Iterate AI
Dec 9, 2024
For product managers working on web and mobile apps, tracking user activity is non-negotiable.
Why?
Tracking MAU isn’t just about having a number on a dashboard; it’s about using it to understand user behavior, and driving meaningful product decisions.
MAU (Monthly Active Users) shows how many users are engaging with your product. It reflects how well your product is fulfilling user needs consistently over time.
This blog dives into the specifics of MAU: what it is, how to measure it, and steps to improve it using data.
What is MAU and Why Does It Matter?
MAU refers to the unique number of users who interact with your app within a 30-day period or every month.
“Interaction” could mean anything in your product context. It could be logging in to completing a key action such as booking a call or making a purchase. It is important to define what is considered as an ‘interaction’ for your product.
For web and mobile apps, MAU matters because it tracks growth, engagement and potential.
For example:
A fitness app may define MAU as users who book at least one workout.
For a SaaS tool it can be users completing a specific task like uploading a file.
Product managers need to define what ‘active users’ and ‘inactive users’ are. This helps them put a meaning and story to the MAU numbers.
How to Measure MAU for Web and Mobile Apps
Measuring MAU requires an analytics setup. Here’s how product managers can configure it:
Set up analytics and define “Active” for your product
Figure out the best tools for your product, such as Mixpanel, Amplitude, etc.
Decide what qualifies as an activity based on your product’s value proposition. For instance:
Web App: Active users might be those who log in and view a dashboard.
Mobile App: Active users might include those who perform a key in-app action, like sending a message or completing a game level.
Track events
Implement event-based tracking to capture user interactions. For example:
Track events like “session_start,” “purchase_complete,” or “form_submission.”
Use unique user IDs and proper labeling to differentiate users across sessions and devices.
Avoid double-counting or duplicates
Ensure unique users are only counted once, even if they interact across multiple devices. Analytics tools usually handle this by using user IDs or cookies.
💡 Use IterateAI to set up analytics
PMs can use IterateAI’s extension to create a list of events to track. IterateAI creates the code and your developer only has to review it, and PMs can implement and track themselves. Using IterateAI reduces dependency on developers and allows PMs to implement product analytics quickly.
How Product Managers Use MAU to Drive Decisions
Here are three ways PMs can use MAU:
Feature prioritization
MAU trends often guide product roadmaps. For example:
If MAU drops after a feature launch, it might indicate a usability issue.
Conversely, a spike in MAU could validate the success of a recent update.
Retention analysis
Combine MAU with retention metrics such as churn rate, customer lifetime value, repeat purchase, etc. to understand how many users stick around.
MAU can also indicate seasonal user behaviour and how engaging their product is. Product managers can then target specific cohorts with personalized push notifications or improved onboarding experiences for better retention.
Behavior segmentation
Segment MAU data by:
Geography: Are users in specific regions more active?
Device: Are mobile users more engaged than desktop users?
Actions: Which features drive the most activity?
For example, if mobile app users who use a particular feature daily contribute significantly to MAU, you might double down on optimizing that feature.
To Remember When Measuring MAU
Here are two things to consider:
Tracking MAU across platforms
For web and mobile apps, users often switch between devices. You can use tools such as Twilio Segment to unify data from different platforms to avoid inconsistencies.
Over-reliance on MAU
While MAU is valuable, it can be misleading when used in isolation. For instance:
High MAU but low daily active users (DAU) may indicate shallow engagement.
A flat MAU might hide churn if new users are replacing those who drop off.
How to Improve MAU: Actionable Tips for Product Managers
Here are four tips:
Short onboarding flow
Simplify sign-up processes.
Use analytics to identify drop-off points and fix them.
Show value upfront in the onboarding to excite users
Optimize for recurring engagement
Send personalized reminders via email or push notifications.
Use gamification (e.g., streaks, badges) to motivate users.
Refine key features
Regularly review feature usage metrics.
Invest in improving underperforming features or sunsetting unnecessary ones.
Leverage feedback loops
Use in-app surveys or Net Promoter Score (NPS) tools to understand what keeps users coming back.
Act on feedback quickly to show responsiveness.
MAU Usage for PMs - An Example
Imagine a productivity app noticed a flat MAU trend despite growing downloads.
Solution:
Set up cohort analysis using Mixpanel or Amplitude to identify user drop-off.
Found that users failed to engage after onboarding due to unclear feature benefits.
Revamped onboarding with tutorials and added push notifications for new features.
Set up analytics without wasting developer time
MAU isn’t just a number; it’s a story about your users and their relationship with your product. Set up any analytics tool for your product using Iterate AI, and check MAU, DAU and other crucial metrics. Yes, you don’t need your devs to spend time setting up the analytics tool. Schedule a demo today to learn more.