How to Identify the Churn Risk Factors in Your App

Plus 28 Examples of Churn Factors Across Four Verticals

women_on_appsWe all know that preventing churn is critical to retaining customers and improving your bottom line. Nowhere is this more important today than in your app; a channel built with the primary purpose of keeping users engaged and interacting with you again and again. 

Your customers are driving the evolution of brand interactions based on the experiences they want - and providing value in your app is necessary to meet these evolving expectations.

But it’s still a challenge most organizations face today: how do we define, discover and prevent churn in our business?

After dozens of conversations with data-savvy growth marketers, product analysts, and data scientists, we discovered that the first task to addressing churn is defining what it means for your business. In this post, we outline:

  • A standard definition for churn we’ve seen used with success
  • The factors you need to include in creating your own definition of churn
  • How your business model impacts what to look for in churn factors
  • 48 examples of churn factors in retail, gaming, lifestyle and media apps


First: How do you define churn?

Without first creating a definition of churn as it relates to your app, you cannot start to measure or model it for predicting which users will churn. With the right analytics tracking software in place, you should have access to the insights and factors you need to define churn risks specific to your app.

Any type of churn is often a factor of usage patterns and user attributes. This means looking at how users interact with your app and their behaviors as well as as looking for underlying commonalities in user profiles that can be associated with churn.

Basically, how users behave in your app and the various attributes they bring to the table (such as location, language, purchase history, etc.) both play a role in defining and uncovering reasons for churn. Most likely, you will reach a point in this process in which you have multiple definitions of churn based on these different factors in order to get a broad sense of the many possible risks in your app.

A Baseline Definition for Getting Started

The most effective way to start defining and measuring churn is by having a baseline definition that’s tied to just usage - in this scenario, churn is defined by the absence of any activity in your app. Here’s why this works: if a user simply isn’t using your app, they are at a high risk of churning. Why? Because if a user doesn’t find enough value in your app to actually open it and use it, the odds of engaging and retaining them are substantially lower. Sounds straightforward, right? Well, it actually is.

Definition #1 of Churn = No in-app activity of any kind in 30 consecutive days

This definition indicates that if a user hasn’t returned to your app in a full month then they should be considered a churned customer. We’ve found this to be a commonality across most apps and verticals. In the age of “mobile moments” and increasing app usage, a month is too long of a usage gap.

If you start with this definition as your baseline, you can easily and immediately surface your most at-risk users while you continue to build out advanced definitions and discover the churn factors specific to your app.

How to Create Your Own Definition of Churn

To go beyond basics and create your own definition using the right risk factors, you need to dive deeper into usage and attribute parameters.

There are several parameters that go into defining churn here. They are:

  1. Event(s) that need to be absent in order for churn to occur
    These are the in-app events that are so critical to your growth, revenue or engagement strategy that users who don’t complete them are considered high-risk audiences. For example: if you’re a retail app, prompting in-app purchases is going to be a huge priority, and an event that has a direct impact on your mobile ROI and the lifetime value of the participating users. If that’s the case, a user who is predicted to not perform the purchase event would be at a high risk of churn.

  2. Whether churn is comprised of either one, some or all of these events
    While there may be one in-app event that stands alone as the most impactful, it surely won’t be the only one that matters. When it comes to defining churn for your app, you’ll want to include multiple significant events and their impact on assessing churn. To go back to our previous example, another key event in your retail app might be “item viewed,” as it relates to the purchased item and the user history.

    Then, you have to decide how your definition includes these events, either at the:
    Union: Churn is absence of EITHER item viewed OR purchase event
    or Intersection: Churn is absence of BOTH item viewed AND purchase event

  3. The window of time in consecutive days, weeks or months in which these events need to be absent
    A news app and a travel app are most likely going to have different perspectives when it comes to deciding the amount of time appropriate for signaling churn - while a 15-30 days absence is a huge risk warning for news publishers, in the travel space, it’s more common.

    In keeping with our example, here is what this third parameter might consist of in a retail app: Churn is absence of EITHER item viewed OR purchase events in 30 consecutive days.

Churn definitions are always based on usage, but you can (and should) use these to discover any user attributes that are most related to churn risk. One common attribute that is often related to churn is location. If you don’t provide a localized app experience, it can negatively impact usage behavior, so tracking the user locations that are most related to churn is critical. For example, consider retail apps that are used around the world. You might find by tracking users who had no activity in 30 consecutive days that the top related user attribute is their location, perhaps India - because they’re using the same version of the app that was built for the US. This could reinforced the need to create an experience specific to that user base in order to actively prevent churn.

The Role of Your Business Model in Defining Churn

Just as not all apps have the same usage patterns, not all apps have the same business models. How you monetize your app plays a role in how you define churn, primarily because the intended goals are different. In order to truly benefit from your churn definitions, you’ll want to make sure you take this into consideration.

One common monetization model is the use of ads in-app. In this case, your app is relying heavily on an increased number of ad impressions to boost the click-through rate and results in more ad revenue. In order to get impressions, you need more users in your app more regularly. If you use ads to monetize your app, you might want to include multiple usage events as indicators of churn. Many of these could include how users are interacting with both organic and paid content in the app, for example:

  1. No events of any kind in 30 consecutive days
  2. No content viewed events in 30 consecutive days
  3. No content shared events in 45 consecutive days
  4. No ad clicked events in 15 consecutive days

If you have a subscription service revenue model, however, your churn factors will most likely be different. The events that involve usage patterns with viewing and sharing content will be the same, but instead of ad impressions and ad clicks, you’ll want to track factors related to purchasing or not purchasing a subscription, free trial or limited time offer.

28 Common Churn Factors for Four Verticals

You know your app better than anyone, which means you’re going to be able to pull together a definition of churn that suits the nuances of your app experience, customer base, and mobile strategy.

But that doesn’t mean we can’t give you a place to start. Discovering the elements of churn in your app can take time, so having a jumping off point of common churn factors in your vertical will give you a foundation to grow.

common churn factors by vertical


Next steps: Putting your churn definition into action

Having your churn factors identified and definition in place, you can now open up a world of insights into which of your users are most, somewhat and least likely to churn - and, more importantly, why. By being able to discover the underlying churn risk factors, you can put into place personalized, targeted and hugely effective marketing campaigns that re-engage users before you lose them completely, or optimize the app experience and roadmap to data-informed issues and negate churn risks.

Leading with insights derived from churn data means elevating your mobile strategy from reactive to proactive. No longer will you have to rely on static retention data alone or wonder which of your users you’re going to lose; instead, you have the power and the capacity to cut churn risk off at the pass and improve your app, leading to better ROI, enhanced clarity and happier customers.

Top image courtesy of nenetus at

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