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Return on Media Models

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Handbook of Market Research

Abstract

The proliferation of marketing media, especially since the advent of digital media, has created an urgent need for marketers to understand their relative importance in generating revenue for their brands. Ultimately, this understanding should result in managers’ ability to project returns from their media investments. This chapter will focus on quantitative methods that enable such media return calculations. We begin with a definition of “return on media” and show how it connects to the need of estimating top-line lift, i.e., consumer response to media, from various data sources. We introduce the standard media-mix response model and discuss the estimation of media response elasticities. We extend these models to include brand-building and customer-equity effects and intermediate-performance variables. Finally, we address return to media in the digital era, with specific reference to path-to-purchase models, and we describe how media returns are derived from sales response models.

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Acknowledgment

I am grateful to coauthors in other publications that have helped shape the content of this chapter, in particular material from Hanssens et al. (2001), Dekimpe and Hanssens (2007, 2011), Hanssens and Dekimpe (2008), and Farris et al. (2015).

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Authors and Affiliations

  1. UCLA Anderson School of Management, 110 Westwood Plaza, Los Angeles, CA, 90095-1481, USA

    Dominique M. Hanssens

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  1. Dominique M. Hanssens
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Correspondence to Dominique M. Hanssens .

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Editors and Affiliations

  1. Department of Business-to-Business Marketing, Sales, and Pricing, University of Mannheim, Mannheim, Germany

    Christian Homburg

  2. Department of Marketing & Sales Research Group, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Martin Klarmann

  3. Marketing & Sales Department, University of Mannheim, Mannheim, Germany

    Arnd Vomberg

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Hanssens, D.M. (2022). Return on Media Models. In: Homburg, C., Klarmann, M., Vomberg, A. (eds) Handbook of Market Research. Springer, Cham. https://doi.org/10.1007/978-3-319-57413-4_1

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