Product analytics
From Hogpedia, the free encyclopedia
Product analytics is the measurement of how people use a software product, based on events recorded while they use it. PostHog's glossary defines it as analytics that track identified and anonymous users and how they interact with a product, and notes that product analytics tools usually offer more detailed analysis than web analytics tools because they can follow an identified user.[1]
Product Analytics is also the name of the PostHog product that does this.[3]
What problem it solves[edit]
A team that ships a feature cannot tell from the code whether the feature worked. Server logs show that a request happened; they do not show that a person finished what they came to do, or where they stopped.
Product analytics answers four questions that a log cannot:
- How many? How often does a thing happen, and is that number moving?
- Where do people stop? At which step of a sequence do people drop out?
- Do they come back? Does a person who did a thing once do it again?
- What did they do first? What path did a person take to reach a point?
How it works in PostHog[edit]
An event is a named record of a thing a person did, with properties attached, tied to a person. A PostHog SDK sends those events; autocapture can record clicks and pageviews without a developer naming each one first.[2]
From that one event stream, PostHog builds four main insight types:
- Trends count events over time, broken down by a property.
- Funnels measure conversion through an ordered sequence of steps.
- Retention measures whether people who did one thing return to do it again.
- User paths show the routes people take between events.
Anything the insight editor cannot express can be written as SQL against the same data, in a dialect PostHog calls HogQL.[4]
How it relates to other PostHog products[edit]
Product analytics is the layer the other products read from and write to.
- Session replay answers why a funnel step loses people. A funnel gives the number; a replay shows one person failing at that step.
- Feature flags record which variant each person saw, so an analytics query can be split by it.
- Experiments are built directly on funnel and trend insights: an experiment metric is an insight, measured per variant.
- Surveys attach what a person said to what that person did.
Web analytics, a separate PostHog product, reports on the same event stream but is organized around traffic, sources, and pages rather than around identified people.
See also
References
- ^PostHog glossary, "Product analytics"
- ^PostHog documentation, Product analytics
- ^PostHog product analytics
- ^PostHog documentation, SQL
External links
This page was last modified on October 7, 2026.
Hogpedia is part of the posthog.com repository. Hedgehogs are PostHog brand assets – read the brand guide before reusing one.
Main Page · About · Donate · posthog.com