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Event Segmentation Build an event segmentation analysis Choose the right measurement Create in-line custom events Interpret your analysis, part 1 Interpret your analysis, part 2: Advanced features Custom formulas: Syntax and definitions

Funnel Analysis Get the most out of Amplitude's Funnel Analysis chart Build a funnel analysis Interpret your funnel analysis How Amplitude computes funnels How Amplitude computes conversions through funnels How Amplitude handles simultaneous events in a funnel How filters work in a Funnel Analysis chart How Amplitude handles segmenting on a user property in a Funnel Analysis chart A/B testing in a Funnel Analysis chart Combine funnel events inline Compare multiple funnel events in a single step Compare group-by values in your Funnel Analysis chart to each other Hold properties constant in a Funnel Analysis chart Identify conversion drivers in your funnel analyses Mark a step in your funnel as optional

Retention Analysis Build a retention analysis Interpret your retention analysis Build a usage interval analysis Interpret your Retention Analysis chart: Usage interval How the Retention Analysis chart calculates retention How time works in a retention analysis

Data Tables Multi-dimensional analysis with Data Tables Results limits and sorting logic in Data Tables charts Create a metric Use session metrics to evaluate content paths Attribute credit to multiple acquisition touch points

Journeys Understand the paths users take, and why they convert Understand and use the Journeys visualizations

Experiment Results Dig deeper into experimentation data with Experiment Results Using formula metrics in Experiment Results

Revenue LTV Interpret your revenue analysis The Revenue LTV chart: Track how well you're monetizing new users

Compass The Compass chart: discover your users' 'a-ha' moments Find your company's inflection metrics with Compass Interpret your Compass chart, part 1 Interpret your Compass chart, part 2: Correlation and cohorts

Stickiness Stickiness: Identify the features that drive users back to your product Interpret your stickiness analysis

Personas The Personas chart: Find your product's user personas Interpret your Personas chart

Impact Analysis Impact Analysis: How engagement changes user behavior Interpret your Impact Analysis chart

User Sessions User Sessions: Track engagement frequency and duration Interpret your User Sessions chart Marketing metrics recipes

Engagement Matrix Engagement Matrix: see how users feel about your product Interpret your Engagement Matrix

Lifecycle Lifecycle: track the growth of your product's user base Interpret your Lifecycle chart

Other Charts Amplitude SQL: Getting started with Query Amplitude SQL: Table schema and field shortcuts User Composition: View your users by common properties

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Interpret your Retention Analysis chart: Usage interval

This article helps you:

Read a retention analysis
Understand the Retention Analysis chart's usage interval view

In a retention analysis, the usage interval shows the percentage of active users who’ve triggered the selected events with a specified daily, weekly, or monthly median frequency. These events must be triggered on at least two different days in order for the users to be included.

Your usage interval is important for drawing accurate conclusions about your retention numbers. Some products are built to be used daily, while others might be used much less frequently. Knowing how often your product is actually used will help you gauge the health of your product when looking at Retention Analysis and Lifecycle charts.

To view the usage interval, click Usage Interval in the Measured As module.

Screenshot_2023-03-31_at_12.19.15_PM.png

Let's say your product's critical event is Purchase Song or Video. You can select this event and use the usage interval view to find the usage interval for that event. To calculate this, Amplitude plots the distribution of each user's median return period: For each user, Amplitude will look at all Purchase Song or Video events they triggered in the last 15 days, and then determine the median length of time between each of these events.

For example, the highlighted data point tells us that 65.4% of your users have a median interval of four days or fewer between each Purchase Song or Video event. This inflection point can be interpreted as your usage interval. You can use this usage interval to create a Return On (Custom) chart or a Lifecycle chart. In this case, it looks like four days is the expected usage interval for active users with the critical event of Purchase Song or Video.

Note

To learn more about how to find your critical event, check out this blog post.

You can see how the median frequency between events changes over time by selecting the Usage Interval Over Time view. Amplitude does not plot averages in this view; instead, it shows the actual percentages.

For example, the following data point shows us that of the users who triggered Purchase Song or Video on March 10th, 89.1% of them fired it again within seven days.

Screenshot_2023-03-31_at_12.21.42_PM.png

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May 30th, 2024

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