MAU
What is MAU?
MAU (Monthly Active Users) measures the number of unique users who engage with a product or service at least once during a 30-day period. This metric serves as a fundamental indicator of product engagement, user base size, and growth trajectory, particularly for SaaS companies, mobile apps, and product-led growth businesses.
Unlike simple registered user counts that include inactive accounts, MAU focuses exclusively on users who actively use the product within the measurement window. A "unique user" is counted only once regardless of how many times they engage during the month, and "active" is defined by specific engagement criteria that vary by product—logging in, performing a core action, or completing a meaningful workflow. This distinction between registered users and active users reveals the real health of a product's user base.
MAU has become the industry standard engagement metric for product-led companies because it balances comprehensiveness with actionability. According to Bessemer Venture Partners' Cloud Index, public cloud companies average 70-80% MAU/registered user ratios, with best-in-class PLG companies exceeding 85%. For B2B SaaS companies, MAU provides critical insights into product adoption, feature stickiness, and user retention that directly correlate with expansion revenue and churn risk. Understanding MAU trends enables product and growth teams to identify engagement issues early and optimize for sustainable growth.
Key Takeaways
Active Engagement Focus: MAU counts only users who meaningfully engage within 30 days, providing a more accurate picture of product health than total registered users
Unique User Deduplication: Each user is counted once per month regardless of activity frequency, measuring reach rather than intensity of engagement
Product-Specific Definition: "Active" criteria must be customized to each product's core value proposition—what constitutes meaningful engagement varies significantly
Growth and Retention Indicator: MAU trends reveal whether a product is growing (new user acquisition), stagnating, or declining in engagement over time
Foundation for Advanced Metrics: MAU serves as the denominator or component for calculating DAU/MAU ratio, stickiness, feature adoption rates, and monetization metrics
How It Works
MAU calculation and tracking involves several key components that work together to provide meaningful engagement insights:
Define "Active" Criteria: Product teams must establish what specific user actions constitute "active" usage. For a CRM, this might be logging in and viewing or editing records. For a collaboration tool, it could be posting messages, commenting, or sharing files. For analytics software, it might be running reports or viewing dashboards. The active definition should reflect core product value—actions that indicate users are getting value from the product rather than superficial engagement like simply logging in.
User Identification and Tracking: Implement tracking systems that identify unique users across sessions and devices. Most products use user IDs from authentication systems to track individual users. For applications with anonymous usage, implement fingerprinting or device identification. The key is consistently identifying the same user across multiple interactions within the measurement period.
30-Day Rolling Window: Calculate MAU using a rolling 30-day window rather than calendar months. This provides consistent measurements regardless of whether a month has 28, 30, or 31 days and enables daily MAU tracking. On any given day, MAU represents the count of unique users who performed qualifying actions at least once in the preceding 30 days.
Deduplication Logic: Ensure that users who perform active behaviors multiple times within the month are counted only once. The system tracks when each user last performed an active action and includes them in MAU as long as their last activity falls within the 30-day window.
Segmentation and Analysis: Calculate MAU across different user segments, geographies, plan tiers, or cohorts to understand engagement patterns. For example, tracking MAU separately for free versus paid users, or for different customer segments, reveals where engagement is strongest and where retention issues may exist.
Trend Monitoring: Track MAU over time to identify growth trends, seasonal patterns, or engagement declines. Week-over-week and month-over-month MAU growth rates provide key signals about product health and market traction.
Cross-Metric Analysis: Combine MAU with other metrics for deeper insights. MAU/registered user ratio reveals activation and engagement quality. DAU/MAU ratio (stickiness) measures how frequently active users engage. MAU paired with revenue metrics shows monetization efficiency.
According to Amplitude's product analytics research, successful B2B SaaS companies typically see 60-80% of their registered users active monthly, while consumer applications may see 30-50% depending on their value proposition and use case frequency.
Key Features
User Base Measurement: Provides standardized metric for communicating product scale and comparing growth across time periods
Engagement Quality Signal: Reveals what percentage of registered users find enough value to actively use the product monthly
Cohort Tracking Compatible: Enables analysis of how MAU evolves for different user acquisition cohorts over time
Segmentation Flexibility: Can be calculated for any user segment, geography, plan type, or customer characteristic
Growth Rate Foundation: Month-over-month MAU growth serves as a key performance indicator for product-led companies
Use Cases
Product-Led Growth Metrics
Product-led growth companies use MAU as a primary metric for board reporting, investor updates, and internal performance tracking. PLG businesses like Slack, Dropbox, and Notion built their growth strategies around expanding MAU through viral adoption and product excellence. Growth teams monitor MAU trends alongside activation rates to ensure new user acquisition translates into ongoing engagement. When MAU growth slows, teams investigate whether the issue stems from reduced new user acquisition or declining engagement from existing users, enabling targeted interventions.
Feature Adoption and Product Development
Product teams track MAU by feature or product area to understand which capabilities drive engagement and retention. By calculating MAU for specific features—for example, "users who used the reporting module" or "users who created automations"—product managers identify which features create stickiness and which remain underutilized. This data informs product roadmap decisions, helping teams prioritize features that increase MAU and deprecate capabilities that few users engage with. Integration with product usage data platforms enables detailed journey analysis showing how feature adoption correlates with MAU retention.
Revenue Forecasting and Monetization
Revenue operations and finance teams use MAU trends to forecast revenue potential and optimize monetization strategies. For freemium products, the conversion rate from MAU to paying customers provides a key funnel metric. For usage-based pricing models, MAU often directly correlates with revenue—more active users mean more seats, API calls, or consumption. By analyzing the relationship between MAU, engagement depth, and expansion revenue, RevOps teams identify ideal engagement patterns that predict upsell opportunities. Platforms like Saber can help identify which companies show MAU growth patterns indicating strong product-market fit and expansion potential.
Implementation Example
Here's a comprehensive MAU tracking and analysis framework for a B2B SaaS product:
MAU Definition Framework
Product: Marketing Automation Platform
User Action | Counts as Active? | Rationale |
|---|---|---|
Login to platform | No | Superficial—doesn't indicate value realization |
View dashboard | No | Passive consumption, minimal value |
Create/edit email campaign | Yes | Core product value—campaign creation |
Send email campaign | Yes | Core product value—campaign execution |
View campaign analytics | Yes | Using insights to drive decisions |
Create automation workflow | Yes | Advanced feature indicating deep engagement |
Edit contact/list | Yes | Data management critical to platform use |
API call (automated) | Yes | Programmatic usage indicates integration |
Account settings change | No | Administrative, doesn't reflect core value |
Active User Definition: User who performs at least one "Yes" action within 30-day window
MAU Tracking Dashboard
MAU by Customer Segment
Segment | MAU | Registered | MAU/Reg Ratio | MoM Growth | Paid Conversion |
|---|---|---|---|---|---|
Enterprise | 3,245 | 3,890 | 83.4% | +5.1% | 94.2% |
Mid-Market | 8,934 | 11,203 | 79.7% | +7.8% | 86.5% |
SMB | 9,156 | 13,421 | 68.2% | +9.4% | 52.1% |
Free/Trial | 3,232 | 3,936 | 82.1% | +12.3% | 0% (target for conversion) |
Key Insights:
- Enterprise shows highest engagement ratio—sticky product in large orgs
- SMB lower engagement suggests potential fit issues or onboarding gaps
- Free/Trial high engagement (82%) indicates strong activation—good conversion funnel quality
MAU Cohort Retention Analysis
30-Day Cohort Retention (by Signup Month)
Signup Cohort | Starting Users | Month 1 MAU | Month 3 MAU | Month 6 MAU | Month 12 MAU |
|---|---|---|---|---|---|
Jan 2025 | 1,847 | 1,534 (83%) | 1,312 (71%) | 1,165 (63%) | 1,034 (56%) |
Apr 2025 | 2,103 | 1,789 (85%) | 1,557 (74%) | 1,420 (68%) | - |
Jul 2025 | 2,456 | 2,131 (87%) | 1,936 (79%) | - | - |
Oct 2025 | 2,789 | 2,467 (88%) | - | - | - |
Cohort Insights: Recent cohorts showing improved retention—product improvements and onboarding enhancements appear effective
MAU Feature Adoption Analysis
Feature-Specific MAU (January 2026)
Feature | MAU | % of Total MAU | MoM Growth | Engagement Impact |
|---|---|---|---|---|
Email Campaigns | 21,234 | 86.4% | +7.1% | Core feature—high baseline |
Automation Workflows | 12,456 | 50.7% | +11.3% | Power user indicator |
A/B Testing | 8,765 | 35.7% | +15.2% | Growing adoption—successful rollout |
CRM Integration | 14,234 | 57.9% | +9.8% | Stickiness driver |
Advanced Analytics | 6,543 | 26.6% | +18.4% | Fastest growing—good positioning |
Social Posting | 3,421 | 13.9% | +2.1% | Low adoption—consider deprecation |
Product Insights: Advanced Analytics showing strong adoption growth—indicates successful product positioning and demand for sophistication
MAU Health Scoring Framework
MAU-Driven Action Framework
Scenario: MAU Growth Slowing
This framework enables product, growth, and revenue operations teams to systematically track, analyze, and act on MAU data to drive product engagement and business growth.
Related Terms
Product-Led Growth: Growth strategy where product usage drives acquisition, retention, and expansion—heavily reliant on MAU metrics
DAU (Daily Active Users): Daily equivalent of MAU, measuring users active within 24 hours
Activation Rate: Percentage of new users who reach active status, feeding MAU growth
Feature Adoption: Measurement of which features users engage with, often expressed as percentage of MAU
Product Usage Data: Detailed behavioral data from which MAU and related engagement metrics are calculated
Customer Health Score: Predictive metric often incorporating MAU and engagement patterns
Churn Rate: Percentage of users who stop being active, directly impacting MAU trends
Frequently Asked Questions
What is MAU?
Quick Answer: MAU (Monthly Active Users) measures the number of unique users who actively engage with a product at least once during a 30-day period, serving as a key metric for product engagement and growth.
MAU differs from simple registered user counts by focusing exclusively on users who actually use the product within the measurement window. A user who signed up months ago but hasn't logged in recently doesn't count toward MAU, while a user who engages multiple times per month counts only once. This metric provides a more accurate picture of product health than vanity metrics like total registered users. For B2B SaaS and product-led growth companies, MAU serves as a fundamental metric for measuring product adoption, tracking growth, and predicting revenue, since active engagement typically correlates strongly with retention and expansion opportunities.
How is MAU calculated?
Quick Answer: MAU is calculated by counting the number of unique users who performed at least one qualifying "active" action within a rolling 30-day period, with each user counted only once regardless of activity frequency.
To calculate MAU, first define what constitutes "active" usage for your product—typically core actions that indicate value realization rather than superficial engagement. Implement tracking that identifies unique users (usually via user IDs from your authentication system) and logs when they perform qualifying actions. For any given day, count the number of distinct users who performed at least one active action in the preceding 30 days. Use rolling 30-day windows rather than calendar months for consistency. For example, if User A logs in and performs active actions on days 1, 15, and 28 of the month, they count as 1 MAU. If User B only performed active actions 35 days ago, they don't count in current MAU.
What's the difference between MAU and registered users?
Quick Answer: Registered users counts all accounts ever created, while MAU counts only users who actively engaged with the product in the last 30 days, providing a more accurate measure of active user base.
Registered users is a cumulative count that only increases—every new signup adds to the total, even if that user never returns. This creates misleading growth metrics since the number always trends upward regardless of actual product engagement. MAU, in contrast, measures only recently active users, so it can decrease if users stop engaging or churn. A product might have 100,000 registered users but only 30,000 MAU, indicating that 70% of users who ever signed up are no longer active. The MAU/registered user ratio (in this example, 30%) reveals engagement quality—higher ratios indicate better activation and retention. Investors and leadership teams focus on MAU rather than registered users because it reflects real product engagement and revenue potential.
What is a good MAU growth rate?
Good MAU growth rates vary significantly by company stage, market, and business model, but B2B SaaS companies typically target 5-10% month-over-month MAU growth in scaling phases. Early-stage product-led growth companies often achieve 10-20% monthly MAU growth during rapid adoption phases, while mature companies may see 2-5% monthly growth as they reach market saturation. According to OpenView Partners' PLG benchmarks, best-in-class PLG companies achieve 70-100%+ year-over-year MAU growth while maintaining strong engagement ratios. Context matters significantly—10% monthly growth on a base of 1,000 MAU is very different from 10% growth on 100,000 MAU. Focus on sustainable, quality growth where new MAU converts to paid users and exhibits strong retention rather than vanity growth from users who quickly churn.
How does MAU relate to revenue?
MAU's relationship to revenue depends on business model but typically shows strong correlation in most SaaS contexts. For seat-based pricing models, MAU directly impacts revenue since more active users mean more seats purchased. For usage-based pricing, MAU often correlates with consumption—more active users generate more API calls, storage, or transactions. For freemium models, MAU represents the top of the monetization funnel—converting a percentage of MAU to paid users drives revenue, making MAU growth essential for revenue growth. Even for companies with fixed subscription pricing, MAU serves as a leading indicator of expansion revenue and churn risk. Accounts with growing MAU typically expand, while declining MAU signals churn risk. Revenue operations teams track MAU alongside annual recurring revenue to understand both growth efficiency (revenue per MAU) and growth sustainability (whether MAU growth supports revenue growth).
Conclusion
MAU stands as one of the most important metrics for understanding product health, user engagement, and growth trajectory in modern B2B SaaS and product-led businesses. Unlike vanity metrics that can mask underlying issues, MAU provides an honest assessment of how many users find your product valuable enough to actively use month after month. This focus on active, engaged users rather than accumulated registrations drives better decision-making across product, growth, and revenue teams.
For GTM organizations, MAU insights inform strategy across acquisition, activation, and monetization. Product teams use MAU trends and feature-specific MAU to prioritize development that increases engagement and stickiness. Growth teams optimize onboarding and activation to convert new users into active monthly users. Customer success teams monitor MAU patterns at the account level to identify expansion opportunities and churn risks. Revenue operations leaders analyze the relationship between MAU growth and revenue growth to understand monetization efficiency and forecast future performance.
As product-led growth continues to transform B2B go-to-market strategies, mastering MAU measurement, analysis, and optimization becomes increasingly critical. Companies that deeply understand what drives MAU growth, how different user segments engage, and which features create stickiness will build sustainable competitive advantages through superior product engagement and customer lifetime value.
Last Updated: January 18, 2026
