Understanding Retention Analysis

Understanding user behavior goes beyond how users discover and start using your product. It is just as important how they continue to engage with it over time. This is where retention analysis comes into play. The Umami Retention report can be a part of this process, highlighting both short-term and long-term user engagement, which you can then match to marketing campaigns, product announcements, feature launches, social media posts, etc, to see what impacts retention.

The Umami Retention report, one in a suite of product analytics reports, allows teams to visualize and analyze user retention patterns. It shows how often users return to your website or product, helping you understand short-term and long-term engagement trends and identify opportunities to produce better outcomes.

Retention Report Key Features

Before we jump into specific use cases, let's look at some key features of the Retention report:

1. Cohort Analysis: The report uses cohort analysis to group users based on when they visited your site. This lets you track how engagement changes for different user groups over time. For example, if you launched a new feature on June 15, you can follow that specific cohort of users over the next however many days to see what impact the new feature has on retention.

2. Daily Visitor Tracking: The Retention report is based on a daily cohort of users.

3. Return Visit Insights: You can see how often those users return on specific days following their initial visit, showing your product's "stickiness."

4. Flexible Time Frame: You can analyze retention for any specific month and year to compare retention rates across different periods or seasons.

5. Visual Representation: The data is presented in a cohort chart, making it simple to identify trends and patterns at a glance.

For a walk-through on how to setup a Retention report, please refer to our docs.

Retention Report Use Cases

Use Case Example: Analyzing the Impact of Onboarding Improvements

Product teams often invest significant resources in improving the onboarding process, aiming to increase user engagement and retention. The Retention report can help you measure the effectiveness of these efforts.

Setup

1. Identify the date when you implemented the onboarding changes.

2. Create Retention reports for the month before and the month after the changes.

3. Compare the retention patterns between these two periods.

Analysis Approach

Once you've set up these reports, you can analyze the data in several ways:

1. Compare the Day 1 retention rates (users who return the day after their first visit) before and after the changes. An increase in Day 1 retention could indicate that your new onboarding process is more engaging.

2. Look at longer-term retention (e.g., Day 7, Day 14, Day 30) to see if the improvements have a lasting impact. Are users sticking around longer after the onboarding changes?

3. Analyze retention patterns for different user segments to see if the new onboarding process is more effective for specific users.

4. If you see improved retention, consider running A/B tests with further onboarding tweaks to continue optimizing the process.

Using the Retention report in this way can help you quantify the impact of your onboarding improvements and guide further optimization efforts.

Use Case Example: Evaluating Feature Launches

When launching new features, you need to know the initial adoption and how these features impact long-term user engagement. The Retention report can help.

Setup

1. Identify the launch date of a new feature.

2. Create Retention reports for the month before, the month of, and the month after the launch.

3. Compare retention patterns across these three periods.

Analysis Approach

With these reports in place, you can:

1. Look for changes in overall retention rates following the feature launch. An increase could indicate that the new feature is driving more frequent usage.

2. Analyze how quickly retention rates change after the launch. A rapid improvement might suggest high user excitement about the new feature. Follow up with marketing to see if they are hearing any positive feedback on social channels, or customer support to see if there is any positive feedback, etc.

3. Examine long-term retention trends (e.g., 2-3 months post-launch) to see if the feature has a lasting impact on user engagement.

4. Segment users based on whether they've used the new feature. Compare retention rates between users who have and have not engaged with the feature to better understand its impact.

5. Use these insights to inform decisions about future feature development and resource allocation. I.E., this data can help you determine your product roadmap.

This approach can help you understand the true impact of new features on user engagement beyond initial adoption metrics.

Use Case Example: Seasonal Trend Analysis

Many products experience seasonal fluctuations in user behavior. Understanding these patterns can help you more effectively plan product updates, marketing campaigns, and resource allocation.

Setup

1. Generate Retention reports for each month of the year.

2. Compare retention patterns across different seasons or specific periods (e.g., holidays, academic semesters, fiscal quarters).

Analysis Approach

With this data, you can:

1. Identify periods of naturally high or low retention. This can help you set more accurate retention goals for different times of the year.

2. Look for consistent patterns year over year. Do you see a dip in retention during the summer months or a spike during the holiday season?

3. Analyze how different cohorts behave during these seasonal changes. Do users who join during high-retention periods tend to stick around longer?

4. Use these insights to plan product updates or marketing campaigns. For example, you might focus on re-engagement campaigns during typically low-retention periods.

5. Compare your seasonal retention patterns with overall usage metrics to understand how seasonality affects your product.

This analysis can help you anticipate and plan for seasonal changes in user behavior, allowing you to optimize your product strategy throughout the year.

Combining Retention Insights with Other Umami Reports

The data gleaned from the Retention report can be a starting point and other Umami reports can help you double-click into the data. Here are a few ways to combine insights from the Retention report with other Umami reports:

Retention + Funnel Report: Use the Funnel report to identify high-impact user actions, such as making a purchase or completing a tutorial, then use the Retention report to see if users who complete these actions have higher long-term retention rates.

Retention + Goals Report: Set retention-based goals in the Goals report (e.g., "X% of users return within seven days"), and use the Retention report to track progress towards these goals over time.

Retention + Journey Report: The Journey report allows you to analyze user paths with 3 to 7 steps, providing insights into how users navigate your product. Use this report to identify the most common paths of highly retained users, then use the Retention report to analyze if optimizing these paths leads to improved long-term engagement for other user segments.

Retention + Journey Report for Feature Discovery: Use the Journey report to understand how users discover and engage with key features. Then, the retention report to see if users who find and use these features have higher retention rates. This combo can help you prioritize which features to promote or optimize for better long-term engagement.

Leveraging multiple Umami reports allows you to understand your product's performance and user behavior patterns. The Journey report's ability to visualize complex user paths complements the Retention report's focus on long-term engagement, allowing you to connect specific user behaviors with retention outcomes.

The Umami Retention report can help product analytics teams looking for a deeper understanding of user engagement over time via visualizations of cohort-based patterns, it enables teams to:

1. Measure the impact of product changes and feature launches on both short-term and long-term engagement.

2. Identify seasonal trends.

3. Set data-driven retention goals and track progress over time.

4. Optimize onboarding and other critical user journeys.

5. Complement insights from other reports like Journey, Funnel, and Goals for a comprehensive view of user behavior.

These are of course just a few key examples that will hopefully get the ideas flowing. Because the Retention report is date-based, you can match the dates to pretty much anything your company is doing on the product, marketing, sales, UI/UX, design, etc, side.

Reviewing your Retention reports and other Umami reports can provide continual insights to drive product improvements and boost user engagement.

What’s great about Umami is it can run alongside your existing analytics tools and can act as a second-source of data to help you confirm what you are seeing from other tools.

Like all Umami reports, the Retention report comes standard with all Umami plans. If you have any questions about using the Retention report or want to discuss how to get the most out of your Umami analytics suite, including how to combine insights from the Retention and Journey reports (or any other report for that matter), don't hesitate to reach out to our support team at [email protected].