Available for the following Plan types:
*with the following add-on:
FullStory for Mobile Apps
Available to the following User roles:
What is Retention?
Retention charting visualizes user engagement by tracking the number of users that return to a specific event after another over time.
The Value of Retention
By running this type of analysis, you can understand how many users are returning to your product to ensure they are engaged, active, and finding enough value within the app to drive recurring usage. Retaining users has a direct positive effect on overall user counts, lifetime value, and other crucial product and business metrics.
Retention provides answers to what keeps your users coming back and why, without any gaps in your data or the need to set up tracking.
An event is referred to as a specific action a user takes. When building a retention analysis, you select any starting event and any returning event. In other words, users in my digital experience did X event then returned to do Y event.
Retention data is computed based on the events (and time frame) selected. Meaning, it compares the date of the starting event to the date of the return event specified.
The Starting Event is the first specific action a user takes in your analysis. You can choose any indexed event in FullStory in the drop down and refine the event with dependent criteria, or you can use the default event Any Activity, which tells FullStory to consider any event as the starting event.
The Return Event is the specific or meaningful action a user comes back to do in your analysis. You can choose any indexed event, refine the event by dependent criteria, or use Any Activity as well. You can choose one starting and up to two returning events in your chart configuration. Two return events allow for comparison purposes. You can also refine either event for a more granular event search.
Retention Display configures the percentage of active users who’ve engaged your selected events within a specified daily, weekly, or monthly frequency. More simply put, it shows how much time has gone by between a user completing the returning event.
On: A user has a returning event on an exact time scale. Meaning, in order for a user to be charted as an N-day user, the user has to specifically return on N-Day.
- Put another way, On means that a customer came back on an exact day in the chart.
On or After: A user has a returning event on an exact time unit or anytime afterwards. Meaning, a user was retained within the general time frame you are analyzing.
- Put differently, On or After means that the graph points include any customer that came back on a day or any day after that.
- Time Interval: This is the period of time, either Day, Week, or Month, which users come back and complete the return event.
Configuring a Retention Analysis
At its core, Retention measures the amount of time between two different user events. To measure this amount of time, you just need to tell FullStory what those events are.
Step 1: Choose the Starting Event
Select the Starting Event. You can choose any event from the list in the drop down, or you can tell FullStory to consider any activity as the starting event for this analysis, by selecting Any Activity.
If needed, you can refine your events with the specific value you are looking for.
Step 2: Choose the Returning Event
Select your Returning Event(s) and refine it, as needed.
Step 3: Choose your Retention Display
Choose to display the % of users returning On or On or After each day, week, or month.
Based on the Time Interval (e.g. Day, Week, Month), the Time Range will auto-populate based on the display. For example, if the display configuration is set to % of users returning On or After each Week, by default, the time value will be set to Weekly: Past 30 days.
Step 4: Select a Segment, Group By, Compare to past and Time Range (as needed)
- Compare Users: Choose one segment, or compare multiple segments, of users to include in the analysis.
Group by: Choose a property to group your data by, like a browser or device.
- If you group by any given property, the data will display the top 5 properties. If you need to display more than the top 5 properties, an alternative solution would be to filter by a custom segment.
- Compare to past: Visualize the data that is important to you in a Period-Over-Period analysis by using the Compare to past button.
- Time Range: Although the Time Range will be auto-populated, you can customize your time range and override the default setting, if needed.
Note: If you choose multiple segments to compare, the segments are mutually exclusive to “Group by." Meaning, you can have one segment selected and group by a property. But if you select multiple segments, you cannot group by a property.
View Sessions, Add to Home and Dashboards
View and play sessions related to any data point from the retention analysis at the bottom of the page. Watching sessions helps you understand what drives the end-user to return. The first dropdown menu represents Returned by N-Day (given day/week/month time interval). The second dropdown represents the date cohort (cohort of users who completed the return event on a specific n-day).
Hover over any given data point in the retention table and you can “watch sessions” related to that data point. When you click watch sessions, you are scrolled to the Session Playlist which filters to the data point selected (i.e the Returned Time Interval and Date Cohort) in the table.
Lastly, you can also add your chart to a dashboard or home.
Interpreting the Retention Curve and Table
There are two ways to visualize and interpret retention data in FullStory: Retention Curve and Retention Table.
The user retention curve calculates the amount of time between when a user completes the starting event and the return event. Any user who doesn’t complete the starting event, will not surface in the data.
On the x-axis you have the n-day of the user’s return and on the y-axis you have the percentage of users.
Hover over each data point to see different insights, such as:
- The % of users being analyzed
- The exact number of users who completed the starting activity
- The exact number of users who came back and completed the returning event
- The segment being analyzed
It’s important to note that Day 0 in the charts above and below mean users had a return event the same day. It refers to the return event, not the starting event.
The Retention Table is a representation of the same data visualized in the curve chart. To read a retention graph, it’s important to understand that the time-related element (the time interval analyzed) is represented horizontally as well as vertically.
Main Elements of the Retention Table
- Summary (purple): The top horizontal row of the table below is a summary of all users who completed the starting and returning event.
- Date cohorts (orange): These dates represent cohorts of users who completed the starting event on this particular n-day.
- Number of users (pink): The number of users that belong to the corresponding date cohort. It is calculated by the total # of users who completed the starting event on that particular n-day. These users are mutually exclusive to their date.
- Retention Rate (blue): Average percentage of users retained on or after the starting event.
Upside down stairs-shaped table
Each day (or each week/month, depending on the selected granularity), a new user cohort is analyzed. As time progresses, the remaining analysis period automatically decreases, giving the table the inverted stairway shape.
So in this example, the Nov. 17, 22 cohort completed the starting event on the last day of the time interval. We only have Day 0 to look at and do not have visibility into the subsequent days because they are in the future.
How do users show up in both On and On or After in the chart?
In this example, we'll use the day time interval but this applies to any week or month analysis as well.
- Users only show up in one date cohort so that they aren’t measured multiple times across the date constraints. This is shown in the table under Date. It is the vertical row of actual dates.
- When using On you are measuring the exact amount of days between the starting and returning event for a user. The percentage only measures specifically that day. Users can be in more than one n-day percentage unlike the date cohort. For example, below we've selected Any Activity as our event and we see 100% in day 0 followed by 14% on day 1. This means that 14% of people completed a return event on day 1.
- When using On or After, the percentage will measure the exact day and any day after. Meaning, Day 3 retention will also contain users who return on day 4, 5, 6, etc.
Can I run a Retention Analysis for my entire Analytics Retention Period?
Yes! Retention Charting is retroactive.
What does Retention Charting measure compared to other FullStory features (Funnels, Metrics, etc)?
Funnels allow you to see if people are completing key flows, such as an acquisition flow. It answers questions like:
- "Are there any friction points?"
- "Is my account or sign up form working?"
- "Is there something broken?"
- Metrics tell you how to track your engagement events.
- Retention tells you if your users are establishing a habit.
What’s the difference between Retention and Conversion?
Conversion is about completing a key flow. Retention is about users completing an event and returning.
Is bracketed retention offered?
Not at this time.
How do I interpret the color scale on the Retention Table?
The colors/percentages represent how many members of the cohort performed the starting event and then completed a return event.
How are the percentages from the retention table calculated?
FullStory only includes the days (or weeks depending on which range of time you're using) that actually have data for that particular week/day in the percentages from the retention table.