Allocating Marketing Resources

by Sunil Gupta & Thomas J. Steenburgh

Overview — Deciding how to allocate marketing resources is particularly difficult because decisions need to be made at many different levels—across countries, products, marketing mix elements, and different vehicles within elements of the mix (e.g., television versus the Internet for advertising). With the increasing availability of data and sophistication in methods, it is now possible to more judiciously allocate marketing resources. In this paper, HBS professors Gupta and Steenburgh discuss a two-stage process where a model of demand is estimated in stage-one and its estimates are used as inputs in an optimization model in stage-two. The researchers propose a matrix with three approaches for each of these two stages, and discuss the pros and cons of these methods. They highlight each method with applications and case studies to present rigorous yet practical approaches to making marketing resource allocation decisions. Key concepts include:

  • This paper lays out a framework for managers who are responsible for allocating marketing resources for their products and services.
  • Scores of studies in the area of allocating marketing resources now make it possible to form empirical generalizations about the impact of marketing actions on sales and profits.
  • In practical terms, information about marketing resource allocation makes a significant impact at all levels of an organization.

Author Abstract

Marketing is essential for the organic growth of a company. Not surprisingly, firms spend billions of dollars on marketing. Given these large investments, marketing managers have the responsibility to optimally allocate these resources and demonstrate that these investments generate appropriate returns for the firm. In this chapter we highlight a two-stage process for marketing resource allocation. In stage one, a model of demand is estimated. This model empirically assesses the impact of marketing actions on consumer demand of a company's product. In stage two, estimates from the demand model are used as input in an optimization model that attempts to maximize profits. This stage takes into account costs as well as firm's objectives and constraints (e.g., minimum market share requirement). Over the last several decades, marketing researchers and practitioners have adopted various methods and approaches that explicitly or implicitly follow these two stages. We have categorized these approaches into a 3x3 matrix, which suggests three different approaches for stage-one demand estimation (decision calculus, experiments and econometric methods), and three different methods for stage-two economic impact analysis (descriptive, what-if and formal optimization approach). We discuss pros and cons of these approaches and illustrate them through applications and case studies.

Paper Information