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Applying Decision Quality to Marketing Mix Decisions

John Busbice, Keen Decision Systems
June 15, 2022 (SDP Invited Talk)

Abstract: Marketing professionals regularly face difficult decisions about how much to invest in marketing including advertising, sales activities, and promotion. These decisions are difficult because there are ambiguous and uncertain causal relationships between investments and outcomes, and competing objectives between stakeholders. Further, the analysis is difficult because of the lack of direct measures of marketing impact and the quality of the data necessary to make inferences to inform decisions. In this webinar we will explore these issues and solutions through the lens of Decision Quality.

Special attention will be given to the use of econometric and optimization methods typically used by marketing mix modelers. We will discuss ways in which marketers as key stakeholders should interact with these models. And we will discuss the value of using Bayesian econometric methods and non-linear optimization routines to assist decision makers. A case study will be provided that demonstrates the application of these methods to the problem.

Generally, the application of methods at the intersection of decision analysis and machine learning to ongoing operational decisions will be discussed including approaches to integrating Bayesian data analysis, optimization and embedding software systems into an organization’s decision-making processes.

Click on the file below to hear a sample of the presentation.  

Click here for access to the full video.

SDP membership is required for access to this webinar.

Keywords: framing framestruc, econometric, marketing, decision hierarchy dechier, influence diagram infldiag, VOI value of information voivoc valoi, optimization optz, risk and uncertainty riskunc, npv

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