User stickiness tells you who's coming back. If your DAU is climbing but your MAU is flat, you've got a stickiness problem—users try your product once and ghost. Amplitude's Retention analysis shows you exactly which user segments stick around and which ones churn, so you can double down on what keeps people engaged.
Stickiness as a Retention Metric
Stickiness is fundamentally about frequency. It answers: how often do your users return after their first action?
Understand DAU/MAU and D1 Retention
The two most common stickiness metrics are DAU/MAU ratio (Daily Active Users ÷ Monthly Active Users, typically 0–100%) and Day 1 retention (the % of new users who come back the next day). DAU/MAU tells you what fraction of your monthly audience is active on any given day; D1 retention shows early survival. In Amplitude, you track this through the Retention chart, which answers: "Of the cohort that took [action X] on day 0, what % returned on day 1, day 7, day 30?"
// Track an event that signals engagement (e.g., a feature usage)
amplitude.track('Feature_Used', {
'feature_name': 'dashboard',
'user_tier': 'pro'
});
// Or with the new SDK:
import * as amplitude from '@amplitude/analytics-browser';
amplitude.track({
event_type: 'Feature_Used',
event_properties: {
feature_name: 'dashboard',
user_tier: 'pro'
}
});Measuring Stickiness with Retention Analysis
Amplitude's Retention chart is built for stickiness analysis. It shows you cohort behavior over time with zero custom SQL.
Set up a Retention cohort in Amplitude
Go to Analyze > Retention and create a cohort. Define your returning action—the event that signals engagement (e.g., 'Session_Start' or 'Report_Generated'). Amplitude will show you what % of users who took that action on day 0 repeated it by day 1, day 7, day 30, etc. You can also segment by user properties (e.g., 'pro' users vs. free users) to compare stickiness across tiers.
// Set user properties that Amplitude can segment on
amplitude.setUserProperties({
'subscription_tier': 'pro',
'signup_source': 'organic',
'days_since_signup': 15
});
// The Retention chart will use these properties to split cohorts
amplitude.track('Report_Generated', {
'report_type': 'monthly_summary'
});Interpret the Retention curve
A steep drop-off after day 1 means poor early stickiness (new users aren't returning). A flat curve after day 7 means you've retained a stable 'core' audience. Look for inflection points—if stickiness tanks on day 3, investigate what happens on day 3 (onboarding ends? first bill? feature limit hit?). In Amplitude, you can click any day to see the actual counts and use Segment to drill into cohorts (e.g., 'free users on iOS').
// Track events at key moments to identify stickiness drop-off points
amplitude.track('Onboarding_Completed', {
'duration_minutes': 12,
'steps_skipped': 2
});
amplitude.track('First_Feature_Used', {
'feature_name': 'custom_report',
'time_to_first_use_hours': 3
});
amplitude.track('Billing_Page_Visited', {
'conversion_result': 'viewed'
});Acting on Stickiness Insights
Once you know where stickiness breaks, you need to act on it. Amplitude lets you build cohorts from retention data and message those users.
Create a cohort of at-risk users
In Amplitude, go to Cohorts > Create and build a cohort with a rule like: "Users who took [action] 8+ days ago and have not taken [action] in the last 2 days." This captures users who were active but dropped off—your churn risk. You can export this cohort to your email or product messaging tool to re-engage them.
// Use Amplitude's REST API to fetch users in a cohort
const cohortId = 'your-at-risk-cohort-id';
const response = await fetch(
`https://api.amplitude.com/api/2/cohort/${cohortId}/members`,
{
headers: {
'Authorization': `Bearer ${amplitudeApiToken}`
}
}
);
const atRiskUsers = await response.json();
// Send these user IDs to your email platform or in-app messaging systemCompare stickiness across segments
Build retention curves for different cohorts side-by-side. Create a retention chart for 'Pro users' and overlay 'Free users.' If pro users have 60% D7 retention and free users have 20%, you have a pricing or feature-fit problem. In Amplitude, use the Segment dropdown to split by user properties like plan or signup_source.
// Amplitude segments retention automatically based on user properties
// No code needed—just set this property:
amplitude.setUserProperties({
'plan': 'pro' // or 'free', 'starter', etc.
});
// Then in the UI: Analyze > Retention > Segment by 'plan'
// Amplitude will show separate curves for each planCommon Pitfalls
- Confusing daily active users (DAU) with stickiness. High DAU doesn't mean high stickiness if your MAU is also growing—you might just be acquiring faster than you're retaining.
- Tracking the wrong returning action. If you measure stickiness by 'Login' but users benefit most from 'Report_Shared', you'll build retention plans around the wrong behavior.
- Ignoring cohort size. A 90% retention curve for a 5-person cohort is noise. Always check the N in Amplitude's Retention chart—small cohorts are unreliable.
- Not accounting for platform differences. Mobile users might have lower D1 retention than web simply because they forget to open the app. Segment by platform in Amplitude to measure fairly.
Wrapping Up
User stickiness is the heartbeat of a healthy product—it tells you if you're building something people need or just something they try once. Amplitude's Retention analysis strips away guesswork; you see exactly which segments come back and which ones don't. Start with D1 and D7 retention, identify your drop-off points, and build retention experiments around them. If you want to track stickiness automatically and sync insights across your whole analytics stack, Product Analyst can help.