PostHog Metric
Product Analytics
Feature Stickiness = (Feature DAU / Feature MAU) x 100
Feature stickiness measures the ratio of daily active users to monthly active users for a specific feature, expressed as a percentage. A higher ratio indicates that users who discover a feature return to use it regularly, suggesting it provides ongoing value rather than one-time utility.
Full guide: definition, formula, and benchmarksPostHogProduct AnalyticsFeature Stickiness
Feature stickiness measures the ratio of daily active users to monthly active users for a specific feature, expressed as a percentage. A higher ratio indicates that users who discover a feature return to use it regularly, suggesting it provides ongoing value rather than one-time utility.
How to calculate feature stickiness
Why feature stickiness matters for PostHog users
Adoption tells you how many users tried a feature. Stickiness tells you how many found it valuable enough to keep using. A feature with high adoption but low stickiness attracted curiosity but failed to deliver sustained value - a common pattern with flashy but shallow features.
Mapping stickiness into your metric tree connects habitual feature usage to retention and revenue. Features with high stickiness are typically your product's strongest retention drivers. Correlations confirm which sticky features have the strongest statistical relationship with long-term retention.
Understand and act on feature stickiness with KPI Tree
KPI Tree syncs feature-level DAU and MAU data from your warehouse and calculates stickiness ratios per feature. Position stickiness alongside retention metrics in your product health tree.
Assign RACI ownership to your product lead. Set alerts when stickiness declines for key features and track product changes aimed at deepening habitual usage.
Get started with your PostHog data
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Related PostHog metrics
Feature Adoption Rate
Product AnalyticsMetric Definition
Feature Adoption Rate = (Users Who Used Feature / Total Eligible Users) x 100
Feature adoption rate measures the percentage of eligible users who have used a specific feature within a defined period after its release or their first login. It quantifies how effectively your product introduces users to new and existing capabilities.
Daily Active Users
Product AnalyticsMetric Definition
Daily active users counts the unique users who trigger at least one qualifying event in PostHog within a calendar day. It serves as the foundational measure of product engagement, indicating how many users find enough value in your product to return and use it daily.
Event Frequency Analysis
Product AnalyticsMetric Definition
Event frequency analysis examines how often users trigger specific PostHog events within defined time periods. It reveals usage intensity patterns - distinguishing between casual users who perform an action once and power users who perform it dozens of times - and identifies the frequency thresholds that predict retention.
User Retention Rate
Product AnalyticsMetric Definition
Retention Rate = (Users Active in Period / Users Active in Previous Period) x 100
User retention rate measures the percentage of users who return to your product within a defined period after their first use, based on PostHog event data. It is the inverse of churn and the primary indicator of whether your product delivers sustained value over time.
Session Frequency
Product AnalyticsMetric Definition
Average Session Frequency = Total Sessions / Unique Users (per period)
Session frequency measures how often individual users return to your product within a defined period, based on PostHog session data. It distinguishes between users who visit daily, weekly, or sporadically, revealing the cadence of habitual product usage.
Explore feature stickiness across integrations
All PostHog metrics
A/B Test PerformanceBounce RateChurn RateCohort Retention AnalysisConversion RateDaily Active UsersDrop-Off AnalysisEvent Frequency AnalysisFeature Adoption RateFeature Flag Impact AnalysisFunnel Conversion AnalysisGoal Completion RateMonthly Active UsersPage/Screen ViewsSession DurationSession FrequencySurvey Response AnalysisTime Between EventsTime to First ValueTrend AnalysisUser Activation RateUser Flow AnalysisUser Journey AnalysisUser Retention RateUser Segmentation AnalysisWeekly Active UsersEmpower your team to understand and act on PostHog data
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