Measured vs Robyn

Measured is an AI-powered marketing effectiveness platform for enterprise brands. It combines causal experiments, media mix modeling, and advertising-platform data to assess media impact. Geo-matched and first-party split tests measure incremental sales, while automated tools cover machine-learning market selection, audience and geographic splitting, test design, and calibration. Media mix models use incrementality tests as causal priors and can be updated weekly, monthly, or quarterly. The Media Plan Optimizer runs budget scenarios and allocates spending toward marginal ROI, growth, or profitability goals. Measured lists more than 300 fully managed integrations across analytics, business intelligence, CRM and email, ecommerce, social, search, and TV and OTT, plus a REST API for cross-channel performance data. The platform runs on web and API. Pricing is available on request, and each customer is paired with an analytics expert.

Robyn is a free, open-source Marketing Mix Modeling package from Meta Marketing Science. It estimates media channel efficiency and effectiveness, adstock rates and saturation curves using machine-learning techniques. The package is intended for granular datasets with many independent variables, particularly those used by digital and direct-response advertisers with rich data sources. Robyn automates hyperparameter optimization with evolutionary algorithms and uses ridge regression to address multicollinearity and overfitting. Its time-series modeling accounts for trend, seasonality and holidays, and models can be calibrated against ground-truth methods such as geo-based tests, Facebook Lift and MTA. The budget allocator uses a constrained nonlinear solver to seek outcome gains through budget reallocation; model one-pagers support comparisons. Robyn does not require personally identifiable or individual-level data and does not rely on cookies or pixel data. A stable R version is available on CRAN, alongside a development version on GitHub. A Python version is documented as beta and may have translation issues. The package is MIT licensed; support options include a public user group and GitHub issues.