Retention is one of the most important KPIs for any business. It’s a way to measure how many users remain, or “retain”, an app or website over time. This metric is especially important for product founders and CEOs, who want to understand how their product is performing and if it can hold onto its customer base. In this blog post, we’ll explore cohort retention and the two approaches to reporting it. We’ll also look at the tools available to analyze retention through product analytics and how payment data is loaded into those applications.
Defining Active Users for Accurate Retention Measurement
Cohort analysis requires you to define what counts as an active user in order to accurately measure retention. The best way to do this is by using the main user action as an activity event across all platforms and data sources. For example, if your app allows users to send messages or browse profiles, then tracking each of these actions will give you a better understanding of user engagement over time. Additionally, it helps to differentiate between free and paid users because there may be different retention rates for each group depending on your pricing model.
Two Approaches to Reporting Cohort Retention
There are two approaches you can take when measuring and reporting cohort retention – the X-Day (N-Day or Bounded) approach and the Unbounded approach. The X-Day (N-Day or Bounded) approach measures how many users remain after a set period of time – typically 30 days – while the Unbounded approach measures how many users remain after any length of time – 1 day or 1 year – depending on what makes sense for your business model. Both approaches have their advantages and disadvantages which should be taken into consideration when deciding which one works best for your company.
Analyzing Retention Through Product Analytics Tools
Product analytics tools like Mixpanel, KISSmetrics, Heap Analytics, etc., offer powerful insights into how customers interact with your product over time and make it easier to track user behavior across multiple platforms. These tools also make it easier for you to analyze cohorts based on different criteria such as geography, device type, age range etc., allowing you to get granular insights into how each segment behaves differently from another within a given timeframe. Additionally, these tools allow you to load in payment data so that you can understand how well customers are converting from free trials into paying customers as well as track customer lifetime value over time.
Conclusion:
In order to accurately measure cohort retention rates it is essential that you have a clear understanding of what counts as an active user event across multiple channels and platforms as well as clearly define free vs paid users according to your pricing model. There are two approaches that can be used – X-day (N-day or bounded) approach and unbounded approach – both having their own pros and cons that should be taken into consideration when deciding which one works best for your business model. Finally, there are powerful product analytics tools available that allow you to easily track customer behavior across multiple platforms while loading in payment data so that customer lifetime value can be tracked over time helping businesses gauge success more accurately than ever before!
