Monthly Active Users
What is Monthly Active Users?
Monthly Active Users (MAU) is the count of unique users who engage with a product, application, or platform at least once within a 30-day period. In B2B SaaS and product-led growth contexts, MAU serves as a fundamental engagement metric that measures the breadth of a product's active user base rather than the depth of usage by individual users.
MAU provides a standardized measurement for tracking product adoption, user retention, and overall platform health across comparable time periods. When a project management platform counts 12,500 unique users who logged in and performed at least one action during March, they report 12,500 MAU for that month. This metric differs from total registered users or license counts by focusing specifically on active engagement rather than potential or historical usage. A company might have 20,000 registered accounts but only 12,500 MAU, revealing that 37.5% of registered users have become inactive or dormant.
For product-led growth companies, MAU serves multiple strategic purposes beyond simple user counting. Product teams track MAU trends to understand whether new features drive engagement growth or existing changes cause user attrition. Go-to-market teams analyze MAU alongside revenue metrics to calculate revenue per MAU, revealing monetization efficiency. Customer success teams segment MAU by cohort, plan tier, or company size to identify retention patterns and expansion opportunities. Investor relations teams report MAU as a key metric that demonstrates product-market fit and growth trajectory, particularly for freemium models where MAU growth precedes revenue growth as users discover value before converting to paid plans.
Key Takeaways
MAU measures active engagement, not total accounts: Focuses on users who actually interact with the product within 30 days rather than cumulative registrations or license seats
Standard metric for product-led growth: Enables benchmarking across products and time periods to assess engagement trends and product health
Foundation for key unit economics: Revenue per MAU, cost per MAU, and MAU-to-paid conversion rate reveal monetization efficiency and growth sustainability
Leading indicator of retention health: Flat or declining MAU signals engagement problems before they manifest in revenue churn
Requires clear activity definitions: What constitutes "active" varies by product—login alone vs. core action completion significantly impacts reported numbers
How It Works
Monthly Active Users calculation involves defining qualifying activities, identifying unique users who performed those activities within the measurement period, and tracking the metric consistently across time periods for meaningful trend analysis. The measurement methodology requires careful consideration of what "active" means in your specific product context.
The calculation begins with defining the qualifying actions that constitute active usage. For some products, a simple login suffices as the active threshold since users must authenticate to access core functionality. Other products use more stringent definitions like "completed a core workflow," "created or edited content," or "engaged with key features" to ensure MAU counts only users deriving real value. A social media platform might require posting, commenting, or messaging rather than just viewing content, while a CRM might count users who created or updated records rather than those who merely opened the application.
Once activity thresholds are established, systems track unique user identifiers who meet criteria within rolling 30-day windows. The uniqueness requirement prevents double-counting users who log in multiple times per month. If UserID 12345 logs in 47 times during March, they count as one MAU, not 47. This user-centric counting provides accurate audience size measurements rather than session or event totals that inflate true usage.
The basic formula is: MAU = Count of Unique Users Meeting Activity Criteria in Previous 30 Days. On March 31st, you count how many distinct users performed qualifying actions between March 1-31. The same calculation on April 30th covers April 1-30, creating month-over-month trend data. Some teams calculate MAU daily using rolling 30-day windows (today plus the previous 29 days) for more granular monitoring rather than waiting for calendar month completions.
Advanced MAU analysis segments the metric by user characteristics to reveal patterns that aggregate numbers mask. Breaking MAU down by account plan (free vs. paid), company size (SMB vs. enterprise), user role (admin vs. member), or cohort (signup month) shows whether growth concentrates in valuable segments or comes from low-intent users unlikely to convert or retain. A product showing 50% MAU growth driven entirely by free users who never upgrade represents a different situation than 30% growth from paying customers expanding usage.
MAU becomes more valuable when analyzed alongside complementary metrics. The MAU-to-registered user ratio shows what percentage of your total user base remains active. The MAU-to-paid user ratio reveals how many active users you must engage to support your paying customer base in freemium models. MAU growth rate indicates whether you're expanding the active user base or plateauing despite continued registrations. These derived metrics transform MAU from a simple count into a strategic indicator of product health and business performance.
Platforms also track MAU consistency through retention cohorts. If January's 10,000 MAU includes 7,000 users from that month's signups plus 3,000 from prior months, you understand new versus returning user composition. Watching how many of January's MAU remain active in February, March, and beyond reveals retention curves that predict long-term platform growth sustainability.
Key Features
Rolling window calculation: Measured over continuous 30-day periods rather than strict calendar months for consistent comparisons
User deduplication: Counts each unique user once regardless of session frequency or time spent
Segmentation capabilities: Breaks down by user attributes like plan tier, role, geography, or acquisition channel for targeted analysis
Cohort tracking: Measures what percentage of MAU comes from recent signups versus retained users from previous periods
Activity threshold flexibility: Allows companies to define "active" based on product-specific meaningful engagement criteria
Use Cases
Freemium Conversion Funnel Optimization
A B2B collaboration platform with a freemium model tracks MAU across free and paid user segments to optimize their conversion funnel and identify upgrade triggers. Analysis reveals that while total MAU grows 35% quarter-over-quarter, only 3% of free MAU converts to paid plans. Deeper segmentation shows that free users who adopt 3+ integrations within their first 30 days convert at 18% rates compared to 1% for those using the platform in isolation. The product team uses these insights to redesign onboarding flows that encourage integration setup during initial activation, implements in-app prompts that surface integrations based on detected workflows, and creates targeted email campaigns introducing relevant integrations to free users showing high engagement. These changes increase the percentage of free MAU reaching the 3-integration threshold from 12% to 28%, driving overall free-to-paid conversion from 3% to 7% and adding $2.4M in annual recurring revenue.
Product Health Monitoring and Churn Prevention
A SaaS analytics platform tracks MAU trends by customer account to identify at-risk companies before revenue churn materializes. Their system flags accounts where MAU drops more than 25% month-over-month as at-risk, triggering customer success outreach. In Q4, they identify 47 accounts meeting this criteria and conduct proactive health checks. Investigation reveals that 18 accounts experienced team restructuring reducing user count naturally, 12 encountered technical issues preventing login, 9 found competing products, and 8 weren't achieving expected value from the platform. The customer success team resolves technical issues for the 12 affected accounts, offers expanded training to the 8 struggling with value realization, and accepts that the others represent natural account contraction or competitive losses. This MAU-triggered intervention prevents $580K in revenue churn that would have occurred without early warning signals that usage declines provide before customers formally cancel.
Product-Market Fit Validation for New Features
A project management platform launches a new Gantt chart module and uses MAU specifically for that feature to measure adoption and validate product-market fit. They track how many of their overall 45,000 MAU engage with Gantt charts at least once monthly. After launch, Gantt-specific MAU grows to 4,500 (10% of total MAU) within 60 days, then plateaus. User research reveals that while 10% adoption indicates some product-market fit, the plateau suggests the feature appeals primarily to project managers in traditional industries rather than the agile software teams that comprise 60% of their user base. The product team uses this MAU data to refine their roadmap, deprioritizing additional Gantt investments in favor of Kanban enhancements that research indicates would resonate with the larger agile segment. This MAU-informed prioritization prevents six months of development on features that would serve only 10% of users, redirecting resources toward capabilities with broader adoption potential.
Implementation Example
Here's a comprehensive MAU tracking and analysis framework that product operations teams can implement to monitor engagement and identify growth opportunities:
Monthly Active Users Dashboard
Metric | Current Month | Previous Month | 3-Month Avg | YoY Growth | Benchmark |
|---|---|---|---|---|---|
Total MAU | 47,250 | 45,100 | 44,800 | +42% | Target: 50K |
Free MAU | 38,600 | 37,200 | 37,100 | +48% | — |
Paid MAU | 8,650 | 7,900 | 7,700 | +24% | — |
MAU Growth Rate | +4.8% | +3.2% | +3.9% | — | Target: +5% |
Free-to-Paid Ratio | 4.5:1 | 4.7:1 | 4.8:1 | — | Industry: 5:1 |
MAU/Registered Users | 56% | 58% | 59% | -3% | Target: 60%+ |
MAU Segmentation Analysis
MAU Cohort Retention Table
Signup Month | Month 0 (Signup) | Month 1 | Month 2 | Month 3 | Month 6 | Month 12 |
|---|---|---|---|---|---|---|
Jan 2025 | 2,400 | 1,680 (70%) | 1,392 (58%) | 1,152 (48%) | — | — |
Oct 2024 | 2,100 | 1,470 (70%) | 1,218 (58%) | 1,008 (48%) | 735 (35%) | — |
Apr 2024 | 1,950 | 1,365 (70%) | 1,091 (56%) | 936 (48%) | 663 (34%) | 429 (22%) |
Oct 2023 | 1,800 | 1,260 (70%) | 1,008 (56%) | 864 (48%) | 612 (34%) | 396 (22%) |
Insight: Consistent 70% Month 1 retention, dropping to 22% by Month 12
MAU Growth Driver Analysis
Growth Source | Contribution to MAU Growth | Volume | Notes |
|---|---|---|---|
New User Signups | +4,200 MAU | +4,200 | Strong top-of-funnel |
Reactivated Users | +850 MAU | +850 | Win-back campaigns working |
Churned Users | -2,900 MAU | -2,900 | Natural attrition |
Net MAU Change | +2,150 (+4.8%) | — | Healthy growth |
MAU-Based Unit Economics
Metric | Value | Calculation | Trend |
|---|---|---|---|
Revenue per MAU | $47.20 | Monthly Revenue / Total MAU | +8% YoY |
Cost per MAU | $12.80 | (CAC + Hosting) / MAU | -3% YoY |
Gross Margin per MAU | $34.40 | Revenue per MAU - Cost per MAU | +12% YoY |
MAU to Customer Ratio | 28:1 | Total MAU / Paying Customers | Stable |
Free-to-Paid Conversion | 4.2% | Paid Users / Free MAU | +0.8% YoY |
According to Andreessen Horowitz's consumer metrics guide, healthy consumer products maintain MAU growth rates of 10-20% monthly in early stages, decelerating to 3-5% monthly at scale. For B2B SaaS with freemium models, OpenView Partners' benchmarks show that leading product-led companies achieve 40-60% year-over-year MAU growth while maintaining MAU-to-paid conversion rates of 3-7%.
Related Terms
Daily Active Users: Similar metric measured over 24-hour periods for more granular engagement tracking
Product-Led Growth: Growth strategy where MAU serves as a key metric for product adoption and virality
Product Qualified Lead: User segment within MAU showing behaviors indicating sales-readiness
Activation Rate: Percentage of new signups who become MAU by completing key onboarding milestones
Churn Rate: Metric measuring MAU loss that complements MAU growth tracking
Feature Adoption Rate: Tracks what percentage of MAU actively uses specific product capabilities
Net Revenue Retention: Revenue metric often analyzed alongside MAU to understand monetization efficiency
Customer Lifetime Value: Economic value per user that MAU growth should ultimately increase
Frequently Asked Questions
What is monthly active users (MAU)?
Quick Answer: Monthly active users (MAU) is the count of unique users who engage with a product at least once within a 30-day period, serving as a key metric for measuring product adoption, engagement, and overall platform health.
MAU quantifies how many distinct people actively use your product within any given month rather than simply counting total registrations or licensed seats. If your collaboration platform has 50,000 registered accounts but only 28,000 users logged in and performed actions during March, your MAU is 28,000. This metric focuses on active engagement rather than passive account existence, providing a more accurate picture of your product's actual user base and engagement levels. Product teams track MAU trends over time to understand whether new features drive growth, identify engagement problems before they cause churn, and measure the effectiveness of retention initiatives.
How do you calculate MAU?
Quick Answer: Calculate MAU by counting unique users who performed qualifying actions within a 30-day period: MAU = Count of Unique User IDs Meeting Activity Threshold During Previous 30 Days, with "activity" defined by product-specific engagement criteria.
MAU calculation requires first defining what "active" means for your specific product context—typically login plus core action completion like creating content, updating records, or engaging with key features. Then count how many distinct user identifiers performed these qualifying activities within your measurement window. If the same user logs in 20 times during the month, they count as one MAU, not 20. Most teams calculate MAU at month-end by counting unique active users across the previous 30 calendar days, though some use rolling 30-day windows for daily MAU tracking. The key is consistency—maintaining the same activity definition and calculation methodology across time periods to ensure trend data remains comparable and meaningful.
What's the difference between MAU and total users?
Quick Answer: Total users counts all registered accounts regardless of activity status, while MAU counts only users who actively engaged within the past 30 days, making MAU a more accurate indicator of current platform health and engagement.
Total users represents the cumulative count of everyone who ever created an account or received access to your platform, including users who signed up years ago and never returned. This metric grows perpetually but doesn't reflect current engagement or product health. MAU specifically measures recent active usage by counting only users who interacted with your product within the past 30 days. A product might report 100,000 total users but only 35,000 MAU, revealing that 65% of registered accounts have become dormant. The MAU-to-total-users ratio indicates retention effectiveness—strong products maintain 50-70%+ ratios showing most registered users remain active, while weak ratios below 30% suggest high abandonment rates and engagement problems. Investors and product teams focus on MAU rather than total users because MAU better predicts revenue potential, product-market fit, and growth sustainability.
What is a good MAU growth rate?
Quick Answer: Good MAU growth rates depend on company stage—early products should target 10-20% monthly growth, while mature platforms aim for 3-5% monthly or 40-60% year-over-year growth, with retention health as important as absolute growth velocity.
MAU growth benchmarks vary significantly by product maturity, market size, and growth stage. Early-stage products in large markets should target 10-20% month-over-month MAU growth as they find product-market fit and scale initial user acquisition. As products mature and user bases expand, growth rates naturally decelerate to 3-5% monthly at scale since percentage growth becomes harder against larger bases. According to Pacific Crest's SaaS survey, top-quartile SaaS companies achieve 40-60% year-over-year growth in key engagement metrics like MAU. However, growth rate alone doesn't tell the complete story—a product growing MAU 15% monthly through promotions that attract low-quality users who churn quickly demonstrates worse health than one growing 5% monthly with strong retention. Sustainable MAU growth balances new user acquisition with cohort retention rates above 30% at 6 months to ensure growth compounds rather than churns through users.
How does MAU relate to revenue in product-led growth?
In product-led growth models, MAU serves as the top-of-funnel metric that feeds downstream conversion to revenue through freemium activation and upgrade funnels. The relationship follows a multiplication chain: MAU × Free-to-Paid Conversion Rate × Average Revenue Per Paying User = Monthly Recurring Revenue. A product with 50,000 MAU, 4% free-to-paid conversion, and $40 average revenue per user generates $80,000 MRR (50,000 × 0.04 × $40). This relationship means revenue growth can come from expanding MAU, improving conversion rates, or increasing per-user monetization. Strong product-led companies optimize all three simultaneously—growing MAU through viral adoption, improving conversion through better onboarding and feature exposure, and expanding average revenue through usage-based pricing or successful upsells. The revenue-per-MAU metric reveals monetization efficiency, with best-in-class PLG companies achieving $50-100+ monthly revenue per MAU compared to $10-30 for less mature products. Tracking both MAU growth and revenue per MAU ensures balanced optimization focused on both audience expansion and monetization effectiveness.
Conclusion
Monthly Active Users stands as a foundational metric for product-led growth companies and any SaaS business seeking to understand product engagement beyond vanity metrics like total registrations or page views. For product teams, MAU trends provide immediate feedback on whether features drive engagement growth or changes cause user attrition. The metric serves as an early warning system for retention problems, revealing declining engagement weeks or months before revenue churn materializes in financial results.
Growth and marketing teams use MAU analysis to understand which acquisition channels deliver users who remain active versus those who sign up but never engage. Customer success teams segment MAU by account to identify expansion opportunities among highly engaged users and at-risk situations where declining MAU signals potential churn. Revenue operations leaders track MAU alongside monetization metrics to calculate unit economics like revenue per MAU and cost per MAU that determine long-term business sustainability and growth efficiency.
As product-led growth strategies become increasingly central to B2B SaaS go-to-market approaches, the ability to systematically track, analyze, and optimize MAU becomes a competitive advantage. Organizations that treat MAU as a strategic metric—segmenting by user characteristics, analyzing cohort retention curves, and connecting usage patterns to revenue outcomes—position themselves to make data-driven decisions about product development, marketing investments, and customer success interventions. For GTM leaders building measurement frameworks, understanding MAU dynamics and relationships to downstream conversion metrics provides the foundation for sustainable growth strategies that balance user acquisition with retention and monetization.
Last Updated: January 18, 2026
