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Ep. 338
Offen Fair Web Analytics is presented as a clear, actionable, and ethical model for web analytics, designed to address data privacy concerns and information overload. It operates on three core pillars: being secure and free with open-source code, self-hosted to ensure data ownership and prevent third-party leakage, and strictly opt-in for user consent, leaving no trace if not agreed upon. This approach shifts the operator’s responsibility to a trust contract with the user, focusing on data minimization, end-to-end encryption, and transparent insights. Unlike traditional analytics, Offen avoids collecting IP addresses and user agent strings, and its end-to-end encryption ensures that even if a server is compromised, the data remains uselessly scrambled. Operators receive essential aggregate data like unique sessions and top pages, while users, through the ‘auditorium,’ can view their specific activity, fostering profound trust. Deployment is simplified through lightweight binaries or Docker images, with options like SQLite for database management and automatic SSL certificate handling. The system supports multiple languages and offers customizable consent banners to match website design. A demo command is available for immediate testing. Offen is highlighted as a genuine ethical alternative, supported by the NL Net Foundation, promoting a more private web by placing users on equal footing with operators and questioning whether fairness can become a primary driver for user engagement.