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Product Analytics terms
Funnels, retention, feature adoption and the tools product teams watch.
Activation rate The share of new users who complete the specific actions that mark them as having found a product's core value. Aha moment The point at which a new user first experiences the core value of a product clearly enough to want to continue. Daily active users (DAU) The count of unique users who take a qualifying action in a product within a single calendar day. Event data model The structured format — event name, timestamp, user ID, and properties — that a single tracked user action is recorded in. Event taxonomy The standardized naming and structure for the user actions a product tracks, so events mean the same thing everywhere. Event tracking Capturing specific user actions, such as clicks or purchases, as discrete, named pieces of data. Feature adoption The share of eligible users who take up and continue using a specific feature after its release. Feature flag A configuration switch that turns a piece of functionality on or off, or for specific users, without deploying new code. Funnel analysis A method for tracking how users move through an ordered sequence of steps toward a goal, and where they drop off. Guardrail metric A secondary metric watched during an experiment to catch harm the primary metric would not show, such as load time or churn. Holdout group A segment of users deliberately kept out of a treatment, campaign or feature, so its true incremental impact can be measured against them. Identity stitching Linking the different identifiers a single person generates across devices, sessions, and platforms into one profile. Multivariate testing (MVT) An experiment that varies several page or product elements at once, to measure each element's individual effect and how elements interact. North star metric The single metric a team chooses as the best proxy for the core value a product delivers to customers. Novelty effect A temporary spike in engagement with a new feature or design that fades once users stop reacting to its newness and it becomes routine. Overall evaluation criterion (OEC) The single metric or composite formula a team agrees in advance will determine whether an experiment's treatment is judged a success. Path analysis Examining the sequences of actions users take through a product to find common, high-value, or drop-off routes. Product-led growth (PLG) A go-to-market approach where the product itself, often via free trials or freemium use, drives acquisition and expansion. Product-qualified lead (PQL) A free or trial user whose in-product behavior signals they are ready to be approached about a paid plan. Recommendation system A system that predicts and ranks the items a specific user is most likely to want, such as products, content, or actions. Retention analysis The study of how many users keep returning to and engaging with a product after their first use. Session length How long a single continuous visit or usage period lasts, from a user's first action until the session ends. Split URL testing An A/B test that sends visitors to entirely separate page URLs for each variant, instead of changing content dynamically on one shared URL. Stickiness The ratio of daily to monthly active users, showing how often the average monthly user returns in a day. Time to value (TTV) How long it takes a new user, from signup, to first experience a product's core value. Tracking plan The document specifying every analytics event a product should fire, its properties, and who owns it. User journey analytics Analyzing the ordered sequence of touchpoints and actions a user takes across sessions and channels toward a goal. User properties Attributes describing a user, such as plan tier or signup date, attached to their profile rather than to a single event. Viral coefficient The average number of new users each existing user brings in, used to measure whether growth is self-sustaining.