Google Meridian vs rex by AureliaX

Google Meridian is a free, open-source Bayesian marketing mix modeling library for estimating channel contribution and ROI, modeling response curves and planning budgets. It is designed to estimate causal marketing impact and incremental outcomes for treatment variables. Teams can use geo-level data for media effect estimates, incorporate business knowledge through priors, and include controls such as Google Query Volume. Meridian supports reach and frequency modeling for video and search query volume data to account for organic demand. Its budget optimization and scenario planning features help teams assess channel allocation. Meridian GeoX supports geo experiments whose results can be used to calibrate models; automated calibration and expanded model health diagnostics are also supported. The Scenario Planner notebook requires access to at least one trained model stored in Google Drive or Google Cloud Storage. Meridian Studio is a Google Cloud-powered enterprise platform for managing models, with capacity to run up to hundreds simultaneously. Google describes Meridian as intended for cross-functional measurement teams, including analysts, business users, data scientists and technical practitioners. Support includes community discussions and expert support through Discord, plus technical troubleshooting through GitHub.

rex by AureliaX is a Marketing Mix Modelling platform for measuring and improving marketing performance across online and offline channels. Bayesian machine-learning models test starting assumptions against two to three years of historical data. Response curves and scenario planning support recommended budget allocations, while the platform provides budget planning, forecasting and ROI reporting. Users can inspect model components, confidence intervals, initial assumptions and how incoming data changed them. rex connects to more than 500 marketing platforms, including Google Ads, Meta, TikTok, Snapchat, LinkedIn and Pinterest. For offline channels without APIs, templates accept weekly or monthly spend and reach figures. Recommendations are updated monthly and reviewed by the maker’s team. Onboarding typically includes two or three sessions and a monthly review. The service is available through web and API access. Its maker describes it as GDPR-compliant and privacy-first and says it does not rely on user-level cookies. Pricing is tailored to business needs, users and modules, with pilot programs for strategic partners.