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Active user

Active users refer to the number of unique users who engage with an app or a website during a predefined period of time, and is a metric designed to measure growth, churn, and product stickiness.

What is an active user?

Active users glossary term

As a marketer looking to encourage growth, or a product manager after maximizing retention, you not only need to know how often users access your app/website, but understand the depth of their use and level of engagement.

What do we mean by engagement?

In the app world, the most common example of an active user’s engagement is an account log-in. However, engagement can differ across industries and business models.

An online banking app, for example, could define engagement as making a transfer. An eCommerce app, on the other hand, could define this as adding an item to a cart, whereas a SaaS company could focus on software usage.

Either way, active users are identified through a personal unique identifier, which could be their email, user ID, cookies – when dealing with web users – or a combination of all, in case one fails.

Benefits of measuring active users

calculating active users

An increasing volume of active users is a good sign you’re doing something right.

Determining the number of your active users over time helps you to assess the effectiveness of your campaigns, and the customer experience your app delivers. It also ties into other key metrics; Lifetime value (LTV) can’t be calculated without knowing your retention rates, while retention rates rely on active users count.

In other words, your number of active users provides a basic measure of the general health of your app, and maintaining a finger on the pulse of your active users trends allows you to align their needs with your values.

Common types of active user metrics

As mentioned above, the criteria used to define an active user depends on your line of business and definition of an active user’s engagement. Is your user logging into the app, completing a specific action, or performing a certain number of actions? 

However you choose to define your activity criteria, your active users will be counted over a set period of time, which would fall under one of the following categories:

  • Daily Active Users (DAU)The number of unique users that engage with your app within a 24-hour window. DAU is typically used by businesses where users are expected to interact with the app on a daily basis (e.g. gaming apps).
  • Weekly Active Users (WAU) – The number of unique users that engage with your app within a 7-day window. WAU is typically used by businesses where users are expected to interact with the app at a weekly frequency (e.g. analytics tools).
  • Monthly Active Users (MAU) The number of unique users that engage with your app within a 30-day window. MAU is typically used by B2B apps where users are expected to interact a few times a month or less (eg. banking apps).

Calculating active users

Theoretically speaking, calculating active users could be regarded as deceptively simple, but it can become more complicated depending on how your activity is defined. 

Here are the steps you need to take in order to get started:

  1. Define the criteria for an active user
  2. Define the frequency of engagement you’re looking to measure (DAU, WAU, MAU)
  3. Collect the data using your analytics tool of choice, and sum the number of unique users who meet your active user criteria for each period of time.

Let’s review an example together:

  • Criteria – app user clicked a button, swiped, or scrolled
  • Frequency of engagement – DAU
  • On day X, the following engagements were registered:
    • User 1 clicked a button, and then closed the app
    • User 2 logged into the app but then remained idle
    • User 3 logged into the app, scrolled, swiped, or clicked a button
    • User 1 logged back into the app, and clicked another button
  • Bottom line: Our DAU count adds up to 2. Why?
    • User 1 is an active user (counted once)
    • User 2 is not considered active
    • User 3 is also an active user

Keep in mind that measuring active users heavily depends on the long-term growth goals and business model of your company. 

For example, let’s say the main objective of the UK’s National Health Service is to increase vaccination awareness through their app. The best way for them to measure their active users would be to count the number of unique users that logged into their app.

Uniqlo’s key objective, however, is to get more sales, in which case their active user measurement would be the number of unique users that completed a purchase on their app over a given period.

Different business goals = different active user criteria.

The DAU/MAU ratio – measuring product stickiness

This ratio allows you to measure the relative volume of monthly active users who engage with your app over a 24-hour time period. 

Using the DAU/MAU metric, you can forecast traction and potential revenue over time, but even more importantly – it helps you determine the value of your product for your users by keeping track of how often they return to your app. 

It’s calculated in the following way:

Active user DAU MAU ratio

If, for example, you had 2,000 DAU and 8,000 MAU during the month of August, your stickiness ratio for that month would be 25%. That’s a very happy place to be in, considering that across industries, a stickiness average of 20% is considered good, while 25% and beyond is considered exceptional. 

 Key takeaways

  • In the app world, an active user is most commonly regarded as a user logging into their account. However, the various types of engagement that make up an active user can differ between business sectors and business goals.
  • Determining the number of your active users over time helps you to assess the effectiveness of your campaigns, and the customer experience your app delivers. 
  • Counting your active users over a set period of time can fall into one of the following categories: Daily Active Users (DAU), Weekly Active Users (WAU), and Monthly Active Users (MAU). Different industries and business needs should dictate the ideal frequency for measuring the volume of active users.
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