Retention Analytics: Retention analytics for stopping churn in its tracks
Get actionable retention analytics that show you how to prevent churn and grow your base of loyal users. Drive retention throughout the user lifecycle.
Retention analytics helps you:
- Discover the behaviors and factors that separate retained users from churned ones
- Find your ‘a-ha’ moments and understand which features impact retention with Amplitude Compass
- Get actionable insights that help you make better product and marketing decisions
What is retention, and why is it king?
Retention is a measure of how many users return to your app or website over time. There are a few different ways to compute it, but the most common is ‘N-Day’: the percentage of users who come back on a specific day after their first use. Improving your retention rate is critical for your product’s growth.
Increasing user retention and preventing churn is by far the most important thing you can do to build a sustainable user base and drive growth. It trumps other factors like new user acquisition and virality in how much it can impact your monthly active users.
"Amplitude has helped us understand our users, and that’s helped form a lot of our product decisions around how to increase retention."
TRENTON HUEY, Head of Analytics, Life360
Filling the top of the funnel doesn’t matter if your users are not sticking around long term, and retention has the potential to impact all of your important metrics: engagement, lifetime value, payback period, and more.
Today’s consumers are inundated with apps — the average app loses over 80% of its users within the first 3 days. It’s important to show your users value early and often so that they create a habit of using your app and become loyal, engaged users.
The Retention Lifecycle
Although most teams focus on new user retention, it’s not the whole story. It’s important to keep track of your retention across 3 phases of the lifecycle:
- NEW USERS
- CURRENT USERS
- RESURRECTED USERS
If you neglect any of these phases, you’re missing out on major opportunities to improve overall growth. Amplitude makes it easy for you analyze the entire user lifecycle.
Customize your retention analytics
Every product is different — so why would you measure retention the same way? While daily usage is important for a social game, the same cannot be said for a food delivery app — you might only expect people to order food once or twice a month.
N day retention
N day retention tells you what percentage of users come back on a specific day.
Example: Day 7 retention = percentage of users who came back exactly on Day 7.
Unbounded retention shows you what percentage of users come back on a specific day or later. You can also think of unbounded retention as the opposite of your churn rate.
Example: Day 7 retention = percentage of users who came back on Day 7, or any day after that.
Bracket retention allows you to define any time brackets that you want, from a single day/week/month to multiple days/weeks/months.
Example: You could set your 1st bracket as Day 0, your 2nd bracket at Day 1-7, and your 3rd bracket as Day 8-14. Amplitude will measure the percentage of users that return during each bracket.
You need to be able to choose a retention definition that accurately reflects the health of your product. While most analytics tools only provide ‘N day’ (did users come back exactly 7 days later?), Amplitude allows you to define retention the way that makes sense for your business.
Calm increased new user retention 3x
Calm, a meditation mobile app, used behavioral cohorting to understand the impact of setting Daily Reminders. They discovered that users who set Daily Reminders were 3x more likely to be retained than other users. As a result, Calm started prompting all new users to set a Daily Reminder after their first meditation session, resulting in far more users setting reminders, and higher mobile app retention rates.
How to analyze and improve retention with Amplitude
Facebook found that new users who added 7 friends within 10 days were far more likely to retain long term — and they used that finding to optimize the early user experience around adding friends. To focus your team around such a "north star" metric, you need to discover your own ‘a-ha’ moments.
Amplitude Compass shows you the early user behaviors that best predict whether a user will be retained later on — in other words, it automatically finds potential ‘a-ha’ moments for you. By discovering these behaviors, you can develop user retention techniques that improve the new user experience, hook more users early on, and get more loyal, long-term users.
Use behavioral cohort analysis to understand which behaviors drive website and app retention
Other analytics platforms can show you that your churn rate is high — but they can’t help you figure out how to fix it like Amplitude does. To stop losing users, you need to understand the difference between users who retain, and those who don’t.
Behavioral cohort analysis enables you to measure how different user behaviors impact churn by giving you the ability to group users based on actions they have or have not taken in your product.
From retention analysis to user retention strategies
Most analytics platforms allow you to measure retention, but they don’t help you figure out how to improve it. Retention reports from Amplitude are actionable — they show you which features are having a positive (or negative) impact and what behaviors or factors retained users have in common. Like Calm and QuizUp, you can leverage these insights to improve the user experience and nudge more users to keep coming back.
Inform your retention marketing efforts
There are two main avenues to prevent churn:
- Product changes (e.g. improving an onboarding flow)
- Marketing (ex. sending a campaign to re-engage inactive users).
By using Amplitude to understand how user behaviors affect engagement, your team can craft more targeted, effective tactics. Learn which features to encourage new users to try, when to send push notifications, and which winback campaigns are most effective for long-term user loyalty.