DAU / MAU Ratio Calculator
Calculate stickiness against best-in-class benchmarks
Type your daily active users and monthly active users — get DAU/MAU ratio (stickiness) plus benchmarks: WhatsApp 71%, Instagram 60%, Spotify 35%, Slack 30%, median SaaS 13%.
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What is a DAU / MAU Ratio Calculator?
DAU/MAU is the simplest and most-quoted product engagement metric. It answers: of your monthly users, what percentage come back on any given day? The math is one division. The interpretation is everything — a 13% stickiness for a SaaS analytics tool is healthy; for a chat app, it's a death sentence.
This calculator returns the ratio plus a comparison band against the canonical references: WhatsApp ~71%, Instagram ~60%, Spotify ~35%, Slack ~30%, median SaaS ~13%. The benchmarks are public and frequently cited, so the comparison gives a defensible reference point for your investor deck or board review.
Use it monthly for trend tracking, before fundraising (DAU/MAU is what every investor will ask), and after major releases to see if engagement actually improved.
Why use this DAU / MAU Ratio Calculator
Built for Indians, by Indians. Every number, every formula, every slab — tuned to FY 2026-27 reality.
Benchmark comparison
See your number against WhatsApp, Instagram, Spotify, Slack, and SaaS median.
Stickiness band
Categorised: world-class (50%+), great (30-50%), healthy (15-30%), weak (<15%).
Live calculation
Type DAU and MAU; ratio appears instantly.
Browser-only
No numbers sent anywhere.
Using the DAU / MAU Ratio Calculator in 4 steps
No onboarding, no signup. Answer three fields and the numbers update live.
Pull DAU and MAU
From GA4, Mixpanel, Amplitude, or your warehouse. Use the same "active" definition for both.
Pick consistent date range
DAU = avg daily active over last 30 days. MAU = unique users in same 30 days.
Enter both
Calculator returns DAU/MAU ratio and benchmark comparison.
Track monthly
Save the score in a spreadsheet. The trend matters more than the absolute.
Tips to get the most out of it
Define "active" precisely and consistently. "Opened the app" is loose; "performed core action" is tight. Stick with one definition forever or your trend is meaningless.
For B2B SaaS, segment by user role. Power users vs. occasional users have wildly different DAU/MAU. The blended number can hide red flags.
DAU/MAU is gameable — daily push notifications inflate it without real engagement. Pair it with depth metrics (sessions per day, time spent).
Don't compare across categories blindly. A B2B tax-filing tool isn't supposed to have WhatsApp's stickiness. Use the SaaS median (13%) as your baseline, not Instagram's 60%.
Real-world scenarios
How Indians actually use this calculator — concrete inputs, concrete outcomes.
Investor pitch sanity check
B2B SaaS prepares Series A pitch. DAU 4,200, MAU 12,000. Stickiness 35% — well above SaaS median 13%. Becomes a flagship slide in the deck.
Consumer app post-launch
Social app DAU 80K, MAU 600K. Stickiness 13% — below Instagram's 60% benchmark. Concerns about category fit. Investigates daily-loop incentives, push strategy.
Internal trend tracking
Founder tracks DAU/MAU monthly. From 9% (Jan) to 18% (Jun) after activation overhaul. Quotes the journey in next investor update — momentum proof.
Frequently Asked Questions
Still have a question? Our team replies within a business day.
It's the simplest and most universal. For deeper engagement, pair it with sessions per active user and core-action frequency. But DAU/MAU is the single number every investor and board asks for.
Median is ~13%. Above 25% is excellent. Productivity tools (Slack, Notion) hit 30%+. Tools used episodically (tax software, recruiting) sit at 5-10% and that's fine for the category.
Either, but be consistent. Mobile apps often use 28 days (4 weeks) for simpler week-on-week comparison. SaaS uses 30 days.
No — DAU is a subset of MAU. If you compute >100%, your data has duplicates or your active definitions don't match.
They're related but not the same. Retention measures what % of a cohort returns. DAU/MAU measures average daily engagement of the current user base. High retention drives high DAU/MAU but they aren't identical.
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