Vemetric is a web and product analytics tool built to show how users arrive, convert, and interact with a product in one place. Its site describes it as focusing on simplicity and ease of use, with an emphasis on privacy. The service is based in the EU, and it says that it uses no cookies by default and is GDPR compliant.
The product includes web analytics that surface most visited pages, best referrers, top countries, and other insights for marketing pages as well as the product itself. It also tracks user journeys, merging anonymous and logged-in activity, and lets each user’s data be saved and viewed across devices. Another feature, Event Streams, presents events in chronological order, with real-time monitoring, advanced filtering and search, and filtering by several criteria. Funnels are used to track conversion rates through a series of events, map steps to pageviews or events, and see where users drop off. The site also mentions an interactive activity heatmap and dashboard integration, along with user segments, campaigns, and automations as features planned for the future.
Vemetric says it is used by organizations around the globe, and the customer examples shown include AI search and GEO, creator tools, project management SaaS, AI customer support, SaaS starter kits, and DeFi blockchain projects. It is presented as a web service, with documentation for integrating it into projects and a live API. The site also includes a changelog, a blog, an about page, and a separate open-source Favicon API.
Vemetric is an Analytics (BI, web, product) project. It focuses on understanding how users interact with web products and identifying opportunities for product improvement. Vemetric is a B2B product aimed at product managers. Vemetric follows a freemium model. It ships for the web and API.
Vemetric first shipped in 2025. The project is developed in the open on GitHub with 354 stars and 39 commits in the last 90 days. Among its 7 catalogued features are user journey tracking, feature adoption analytics, and conversion tracking. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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