Summarize with AI

Summarize with AI

Summarize with AI

Title

WAU (Weekly Active Users)

What is WAU (Weekly Active Users)?

WAU (Weekly Active Users) is a product engagement metric that counts the number of unique users who perform a meaningful action within your product during a seven-day period. This metric measures active engagement rather than simple account creation or passive subscription status, providing insight into how many users actually derive value from your product each week.

The definition of "active" varies by product and business model but typically involves actions that demonstrate core value realization—logging in, completing key workflows, consuming content, or utilizing primary features. A project management tool might define active users as those who create or update tasks, while a data analytics platform counts users who run queries or view dashboards. The critical element is that WAU measures behavioral engagement rather than account status, distinguishing users who actively benefit from your product from those with dormant accounts.

WAU emerged as a critical metric for B2B SaaS companies because it provides more granular insights than monthly metrics while avoiding the noise of daily fluctuations. Monthly Active Users (MAU) can mask declining engagement trends that become obvious in weekly data, while Daily Active Users (DAU) often show high volatility that makes trend analysis difficult. Weekly measurement aligns well with business rhythms—most B2B work operates on weekly cycles with consistent Monday-Friday patterns—making WAU particularly relevant for understanding how products integrate into professional workflows.

For product-led growth companies, WAU serves as a leading indicator for retention, expansion, and churn. Declining WAU within a customer account signals disengagement before it becomes cancellation. Growing WAU indicates increasing product adoption and potential expansion opportunities. The ratio of WAU to MAU reveals engagement consistency—products with high WAU/MAU ratios demonstrate strong habit formation and sticky value propositions, while low ratios suggest sporadic usage patterns that often precede churn.

Key Takeaways

  • Weekly engagement measurement: WAU counts unique users performing meaningful actions within seven-day periods, providing more granular insights than monthly metrics without daily volatility

  • Product-specific activity definitions: What constitutes "active" varies by product type, requiring clear definitions of value-generating behaviors rather than simple logins

  • Leading retention indicator: Changes in WAU predict churn and expansion earlier than revenue metrics, enabling proactive customer success intervention

  • Habit formation proxy: The WAU/MAU ratio reveals engagement consistency, with ratios above 50% indicating strong weekly usage habits versus sporadic monthly access

  • Growth velocity metric: WAU growth rate measures product adoption speed and viral coefficient impact more responsively than annual recurring revenue changes

How It Works

WAU calculation operates through systematic tracking of user activity across rolling seven-day windows, combining unique user identification with activity threshold definitions to produce weekly engagement counts. The process begins with instrumentation that captures user actions within your product, tagging each activity with a user identifier and timestamp.

The fundamental calculation identifies all unique users who performed at least one qualifying action during a specific seven-day period. If a user completes multiple actions in the same week, they still count as one active user—WAU measures unique engagement, not total activity volume. The calculation typically runs daily, examining the previous seven days to generate current WAU values. For example, WAU calculated on Thursday January 18 includes any user who was active between Friday January 12 and Thursday January 18.

Activity qualification forms the foundation of meaningful WAU measurement. Simply opening the application or remaining logged in typically doesn't constitute "active" usage. Instead, define qualifying actions based on your product's core value proposition and the behaviors that correlate with retention. A design collaboration tool might require users to create or edit files, comment on work, or share projects. An email marketing platform counts users who create campaigns, send emails, or view analytics. These activity thresholds ensure WAU reflects value realization rather than passive access.

User identification enables accurate unique counting across sessions and devices. Authenticated user IDs provide the most reliable identification, linking all activity from a specific user regardless of device or browser. For products with anonymous or guest access, consistent cookie-based identification becomes critical to avoid inflating WAU counts. Account-based metrics aggregate individual users within organizations to understand company-level adoption rather than individual engagement.

Rolling window calculations provide continuous measurement without the artificial boundaries of calendar weeks. While calendar-week WAU (Monday-Sunday) offers business-friendly reporting aligned with work weeks, rolling seven-day windows enable daily tracking of WAU trends without waiting for week-end boundaries. Product analytics platforms like Amplitude and Mixpanel typically calculate both formats, using rolling windows for trend detection and calendar weeks for reporting and target-setting.

Segmentation enhances WAU analysis by revealing engagement patterns across user cohorts, features, or customer segments. Compare WAU across free versus paid users to understand how monetization affects engagement. Track WAU by user role (admin, member, viewer) to identify which personas drive the most active usage. Measure feature-specific WAU to understand which capabilities attract regular engagement versus one-time usage. These segments transform WAU from a single number into a diagnostic tool for product strategy and customer success prioritization.

Key Features

  • Rolling seven-day calculation windows that provide continuous engagement measurement without calendar-week boundaries or reporting gaps

  • Unique user counting logic ensuring individuals count once per period regardless of activity frequency, focusing on reach rather than intensity

  • Product-specific activity thresholds defining meaningful engagement based on core value actions rather than passive presence or simple logins

  • Cohort and segment analysis breaking WAU into user groups, features, or customer segments to identify engagement drivers and at-risk populations

  • Trend visualization and comparison showing WAU growth rates, week-over-week changes, and year-over-year patterns to identify engagement trajectory

Use Cases

Product Engagement Health Monitoring

A B2B collaboration platform with 50,000 total accounts tracks WAU as their primary product health metric. Their 450-person customer success team monitors WAU trends at the account level, with alerts triggered when an account's WAU drops below 40% of their 90-day average. A mid-market customer with typical WAU of 180 users (from 300 total seats) suddenly shows 110 WAU for two consecutive weeks. The customer success manager receives an automated alert, investigates to discover the customer's busiest department experienced leadership changes, and proactively reaches out to schedule re-onboarding training. This WAU-triggered intervention prevents what would have been a $120K annual churn, demonstrating how weekly engagement data enables retention actions before revenue impact materializes.

Feature Adoption and Product Development Prioritization

A project management SaaS company tracks feature-specific WAU to inform product roadmap decisions. They discover their core task management features show 28,000 WAU (82% of total users), while their newer time tracking capability shows only 3,200 WAU (9% of users). Conversely, their recently launched automation features already reach 15,000 WAU (44% of users) despite being available for only two months. These WAU insights drive strategic decisions: deprecate the underutilized time tracking feature to reduce maintenance costs, invest heavily in automation capabilities showing strong adoption velocity, and maintain focus on core task management that drives consistent weekly engagement. The product team discovers that accounts with automation feature WAU above 50% of their total seats have 3.1× lower churn rates, reinforcing investment priorities.

Growth Metric and Viral Coefficient Validation

A freemium design tool uses WAU growth rate as their primary growth metric, tracking weekly changes to measure product-led acquisition effectiveness. Their WAU grows from 125,000 to 143,000 over four weeks (14.4% growth), indicating strong product adoption and viral sharing mechanics. They calculate that each cohort of new users generates an average of 1.2 additional users through invitations and collaboration features within their first month, validated by WAU cohort analysis. When they launch a new file sharing feature that simplifies external collaboration, WAU acceleration increases to 22% monthly growth, confirming the feature's viral impact. The growth team uses WAU as their North Star metric because it reflects actual product value delivery rather than simple signup counts, preventing optimization for vanity metrics that don't correlate with retention or monetization.

Implementation Example

WAU Tracking and Analysis Framework

Implement comprehensive WAU measurement using this systematic approach to definition, calculation, and analysis:

WAU Calculation Architecture
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
<p>Step 1: Define Qualifying Activity<br>┌────────────────────────────────────────────────────────┐<br>Core Value Actions (Product-Specific):                 <br>Task Management App: Create/edit/complete task       <br>Analytics Platform: Run query, view dashboard        <br>Design Tool: Create/edit file, leave comment         <br>CRM: Update contact, log activity, send email        <br><br>Exclusions (Not Active):                               <br>Login without subsequent action                      <br>Page view only                                       <br>Settings changes only                                <br>└────────────────────────────────────────────────────────┘</p>
<p>Step 2: Calculate WAU (Rolling 7-Day Window)<br>For date D:<br>WAU = COUNT(DISTINCT user_id)<br>WHERE activity_timestamp >= D - 7 days<br>AND activity_timestamp <= D<br>AND activity_type IN (qualifying_actions)</p>


WAU Tracking Dashboard

Monitor weekly engagement trends with key metrics and comparisons:

Metric

Current Week

Previous Week

WoW Change

4-Week Avg

YoY Change

Target

Total WAU

34,280

33,150

+3.4%

32,890

+28.2%

35,000

Free Users WAU

12,450

12,100

+2.9%

11,950

+31.5%

-

Paid Users WAU

21,830

21,050

+3.7%

20,940

+26.4%

-

Power Users (5+ days/week)

8,240

8,010

+2.9%

7,980

+24.1%

9,000

New User WAU (<30 days)

4,120

3,890

+5.9%

3,840

+42.3%

-

At-Risk Accounts (<30% of seats)

142 accounts

138 accounts

+2.9%

145 accounts

-8.4%

<120

Engagement Consistency: WAU/MAU Ratio

The WAU/MAU ratio reveals how consistently users engage weekly versus monthly:

User Segment

WAU

MAU

WAU/MAU Ratio

Interpretation

Action

Enterprise Customers

8,240

12,100

68%

Very Strong - multiple weekly sessions

Expansion opportunity

SMB Paid Users

13,590

24,350

56%

Strong - consistent weekly usage

Maintain engagement

Power Users

8,240

9,100

91%

Exceptional - nearly daily usage

Feature adoption study

Free Trial Users

2,180

6,840

32%

Weak - sporadic engagement

Activation intervention

Freemium Users

10,270

32,150

32%

Weak - monthly check-ins only

Upgrade nurture campaign

Benchmark Standards:
- WAU/MAU > 60%: Excellent habit formation, strong retention predictor
- WAU/MAU 40-60%: Moderate engagement, typical for weekly-use B2B tools
- WAU/MAU 20-40%: Low consistency, high churn risk
- WAU/MAU < 20%: Poor engagement, immediate intervention needed

Account-Level WAU Health Scoring

Track engagement health at the customer account level for proactive retention:

Account

Total Seats

WAU (Current)

WAU (90d Avg)

% of Seats Active

WAU Trend

Health Status

Next Action

Acme Corp

250

184

192

74%

↓ -4%

🟡 Monitor

Check-in call

GlobalTech Inc

180

142

138

79%

↑ +3%

🟢 Healthy

Expansion discussion

StartupXYZ

45

12

28

27%

↓ -57%

🔴 Critical

Urgent intervention

Enterprise Co

500

368

365

74%

→ Stable

🟢 Healthy

QBR schedule

MidMarket LLC

95

58

71

61%

↓ -18%

🟡 Monitor

Usage training offer

Alert Thresholds:
- 🔴 Critical: WAU drops >40% from 90-day average OR <30% of seats active
- 🟡 Warning: WAU drops 15-40% from average OR 30-50% of seats active
- 🟢 Healthy: WAU within 15% of average AND >50% of seats active

Cohort WAU Retention Analysis

Track how different user cohorts maintain weekly engagement over time:

Signup Cohort

Week 1 WAU

Week 4 WAU

Week 8 WAU

Week 12 WAU

12-Week Retention

Notes

October 2025

1,840

1,250

980

820

45%

Baseline cohort

November 2025

2,150

1,620

1,380

1,210

56%

Improved onboarding launched

December 2025

1,690

1,270

1,080

950

56%

Holiday season dip, strong recovery

January 2026

2,480

1,940

-

-

-

New feature driving adoption

Feature-Specific WAU Analysis

Understand which features drive regular engagement versus one-time usage:

Feature

Feature WAU

% of Total WAU

WAU Growth (MoM)

Avg Sessions/Week

User Retention Impact

Core Task Management

28,120

82%

+2.1%

4.2

Baseline (1.0×)

Automation Builder

15,280

45%

+18.4%

2.8

+3.1× retention

Time Tracking

3,240

9%

-2.3%

1.4

-0.3× retention

Reporting Dashboard

12,450

36%

+5.7%

2.1

+1.8× retention

Collaboration Comments

18,690

55%

+8.2%

3.6

+2.4× retention

Mobile App

8,940

26%

+12.1%

5.8

+1.9× retention

Strategic Insights:
- Automation Builder: High growth + strong retention impact = priority investment
- Time Tracking: Low adoption + negative retention = deprecation candidate
- Mobile App: Highest session frequency suggests daily habit formation
- Collaboration: Over half of users engage weekly = core differentiation

WAU Growth Velocity Dashboard

Track growth metrics to measure product-led acquisition effectiveness:

Period

WAU

New Users Added

WAU Growth

Churn (Lost WAU)

Net Growth

Growth Rate

Week 1

31,250

2,180

+2,180

-840

+1,340

+4.3%

Week 2

32,590

2,340

+2,340

-1,000

+1,340

+4.1%

Week 3

33,150

1,920

+1,920

-1,360

+560

+1.7%

Week 4

34,280

2,450

+2,450

-1,320

+1,130

+3.4%

4-Week Total

-

8,890

-

-4,520

+4,370

+14.0%

According to Mixpanel's product analytics research, B2B SaaS products with WAU/MAU ratios above 50% achieve median annual retention rates of 90-95%, while products below 30% WAU/MAU ratios experience 60-70% retention, demonstrating the strong correlation between weekly engagement consistency and long-term customer retention.

Related Terms

  • Monthly Active Users (MAU): Monthly engagement metric providing broader timeframe measurement, with WAU offering more granular trend detection

  • Daily Active Users (DAU): Daily engagement metric showing highest granularity but more volatility than WAU for B2B products

  • Product Engagement Score: Composite metric incorporating WAU alongside other engagement dimensions like feature adoption and session depth

  • Customer Health Score: Overall account health assessment often incorporating WAU trends as a key behavioral component

  • Activation Milestone: Critical product actions indicating value realization, with sustained WAU confirming successful activation

  • Product-Led Growth (PLG): Go-to-market strategy where WAU serves as a primary growth and retention indicator

  • Churn Prediction: Analytical approach using declining WAU patterns as early warning signals for potential cancellations

  • Feature Adoption Rate: Metric measuring specific capability usage, enhanced by tracking feature-specific WAU segments

Frequently Asked Questions

What is WAU (Weekly Active Users)?

Quick Answer: WAU (Weekly Active Users) counts the number of unique users who perform meaningful actions within your product during a seven-day period, measuring actual engagement rather than account status or simple logins.

WAU serves as a critical product health metric that reveals how many users actively derive value from your product each week. Unlike vanity metrics such as total registered accounts or cumulative signups, WAU measures behavioral engagement through actions that demonstrate core value realization—creating content, analyzing data, collaborating with teammates, or completing key workflows specific to your product's value proposition. This focus on active usage rather than passive access makes WAU a strong predictor of retention, expansion opportunities, and overall product-market fit.

How do you calculate WAU?

Quick Answer: Calculate WAU by counting distinct users who performed at least one qualifying activity during a seven-day period. Use rolling windows (count previous 7 days from any date) or calendar weeks (Monday-Sunday) depending on reporting needs.

The calculation requires three components: defining what constitutes "active" behavior for your product, implementing tracking to capture these activities with user IDs and timestamps, and querying your analytics database for unique user counts within seven-day windows. Most product analytics platforms like Amplitude, Mixpanel, or Heap provide built-in WAU calculations once you configure event tracking. For manual calculation, use SQL queries like: SELECT COUNT(DISTINCT user_id) FROM events WHERE event_date >= CURRENT_DATE - 7 AND activity_type IN ('qualifying_actions'). Ensure you track unique users, not total activities—a user who completes 50 actions in one week still counts as one active user.

What is a good WAU/MAU ratio?

Quick Answer: A WAU/MAU ratio above 50% indicates strong weekly engagement habits for B2B SaaS products, while ratios below 30% suggest sporadic usage and higher churn risk. Optimal ratios vary by product type and usage patterns.

The WAU/MAU ratio reveals engagement consistency by showing what percentage of monthly users engage weekly. Products designed for daily or weekly use (project management, communication tools, CRMs) should target 50-70% WAU/MAU ratios, indicating most monthly users engage multiple weeks per month. Products with natural monthly rhythms (billing software, monthly reporting tools) may function well at 30-50% ratios. Consumer social apps often achieve 70-80%+ ratios reflecting daily usage habits, while B2B tools typically range 40-60%. Low ratios below 30% suggest users check in monthly but don't form weekly habits, indicating weak product stickiness and elevated churn risk requiring activation improvements or product strategy adjustments.

Why measure WAU instead of MAU or DAU?

WAU provides optimal granularity for most B2B SaaS products by capturing meaningful trends without excessive volatility. MAU masks declining engagement—a user might engage heavily in week one then disappear for three weeks while still counting as an active monthly user, hiding the disengagement pattern. Conversely, DAU shows high day-to-day fluctuation as B2B users naturally skip weekends and take vacations, creating noise that obscures true trends. Weekly measurement aligns with business rhythms where most professional workflows operate on Monday-Friday cycles, making WAU naturally suited to B2B usage patterns. Additionally, weekly windows provide sufficient data points for trend analysis while enabling faster feedback cycles than monthly metrics—teams can identify and respond to engagement changes in weeks rather than waiting for full month closures.

How do you use WAU to predict churn?

Use declining WAU patterns as early warning signals for potential churn by monitoring account-level WAU trends compared to historical baselines. When an account's WAU drops significantly below their 90-day average (typically 20-40% declines over 2-3 consecutive weeks), flag them for customer success intervention. Combine WAU decline with other signals like decreased feature breadth (users engaging with fewer capabilities), shortened session durations, or reduced seat utilization (lower percentage of purchased seats active weekly). Build predictive churn models using WAU trajectory as a primary input—machine learning approaches that incorporate week-over-week WAU changes, WAU/MAU ratio trends, and feature-specific WAU patterns often predict churn 30-60 days in advance with 70-85% accuracy. This early detection enables proactive retention actions before customers make cancellation decisions, significantly improving save rates compared to reactive post-cancellation approaches.

Conclusion

WAU (Weekly Active Users) represents one of the most actionable metrics for B2B SaaS product teams, customer success organizations, and growth leaders focused on measuring and improving product engagement. By tracking how many users actively derive value from your product each week, WAU provides a granular, timely view of product health that enables proactive decision-making around retention, expansion, and product development priorities.

Product teams use WAU trends and feature-specific WAU analysis to validate product roadmap decisions, prioritizing capabilities that drive consistent weekly engagement while deprecating underutilized features that consume development resources without improving retention. Customer success teams leverage account-level WAU monitoring to identify disengagement patterns early, triggering interventions weeks or months before churn risk materializes in support tickets or cancellation requests. Growth teams treat WAU as a North Star metric that reflects actual product value delivery rather than vanity metrics like total signups, optimizing acquisition channels and onboarding experiences based on their impact on sustained weekly engagement.

As product-led growth strategies dominate modern B2B SaaS go-to-market approaches, WAU will continue growing in strategic importance as the primary measure of product-market fit, engagement quality, and retention predictability. Companies that instrument comprehensive WAU tracking across user segments, features, and cohorts create competitive advantages through faster feedback cycles, more accurate retention forecasting, and better alignment between product investment and customer value delivery. Understanding WAU calculation, interpretation, and application helps teams shift from revenue-lagging indicators toward leading behavioral metrics that predict and drive sustainable growth. Explore product engagement and product-led growth strategies to maximize the value of weekly engagement data in your product operations.

Last Updated: January 18, 2026