GA4 for Product Analytics: Capabilities and Limitations

GA4 Is More Than Web Analytics

Google Analytics 4 was redesigned around an event-based, user-centric model that makes it capable of handling many product analytics use cases. For early-stage products or teams already deeply invested in the Google stack, GA4 may be sufficient. But it has real limitations compared to dedicated product analytics tools, and knowing those limits helps you make the right tooling decision.

What GA4 Does Well for Product Analytics

• User-level tracking: GA4 ties events to users via User-ID or Google Signals, enabling cross-session analysis
• Retention reports: Built-in cohort retention analysis (though less flexible than Mixpanel/Amplitude)
• Path analysis: "User explorer" and "Path exploration" show sequences of events per user
• Custom events: Full custom event tracking with up to 25 parameters per event
• BigQuery export: Raw event export for SQL-based analysis — this is where GA4 gains significant power
• Cost: Free for most usage levels

Where GA4 Falls Short for Product Analytics

• Funnel flexibility: GA4 funnels are limited to the Exploration UI — Mixpanel and Amplitude have more flexible funnel definitions and better UX for non-technical product managers
• Behavioral cohorts: GA4 doesn't support cohorts defined by specific sequences of events with the granularity that Amplitude does
• Query limits: GA4 exploration reports have sampling at high volumes and limited export options without BigQuery
• Real-time analysis: GA4's real-time view is limited compared to Mixpanel's real-time funnel and retention updates
• Mobile analytics depth: Firebase + GA4 covers basics but Amplitude's mobile-specific analysis is more powerful

The Recommendation

Start with GA4 if you're pre-product-market-fit. The free tier is sufficient, the learning curve is manageable, and the BigQuery integration gives you advanced analysis capability when needed. Adopt Mixpanel or Amplitude when your product team has dedicated product managers or analysts running frequent product experiments and retention analyses. Our product analytics service helps teams make this transition without losing historical data.