Product Analytics: Definition, Examples, and Metrics
Definition
Product analytics helps you understand what people do after they arrive at your website or start using your product. Instead of looking only at pageviews, it tracks actions such as starting signup, completing onboarding, or using a key feature. These events help teams see which steps people complete, where they get stuck, and which parts of the product deserve a closer look.
How EventDash implements it
EventDash combines website analytics with product-focused measurements, including conversion funnels, HTML goals, custom events, JavaScript error tracking, and Core Web Vitals on paid plans. It is designed for teams that want to connect website activity with important conversion steps without adding a separate tracking script for every action.
Product analytics vs. web analytics
Web analytics usually starts with acquisition and traffic: where visitors came from, which pages they viewed, and how they moved around a website. Product analytics focuses more closely on what people do and whether they reach meaningful milestones.Consider a SaaS website. A web analytics report might show that the pricing page attracted 1,000 visits. Product analytics can help answer a follow-up question: how many people started signup, and how many completed it?The two approaches work well together. Traffic reports help explain how people arrive; event-based measurement helps explain what happens next.For a closer look at the distinction, see pageviews vs. product analytics.
Product analytics examples
The events you track should reflect the actions that matter to your product. For a SaaS business, that might mean account creation, onboarding completion, or use of a key feature. For an online service, it could be a search, a booking step, or a completed purchase.Once those events are in place, you can group them into a funnel to see how people progress toward a goal. You can also compare patterns over time to see whether a change in the product coincides with a change in behavior.The aim is not to track every click. Start with a few actions that help answer a real product question, then add detail when you have a reason to investigate further.
Which product analytics metrics should you track?
The useful metrics depend on the product and the stage of the customer journey. Common starting points include:- Activation: how many new users reach a meaningful first milestone.- Conversion rate: how many people complete a defined goal.- Funnel drop-off: how many people stop progressing between steps.- Feature adoption: how often people use an important feature.- Retention: whether people return and continue using the product over time.Choose metrics that relate to a decision you need to make. A large event count does not automatically tell you whether a product is easier to use or whether customers are getting value from it.For step-by-step conversion analysis, see the conversion funnel definition.
Choosing a product analytics tool
Before choosing a tool, consider how much implementation work it requires, which events it can collect, how it presents funnels, and whether its privacy approach fits your needs.Some teams need detailed user journeys and advanced behavioral analysis. Others mainly want reliable conversion tracking, a clear view of funnel drop-off, and a small set of useful product metrics. Those needs can lead to different choices.EventDash focuses on website analytics, funnels, HTML goals, custom events, and performance measurements. Compare its capabilities with your actual reporting requirements rather than assuming every product analytics platform offers the same features.You can compare EventDash with Plausible and PostHog to explore different approaches to analytics.