Google Meridian vs LiftLab

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.

LiftLab is a marketing measurement platform for assessing brand and performance media spending and informing budget decisions. Its Two-Stage Agile Marketing Mix Model separates advertising auction cost dynamics from consumer response to estimate channel response curves. The Scenario Planner builds Conserve, Maintain, and Accelerate budget scenarios within constraints such as channel caps, CAC ceilings, and committed spend. Geo experiments in the Incrementality Testing Suite feed causal results back into the model for calibration; supported methods also include Stratified Random Sampling, Synthetic Controls, Switchback tests, Strategy experiments, and Go Dark with Pacing. PlatformSense monitors daily performance changes and uses live signals to inform reallocation recommendations. Miles, an AI-powered analyst, answers questions in plain English using LiftLab’s measurement methodology. LiftLab says it connects with more than 50 paid media platforms, plus analytics, CRM, warehouses, and first-party data sources. Starting data requirements are 12 to 24 months of weekly channel spend, one primary outcome KPI, and a promotional calendar. It is designed for enterprise marketers, including teams spending $5 million or more annually on media. Pricing is on request.