Marketing Mix Modeling Explained – With R
Marketing mix modeling (MMM) is a process used to quantify the effects of different advertising mediums, i.e. media. It is also used to optimize the spend budget over these different mediums. The popular method of choice is multiple regression analysis. The model also takes into account other variables such as pricing, distribution points, and competitor tactics. This article will explain the math
Robyn
RobynRobyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. A New Generation of Marketing Mix ModelingOur mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community. Automated hyperparameter optimization w
GitHub - facebookexperimental/Robyn: Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, redu
What is Robyn?: Robyn is an experimental, semi-automated and open-sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. It uses various machine learning techniques (Ridge regression, multi-objective evolutionary algorithm for hyperparameter optimization, time-series decomposition for trend & season, gradient-based optimization for budget allocation, clustering, etc.) to define
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