DAU/MAU Stickiness — how "sticky" your product really is

2026-05-22 · by Rodion Latipov

DAU/MAU Stickiness — how "sticky" your product really is

Stickiness shows what share of your monthly audience returns to the product every day. It's the most honest engagement indicator: you can buy MAU growth with ads, but you can't buy stickiness — it reflects the product's real value.

> Stickiness = DAU / MAU × 100%

DAU is the average number of unique daily users. MAU is uniques over a month. The result: what % of monthly users show up on a typical day.

How to read the number

A stickiness of 20% means the average user is active 6 days out of 30. A stickiness of 50% → 15 days out of 30 → the product has become part of the daily routine.

StickinessWhat it means
<10%Low engagement — the product is "remembered" rarely
10-20%Normal for most SaaS and content apps
20-50%High engagement — a habit is forming
>50%A daily-habit product (messengers, social)

Benchmarks by product type

Product typeTypical StickinessExamples
Messengers / social50-60%WhatsApp, Instagram
Daily utility30-50%Maps, weather, banking
Productivity / SaaS20-40%Slack, Notion (workdays!)
Content / media15-30%YouTube, news
B2B SaaS (niche)10-20%Analytics, CRM
Transactional<10%Marketplaces, delivery, travel
Important: low stickiness isn't always bad. A tax service or a flight-booking site doesn't need daily use — there, frequency at the right moment matters more. Compare against the norm for your product type, not against Instagram.

Why stickiness matters more than MAU growth

You can pour $1M into ads and double MAU in a month. But if those new users don't come back — DAU doesn't grow, stickiness falls, and a month later MAU collapses back. That's a "leaky bucket".

High stickiness = confirmed product-market fit. First make sure existing users return, then scale acquisition. Growth against falling stickiness is an illusion.

The catch: workdays distort B2B

For B2B tools (Slack, Jira, CRM), users are active 5 days a week, not 7. The structural stickiness ceiling for them is ~71% (5/7), and a realistic "excellent" number is 30-40%, not 50%+.

For such products, calculate DAU/WAU (Weekly Active Users) or stickiness over workdays only — it's more honest.

4 levers to grow Stickiness

1. Shorten time-to-value in onboarding

A user who gets value in the first session returns far more often. Remove friction between sign-up and the "aha moment".

2. Return triggers

3. Habit loops

Trigger → action → variable reward → investment. The more often the loop runs, the stronger the habit. Social apps are masters of this; SaaS can build it in gently (a daily metrics summary).

4. Expand use-cases

One scenario = used occasionally. Several related scenarios = a reason to come back more often. Notion grew from notes into a "second brain" exactly this way.

Real-world: the leaky-bucket math

Product A: MAU 100k, stickiness 10% → DAU 10k
Product B: MAU 50k, stickiness 40% → DAU 20k

Product B is half the size by MAU but has twice the DAU and far higher monetization and retention. Investors and advertisers pay for DAU and engagement, not for "registered" users.

When Stickiness is MISLEADING

1. Product type — for transactional services, low stickiness is normal
2. Workdays — the B2B ceiling is ~71%, don't compare to 7-day products
3. Bots and fraud — inflated DAU overstates stickiness
4. Definition of "active" — opening a push ≠ a real session; pin down an honest definition of Active

Relationship to other metrics

MetricRelationship to Stickiness
DAU / MAUThe components of the formula themselves
RetentionHigh retention → high stickiness
ARPDAUStickiness × monetization = revenue per user
ChurnLow stickiness is an early predictor of future churn

Bottom line

Stickiness is a real-habit detector. Compare it to your product type (not to social apps); for B2B, account for workdays. First raise the stickiness of existing users, then scale MAU — otherwise you're pouring water into a leaky bucket. Rising stickiness is the best confirmation that the product is genuinely needed.

Calculate your Stickiness below — the built-in calculator shows the % and an interpretation.

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Further resources

🧮 Calculate it right here:

Open the full version: https://metricstree.vercel.app/stickiness

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