Google Meridian

​Haus is a marketing science platform that enables brands to measure the precise business impact of their advertising efforts, both online and offline, through automated incrementality experiments. It offers products like GeoLift for geo-based incrementality testing, Causal Attribution for day-to-day incrementality reporting, and the upcoming Causal MMM for incrementality-powered media mix modeling. These tools allow users to design and launch experiments in minutes, obtain results in as little as two weeks, and optimize marketing investments with daily incrementality reporting. Haus emphasizes privacy-durable solutions that do not rely on pixels, cookies, or personally identifiable information, ensuring compliance with evolving privacy regulations.

Robyn is an open source, experimental Marketing Mix Modeling (MMM) package developed by Meta’s Marketing Science team. It’s designed to help advertisers and analysts build rigorous, data-driven models that quantify how different marketing channels contribute to business outcomes (like sales, conversions, or other KPIs) in a privacy-safe, aggregated way. Rather than relying on user-level tracking, Robyn analyzes historical time-series data, combining marketing spend or reach data (ads, promotions, organic efforts, etc.) with outcome metrics, to estimate incremental impact, saturation effects, and carry-over (adstock) dynamics. Under the hood, Robyn blends classical statistical methods with modern machine learning and optimization; it uses ridge regression (to regularize against multicollinearity in many-channel models), time-series decomposition to isolate trend and seasonality, and a multi-objective evolutionary algorithm.