Pirsch
Cookie free, privacy-first website analytics that runs lightweight and open-source. Easy server side integration and GDPR compliant.
Pros
- Does not use cookies and does not store personally identifiable information
- Minimal impact on website loading speed
- Pirsch is open-source, allowing for full transparency on how data is collected and processed
Cons
- Fewer advanced reports and funnels than Google Analytics
- Price increases with page views
Pirsch offers a clean, fast web analytics dashboard that surfaces the numbers you actually need. Its interface focuses on simple charts, real time visits, and easy to read page and event views. You get quick access to trend lines and conversions without wrestling through dozens of reports. The product is also privacy minded and cookieless, so compliance is simpler out of the box.
Under the hood Pirsch packs practical features that teams use daily. You get conversion goals, event tracking, a tiny JS snippet, server side event options, a built in shortener, webhooks and an API for custom pipelines. It supports hosted or self hosted installs, white labeling for agencies, and exports for offline analysis. Those bits mean prototypes and campaigns can ship with reliable counts and usable webhooks feeding other systems.
Why many teams pick Pirsch over Google Analytics is simple: clarity, control and reliability. The dashboard is less noisy so product and marketing people find insights faster. Self hosting or server side events reduce data loss from ad blockers which improves event completeness. Setup is quicker, so you can instrument a site and get useful data in hours rather than weeks. For privacy conscious brands or small teams who do not need every advanced funnel, Pirsch gives better ROI on analytics effort.
If you need deep, sampled funnels, session replay, or very large scale cohorts, full feature parity with Google Analytics is not the point here. Pirsch trades exhaustive menus for speed and control. Teams that want fast, accurate metrics, easier compliance, and a low footprint analytics stack will find it a practical and modern alternative.


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