Ebiquity's Mixed Marketing Modeling


To better understand Ebiquity's Mixed Marketing Modeling approach, including how it effectively mitigates other factors that could impact ROI to isolate ad impact

Early Findings

  • Market Mix Modeling (often also referred to as MMM) is a data science based marketing analytics approach which helps to quantify the impact of multiple marketing inputs.
  • Market Mix Modeling has a core purpose of helping to understand how much each individual marketing input of a mix campaign is of impact, specifically in terms of contribution to sales, which allows its users to determine how much to spend on each input.
  • Market Mix Modeling uses Multi-Linear Regression, with a dependent variable that is either Sales or Market Share, and independent variables usually being categories including “Distribution, price, TV spends, outdoor campaigns spends, newspaper and magazine spends, below the line promotional spends, and Consumer promotions information”.
  • The data is then input into an equation which uses dependent variables and predictors to calculate the ROI of each independent variable.
  • Ebiquity claims to have one of the most advanced mixed marketing testing tools on the market, TestMatch, which they say allows clients to most accurately understand each element of their marketing spend.
  • Ebiquity also claims their model and analytics enable their analysts "to handle more data and run more models than anyone else”.
  • Of additional relevance, Ebiquity recently partnered with company Evergage in order to allow Ebiquity to further personalize their data technology, which will specifically allow them to use market mix modeling data to better personalize paid campaigns.
  • When Facebook began to offer data for companies to input into market mix modeling, Ebiquity was one of the first participating companies, using Facebook’s new tools to help users better measure the impacts of Facebook, Instagram and other inputs on engagement.

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