PostHog tells you what users do in your product. KPI Tree tells you what that means for your business.

A/B test performance evaluates the outcomes of PostHog experiments by comparing engagement, conversion, and retention metrics across control and treatment variants. It determines whether feature changes produce statistically significant improvements and quantifies their impact on downstream business metrics.

Bounce rate in PostHog measures the percentage of sessions where a user visits a single page or screen and leaves without triggering any additional events. It indicates how effectively your entry points engage users enough to explore further.

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.

Cohort retention analysis groups PostHog users by their signup or first-use date and tracks what percentage remain active over subsequent days, weeks, and months. It reveals retention curves per cohort, showing whether product changes improve or degrade long-term user retention.

Conversion rate in PostHog measures the percentage of users who complete a defined conversion action - such as signing up, activating a feature, upgrading to a paid plan, or completing a key workflow. It quantifies how effectively your product converts users at each stage of the journey.

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.

Drop-off analysis identifies the specific steps within PostHog funnels where users disengage or fail to proceed. It quantifies attrition at each stage to pinpoint the features, screens, or interactions that cause users to abandon their journey before reaching the desired outcome.

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.

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.

Feature flag impact analysis evaluates how PostHog feature flags and gradual rollouts affect engagement, conversion, retention, and revenue metrics. It measures the business impact of enabling or disabling features for specific user segments, providing evidence for rollout decisions.

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.

Funnel conversion analysis tracks user progression through defined multi-step journeys in PostHog - from initial action through intermediate steps to final conversion. It measures the conversion rate at each step and identifies where the largest opportunities for improvement exist.

Goal completion rate measures the percentage of PostHog users who achieve a predefined product objective - such as completing onboarding, creating their first project, inviting a team member, or reaching a usage milestone. It quantifies how effectively your product guides users toward its intended value.

Monthly active users counts the unique users who trigger at least one qualifying event in PostHog within a 30-day period. It provides a broad measure of your product's reach and the size of your engaged user base, serving as a primary growth indicator.

Page and screen views measure the total number of times specific pages or screens are viewed within your product, as tracked by PostHog. This metric reveals which areas of your product receive the most attention and how users navigate through your interface.

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.

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.

Survey response analysis evaluates PostHog in-product survey results - including NPS, satisfaction scores, and open-ended feedback - alongside quantitative product usage data. It connects qualitative user sentiment to behavioural patterns to reveal why users behave the way they do.

Time between events measures the duration between two specific PostHog events in a user's session or journey - such as the time between signup and first project creation, or between feature discovery and first use. It reveals workflow efficiency and user momentum through your product.

Time to first value measures the duration between a user's first interaction with your product and the moment they complete a defined value-delivering action - their "aha moment" - as tracked in PostHog. It quantifies how quickly your product demonstrates its worth to new users.

Trend analysis examines how PostHog metrics change over time - daily, weekly, monthly, and quarterly. It identifies growth trajectories, seasonal patterns, and anomalies in product usage, engagement, and conversion metrics to inform strategic decisions and surface issues early.

User activation rate measures the percentage of new signups who complete a defined set of activation actions in PostHog within a specified timeframe. Activation actions typically represent the behaviours that correlate with long-term retention, such as completing onboarding, creating a first project, or inviting a colleague.

User flow analysis maps the paths users take through your product in PostHog, from entry point through feature interactions to exit or conversion. It identifies the most common navigation patterns, unexpected detours, and the paths that most frequently lead to activation, retention, or churn.

User journey analysis maps the complete multi-session experience of PostHog users over their lifecycle - from first visit through onboarding, feature discovery, habitual usage, and expansion or churn. It reveals the long-term patterns that distinguish users who succeed from those who leave.

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.

User segmentation analysis divides PostHog users into distinct groups based on behaviour, attributes, or lifecycle stage and compares their engagement, conversion, and retention patterns. It reveals which user segments deliver the most value and which require different product strategies.

Weekly active users counts the unique users who trigger at least one qualifying event in PostHog within a 7-day period. It provides a mid-range engagement measure between daily and monthly activity, capturing users who engage regularly but not necessarily every day.