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ABSTRACT
The advertising and marketing communities traditionally have understood television advertising effectiveness and its relationship to in-store marketing tactics through small-market research or marketing-mix modeling. Although these studies have improved the quality of advertising-effectiveness research, they have done little to improve the tools marketers need to translate those insights on a larger scale and optimize their marketing allocations. With the proliferation of “big data,” researchers now have the ability to refine those tools and give marketers a more granular understanding of brand-purchase behavior and the impact of multiple marketing levers on in-store brand sales. This paper leverages the anonymous household-level purchase behavior data from 60 million households across the United States and the second-by-second measurement of television-viewing habits from more than 2 million set-top box households, and the current study applies actual (non-modeled) single-source, household-level data to demonstrate a methodology for optimizing the mix of television advertising and in-store marketing.
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Vol 52 Issue 3
