What is Product Analytics?
Turkish: Ürün Analitiği (Product Analytics)
Product analytics measures how users move through a product, where they drop off, and which behaviors predict retention.
What is Product Analytics?
Product analytics uses events, funnels, cohorts, and behavior metrics to understand what users do inside a product. Web analytics may focus on pageviews; product analytics asks whether users complete the actions that create value.
What Gets Measured?
Typical events include signing up, sending an invite, creating a project, uploading a file, starting payment, downloading a report, or connecting an integration. Each event is stored with properties such as user, plan, acquisition source, device, and time. This data supports activation funnels, feature usage analysis, return behavior, and churn signals.
Analysis Methods
- Funnel: Shows where users drop out of a sequence.
- Cohort: Compares users who started in the same period over time.
- Retention: Measures whether users come back to the product.
- Segment: Separates behavior by plan, role, country, or acquisition channel.
Impact on Product Decisions
Product analytics can show which onboarding step causes friction, which feature influences paid conversion, or which campaign brings high-quality users. Conversion rate, DAU/MAU, and retention should be interpreted together with the target behavior of the product. Privacy, consent, and data retention policies are part of measurement design.
Related Terms
Conversion rate measures the percentage of visitors who complete a target action such as buying, signing up, or submitting a form.
DAU/MAU (Daily/Monthly Active Users)DAU/MAU compares daily active users with monthly active users to show how often people return and how sticky a product is.
User RetentionRetention measures how many users return after their first experience, showing whether a product creates lasting value and habit.