Ever since Neil Borden coined the term “marketing mix” in 1949, companies have searched for ways to analyze and refine how they market and promote their products. For a long time, the leading analytic approach to this problem was “marketing mix modeling,” which uses aggregate sales and marketing data to suggest strategic adjustments to a firm’s marketing efforts. But in the realm of digital ad measurement, this approach was largely taken for an outdated behemoth, easily outmaneuvered by the immediate, precise, and deterministic attribution new technology enabled.
A New Gold Standard for Digital Ad Measurement?
As the digital ad measurement landscape changes, companies should consider marketing mix models calibrated with ad experiments.
March 24, 2023
Summary.
Marketing mix modeling is making a comeback. Fundamental changes to the digital ads ecosystem — such as Apple’s new limits on what advertisers are able to track — mean that deterministic user-level measurement of digital advertising effects is only going to get more challenging. As this data dries up, companies that don’t adapt run the risk of suddenly finding themselves in the dark. In this new landscape, marketing mix models (MMMs) have a specific advantage: They’re able to produce dependable measurements — and insight — purely from natural variation in aggregate data, and don’t require user-level data.
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Digital Intelligence Course
Accelerate your career with Harvard ManageMentor®. HBR Learning’s online leadership training helps you hone your skills with courses like Digital Intelligence . Earn badges to share on LinkedIn and your resume. Access more than 40 courses trusted by Fortune 500 companies.
Excel in a world that's being continually transformed by technology.