TL;DR
WAU/MAU ratio measures weekly active users as a percentage of monthly active users — the engagement metric more appropriate for B2B SaaS where daily use isn't expected. 60-75% indicates strong weekly habit; below 40% suggests the product isn't yet a weekly tool. Better signal than DAU/MAU for most B2B SaaS, planning tools, and analytics products.
What is WAU/MAU ratio?
WAU/MAU ratio measures how often the average monthly active user returns within a typical week. Formula: Weekly Active Users / Monthly Active Users × 100. A 65% WAU/MAU means the average monthly user is active in roughly 2.6 of the 4 weeks in a month.
It is the cadence-appropriate alternative to DAU/MAU for products where daily use is not the goal. Most B2B SaaS — analytics tools, planning software, RevOps platforms, marketing automation — are weekly tools by design. Reporting DAU/MAU for these products produces deceptively low numbers; WAU/MAU is the right reading.
Why WAU/MAU matters
For B2B SaaS, WAU/MAU correlates more strongly with NRR and contract expansion than DAU/MAU. A team using a workflow tool 2-3 days per week is structurally as engaged as a team using a daily tool every weekday — both are weekly habits, and weekly habits drive retention.
Figma is the canonical example: designers don't use Figma daily (often working in other tools), but they use it most weeks. Figma reports WAU/MAU specifically because DAU/MAU would understate engagement. Same for Notion, Linear, Productboard, and most planning/analytics tools.
When to use WAU/MAU vs DAU/MAU
| Product type | Use WAU/MAU or DAU/MAU? |
|---|---|
| B2B analytics, planning, dashboards | WAU/MAU |
| Design tools (Figma, Linear) | WAU/MAU |
| B2B workflow (Slack, Notion) | DAU/MAU (workday-adjusted) |
| Consumer social (IG, TikTok, Snap) | DAU/MAU |
| Music streaming | DAU/MAU |
| Banking, fintech | MAU growth + WAU/MAU |
| E-commerce | MAU growth (cadence varies) |
Benchmarks
| Product type | Best-in-class WAU/MAU | Median | Below average |
|---|---|---|---|
| B2B SaaS workflow (Figma, Notion) | 65-80% | 45-60% | <35% |
| B2B analytics dashboards | 55-75% | 35-50% | <25% |
| B2B planning tools (Asana, Monday) | 60-75% | 40-55% | <30% |
| B2C subscription content | 45-65% | 25-40% | <18% |
Benchmarks compiled from Reforge Engagement Benchmarks 2025, Amplitude Product Benchmarks 2025, and Sequoia Arc Engagement Framework 2024.
Related metrics
WAU/MAU is the weekly-cadence sibling of DAU/MAU. Pairs with engagement rate, activation rate, retention curve, retention rate, NRR, and customer health score.
At a glance
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Frequently asked questions
What is WAU/MAU?
WAU/MAU is the ratio of weekly active users to monthly active users, expressed as a percentage. It measures how often the average monthly user is active within a typical week. For B2B SaaS, 60-75% is strong; below 40% suggests the product isn't yet a weekly tool.
When should you use WAU/MAU instead of DAU/MAU?
Use WAU/MAU for products where weekly use is the goal: B2B analytics, design tools, planning software, RevOps platforms. Use DAU/MAU for products where daily use is the goal: consumer social, music streaming, B2B workflow tools used every day (Slack).
What is a good WAU/MAU for B2B SaaS?
65-80% is best-in-class for B2B workflow and design tools (Figma, Notion, Linear). 55-75% for analytics dashboards. Below 40% indicates the product hasn't yet established a weekly habit — usually an onboarding or value-delivery problem.
Does WAU/MAU predict retention?
Yes — high WAU/MAU correlates strongly with NRR and contract expansion in B2B SaaS. A team using a workflow tool most weeks is structurally as engaged as a daily-use product team and drives the same retention compounding. Pair WAU/MAU with cohort retention curves for the full picture.
Sources
- Reforge. Engagement Benchmarks Report 2025, 2025. reforge.com
- Amplitude. 2025 Product Benchmarks Report, 2025. amplitude.com
- Sequoia. The Arc Engagement Framework, 2024. sequoiacap.com
Fairview tracks WAU/MAU alongside NRR and customer health in one operating view — see the operating intelligence overview for the broader category.
Definitions and benchmarks reviewed by Siddharth Gangal, Founder, Fairview.
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