
Maud Royer developed and stabilized analytics capabilities for the betagouv/recommandations-collaboratives repository over a two-month period. She integrated Matomo analytics by implementing a Django context processor that exposed configuration and user roles to templates, and created an HTML template to render the tracking script with dynamic custom dimensions. The integration was made configurable via environment variables, ensuring minimal overhead when disabled. In a subsequent update, Maud addressed a bug to guarantee the Matomo heatmap plugin script loaded correctly, improving data fidelity and session recording. Her work demonstrated proficiency in Python, JavaScript, and Django, with a focus on maintainable, configurable analytics solutions.

July 2025: Stabilized analytics capabilities for betagouv/recommandations-collaboratives by implementing a targeted bug fix in the Matomo integration. Delivered a fix to ensure the Matomo heatmap plugin script is included in the HTML template when the main matomo.js bundle does not include it, guaranteeing session recording and heatmap visibility for users across configurations. The change reduces configuration-related outages and improves data fidelity for analytics dashboards.
July 2025: Stabilized analytics capabilities for betagouv/recommandations-collaboratives by implementing a targeted bug fix in the Matomo integration. Delivered a fix to ensure the Matomo heatmap plugin script is included in the HTML template when the main matomo.js bundle does not include it, guaranteeing session recording and heatmap visibility for users across configurations. The change reduces configuration-related outages and improves data fidelity for analytics dashboards.
In May 2025, delivered a focused analytics enhancement for betagouv/recommandations-collaboratives by integrating Matomo analytics. Implemented a Django-based context processor exposing Matomo config and user roles to templates, and added an HTML template to render the Matomo tracking script with dynamic custom dimensions for site domain and user roles. The integration is configurable via environment variables and renders conditionally when enabled, ensuring zero overhead in non-analytics environments. This lays the groundwork for data-driven insights and improved product decisions while maintaining performance and privacy controls.
In May 2025, delivered a focused analytics enhancement for betagouv/recommandations-collaboratives by integrating Matomo analytics. Implemented a Django-based context processor exposing Matomo config and user roles to templates, and added an HTML template to render the Matomo tracking script with dynamic custom dimensions for site domain and user roles. The integration is configurable via environment variables and renders conditionally when enabled, ensuring zero overhead in non-analytics environments. This lays the groundwork for data-driven insights and improved product decisions while maintaining performance and privacy controls.
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