How to calculate DAU/MAU ratio in Amplitude
DAU/MAU ratio is a popular metric for measuring products. But how do you actually calculate it in your analytics tool? And what do you need to be aware of when doing so?
What is DAU/MAU ratio?
DAU/MAU ratio is simply the ratio of a product’s Daily Active Users (DAU) and its Monthly Active Users (MAU).
Because every DAU is also a MAU, the ratio will be a number between 0 and 1, often referred to as a percentage (0%–100%).
Imagine a product with only 20 users but they are all very loyal users. If all of those users are active every day of a month, then each day will have a DAU of 20, and the overall MAU of the month will also be 20 (i.e. 20 unique users). So it has a perfect DAU/MAU ratio of 100%. Well done that product (maybe try to get some more users if you’re so good? …).
Conversely, imagine a product that gets 10 new users each day, who each only ever use the product once. The DAU each day will be 10, but the MAU will be around 300 (30 days of 10 users). That would give a DAU/MAU ratio of 3%.
How to create a DAU/MAU ratio chart in Amplitude
It’s really easy to create the DAU/MAU chart once you know how, but impossible to find otherwise!
Here are the steps:
- Create a new event segmentation chart
- Select Any Active Event as the first event. This is the only event we need for now
- Select the formula tab, and enter the following formula: UNIQUES(A)/ROLLWIN(UNIQUES, A, 30)
That’s it! Each day shown on the chart is that day’s DAU/MAU ratio. You might like to calculate the average to put into your pitch deck … more on that later! …
Common Pitfalls
There are a few traps you can easily fall into when measuring DAU/MAU ratio, which will really affect your result.
Active Events
With the above approach, we rely on the Amplitude definition of an active event. Fortunately for you, you can customize which events are considered active.
For example, if some of your tracking events are things not done by a user like “Email:Sent” or “Subscription:Renewed” you should probably make these inactive.
To do so, go to governance, and then toggle the dropdown in the active column for each relevant event (by default they are all set to active).
Similarly, you might have your own business definition of what constitutes an active user (for example, completing some key action like visiting their dashboard or watching a video). In that case, change the chart Any Active Event to the event of your choosing.
User Segments
A secondary consideration is which group of users you want to consider.
For a free social app, this might be all installs or registered users.
For a SaaS product or a consumer subscription service, you’re likely most interested in users with an active subscription.
For an app built for a specific user segment, you might also want to filter to only include your target audience (e.g. by user age). Similarly if you have several roles in your product (e.g. teacher and student for a classroom app) you might want to create separate charts or segments for each role.
Below I’ve set up separate segments for all users and paying users. You can see they have drastically different DAU/MAU ratios!
What is a good DAU/MAU Ratio?
Okay, so you’ve measured your DAU/MAU ratio, but is it good?
As with many metrics, benchmarking is hard. It depends on your market. If users visiting repeatedly each day is important for your business model, maybe you would like to have a ratio of over 20%. Facebook reportedly had a ratio over 50% for many years.
However, many products can survive with single but impactful visits — many e-commerce stores for example. Sure they’d like users to come back and buy more, but they’d settle for a ratio below 5% as long as their conversion rates and cost per visit are good.
Ultimately, I think the most informative thing to do with your DAU/MAU is to watch it change over time, as you make improvements to your product or the way you acquire users.
Improvements and Variants
Rolling Average
The DAU/MAU chart above can be quite bumpy because many products will have a varying influx of new users contributing to the DAU. You can actually smooth the ratio directly in Amplitude by calculating a rolling average for DAU using the formula:
ROLLAVG(UNIQUES, A, 30)/ROLLWIN(UNIQUES, A, 30)ROLLAVG(UNIQUES, A, 30)/ROLLWIN(UNIQUES, A, 30)
Segment Slices
It can be interesting to dig into your DAU/MAU ratio within your own user base. For example, grouping your users by their country:
Many other segmentations are possible and you can explore the user properties you have available in your Amplitude implementation.
DAU/MAU vs other User Retention Metrics
DAU/MAU is just one way to measure user retention. Amplitude has a suite of (in my opinion) more powerful retention charts, which can give deeper insights into your product.
Want more help with Amplitude?
Through my agency Permutable, I help companies get more out of their analytics setup, interpret the data, and make decisions that lead to growth.
I’m also currently planning a new online live training course — sign up here if you’re interested.
