PostHog Metric
Product Analytics
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.
PostHogProduct AnalyticsSession Frequency
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.
How to calculate session frequency
Why session frequency matters for PostHog users
A product with 1,000 MAU where each user averages 20 sessions per month is fundamentally healthier than one with 1,000 MAU where each averages 2 sessions. Frequency reveals habit formation - the strongest predictor of long-term retention.
Mapping session frequency into your metric tree connects return visit patterns to retention and revenue outcomes. Correlations show the frequency threshold where retention rates plateau, helping you define your product's "habit zone" and design features that drive users into it.
Understand and act on session frequency with KPI Tree
KPI Tree connects session data from your warehouse and tracks frequency distributions per user segment. Position alongside DAU, MAU, and retention metrics in your engagement tree.
Assign RACI ownership to your growth product manager. Set alerts when average session frequency declines and track product changes and re-engagement strategies against their frequency impact.
Get started with your PostHog data
MCPPull metrics from PostHog directly through the Model Context Protocol.
Connect your existing warehouse where PostHog data already lands.
Our professional services team can build you turn-key AI foundations in a matter of weeks. Data warehouse on Snowflake/BigQuery, ELT with Fivetran, all modelled in dbt with a semantic layer.
Related PostHog metrics
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.
Feature Stickiness
Product AnalyticsMetric Definition
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.
Session Duration
Product AnalyticsMetric Definition
Average Session Duration = Total Session Time / Total Sessions
Session duration measures the average time users spend in your product during a single PostHog session, calculated as the time between the first and last event. It indicates engagement depth and whether users spend enough time to derive value from your product.
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.
Churn Rate
Product AnalyticsMetric Definition
Churn Rate = (Users Lost During Period / Users at Start of Period) x 100
Churn rate measures the percentage of users who stop using your product within a defined period, based on PostHog event data. It quantifies user attrition by identifying users whose activity drops below a defined threshold, providing a behavioural measure of retention failure.
All PostHog metrics
A/B Test PerformanceBounce RateChurn RateCohort Retention AnalysisConversion RateDaily Active UsersDrop-Off AnalysisEvent Frequency AnalysisFeature Adoption RateFeature Flag Impact AnalysisFeature StickinessFunnel Conversion AnalysisGoal Completion RateMonthly Active UsersPage/Screen ViewsSession DurationSurvey 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
Map what drives your metrics, measure progress at any grain, prove what works statistically, and deliver personalised action plans to every team member.
