Monthly Active Users (MAU)

Monthly Active Users, often abbreviated as MAU, is a key performance indicator (KPI) that measures the number of unique users who engage with a product or service within a 30-day period. This metric is commonly used in the digital industry, particularly in online platforms, mobile apps, and games, to assess the overall health and growth of the product.

In the context of Statsig, a user is considered a MAU if they trigger any event, gate check, or experiment check within a 28-day period. This definition can be customized based on the specific needs of the business.

Example:

Let's say you have an online game. If a user logs in and plays the game at least once within a 28-day period, they would be considered a MAU. If you have 1000 unique users who do this, your MAU would be 1000.

Additional Context:

Understanding your MAU can help you gauge the stickiness of your product and the loyalty of your user base. For instance, if your MAU is growing, it could indicate that your product is retaining users and possibly attracting new ones. Conversely, a declining MAU might suggest that users are not finding enough value in your product to use it regularly.

In Statsig, the MAU metric is part of the standard set of user accounting metrics, which also includes Daily Active Users (DAU) and Weekly Active Users (WAU). These metrics provide insights into user engagement and can inform growth strategies.

Related Metrics:

  • new_mau_28d: This is the count of users who became a daily active user within the last 28 days.

  • monthly_user_stickiness: This is the fraction of the previous month's users who have been active within the last 28 days. It provides an indication of user retention.

Remember, the exact definition of an active user can vary depending on your business and product. For example, an active user could be defined as someone who logs in, makes a purchase, or browses a feed for more than 20 seconds.

Join the #1 experimentation community

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy