MAU = # of unique active users in a month

 

For you to correctly measure MAU, it’s important to define what an “active user” is for your service.
 
You can also measure Daily Active User (DAU) using similar data. These two metrics are essential if you want to calculate the stickiness of your service.
 
Keep in mind that "good MAU" rates for B2C apps or software show a higher range of MAU than B2B.
 
For this template, we will be using the database we created for the fake B2B SaaS startup, Awesome Company. We will be considering those who logged into our service this month as active users.
 
On Outcode, you can create a Monthly Active Users Databoard in under 10 minutes.  

Sample MySQL database

 
This is what Awesome Company's MySQL database looks like.
 

To track your MAU, you need the following data:

• log-in date
• user id
   

How to calculate the MAU in SQL

Let’s say we want to find the MAU for April 2022. We need to have user_id and the created_atcolumns from the login_history table to calculate the MAU. You can easily copy and paste the query below to find your own.
 
You can also create your own Databoard and share it with your team.

SELECT DATE_FORMAT(created_at, "%Y %M") AS MONTH,
    COUNT(user_id) AS MAU
FROM login_history
GROUP BY DATE_FORMAT(created_at, "%Y %M")
ORDER BY DATE_FORMAT(created_at, "%Y %M") desc

 
Do you have a better way to find MAU? Please reply below and inspire the fellow Outcoders!
 

Want to do more with your data?

• It is important to analyze your business deeper, beyond this MAU metric. Try finding Daily Active User and combine the two metrics to find the ratio between the two.
• Check out our templates and see how you can use your data here.
   

Share and automate

Outcode helps you to track measures in real-time with the Databoard.

• Share your Databoard or data table with other team members. Copy and paste the page URL anywhere you like.
• Get your real-time MAU sent via Slack or email with Outcode's quick automation feature.