU instead.
For a subscription business, stickiness is a leading indicator where billing metrics are lagging ones. Stripe tells you a customer churned after they cancelled; a cohort's declining stickiness warns you weeks or months earlier, while there is still time to intervene. Daily-habit users almost never cancel — disengagement always shows up in usage before it shows up in revenue.
Stickiness is the earliest reliable signal of retention. By the time a cancellation appears in Stripe, the decision was made long ago; a falling DAU/MAU ratio flags disengagement while the customer is still paying, giving you a window to act. It also tells you whether growth is real — rising MAU with flat or falling stickiness means you are filling a leaky bucket.
Mixpanel's State of Digital Analytics 2026, drawn from 3.7 trillion events across 12,000+ companies, puts B2B SaaS stickiness at roughly 31% (25–35% is broadly in line with the market) — well below the 50%+ typical of social and messaging apps.
Mixpanel's 2026 benchmarks put B2B SaaS at roughly 31%, with 25–35% broadly in line with the market. Consumer social and messaging apps run 50%+, but that comparison is misleading — judge stickiness against your product's natural usage cadence, not against the stickiest apps on earth.
Average your daily active users across the full month, divide by unique monthly active users, and multiply by 100. Use the same definition of "active" for both numbers — ideally a meaningful value action, not just a login — and never use a single day's DAU.
Whatever you define it to be, which is exactly the trap. Counting logins or app opens inflates the ratio without telling you anything about value. Pick a core action tied to the job your product does (sent an invoice, ran a report) and apply it consistently to both DAU and MAU.
No. A payroll, tax, or invoicing tool used once a month can be extremely healthy at 10% because that is its natural cadence; if your product is designed for weekly use, WAU/MAU is the more honest measure. What matters is a fall below your intended frequency — that usually precedes a rise in churn.
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