Web and product analytics
Product analytics vs web analytics: which one do you need?
The short answer
Web analytics answers marketing questions about sessions: how many visits, from where, and did they convert. Product analytics answers questions about identified users over time: who used which feature, who came back, and where they dropped out of a flow. Content and lead-generation sites need the first; software products and apps usually need both.
Key takeaways
- Web analytics counts sessions and sources; product analytics follows identified users over time.
- Content and lead-generation sites need the first; software products usually need both.
- A written tracking plan of ten or so named events is most of the work in product analytics.
On this page 2 sections
| Web analytics | Product analytics | |
|---|---|---|
| Unit of analysis | Session or visit | User and their events |
| Typical questions | Which channel drives enquiries? | Do users who invite a teammate in week one retain better? |
| Typical tools | GA4, Plausible, Matomo | Mixpanel, PostHog, Amplitude |
| Owner | Marketing | Product and growth |
| Set-up effort | Low: install a tag | Higher: design and maintain an event schema |
The event schema is the work
Product analytics is only as good as the events you send. Write down the ten or so actions that define value in your product (signed up, created a project, invited a teammate, upgraded) and name them consistently before you instrument anything. A tracking plan in a spreadsheet saves months of confused charts.
A sensible sequence for a SaaS company
- Web analytics on the marketing site, with UTMs on every campaign.
- Product analytics in the app, identified by user ID, with a short tracking plan.
- A survey in the product at key moments (see how to measure NPS).
- Later, prediction on top of that history (see predictive analytics for small business).
Next step
Compare the tools for this job
Related guides
GA4 alternatives: when to switch and what to switch to
Plausible, Matomo, Fathom, PostHog and Mixpanel compared with Google Analytics 4 by the job each one does, with honest reasons to stay on GA4.
How to measure NPS (Net Promoter Score)
How to ask the NPS question, calculate the score, choose when and where to survey, and turn the follow-up comments into decisions.
What is predictive analytics for a small business?
Predictive analytics in plain terms: what it predicts (churn, lifetime value, lead score, demand), the data you need, and how a smaller business starts.