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For many brands, Marketing Mix Modeling (MMM) has become a de facto standard for calculating advertising return. By separating incremental sales from base sales, MMM quantifies the contributions that each element of the marketing mix makes to the bottom line.
One criticism of MMM is that because its insights aren’t available until after an advertising campaign has run, they are not actionable. In a way, this criticism is a bit disingenuous because MMM is often able to provide general learnings for future media planning and trade deal optimization. But there is some truth to the fact that MMM and media plans (by themselves) often don’t provide reasonably accurate forecasts of future advertising return. This is primarily because the effectiveness of campaigns can vary widely from one to another due to differences in the relative strength of their particular advertising creative. Two campaigns with identical media plans can have vastly different sales outcomes because of differences in the persuasiveness of ads deployed.
To bridge this gap, Comscore has worked with its advertising clients and their MMM suppliers to identify whether there is a predictive correlation between creative pre-testing and MMM results. Representing 37 brands within 27 product categories, we examined the results of 231 advertising campaigns and analyzed the relationship between the creative pre-test scores, media spend and subsequent MMM results. The results showed that across the product categories examined, the pre-test and spend data combined were predictive of the MMM outcomes at a compelling 0.90 correlation level (see below chart). This relationship held true within product categories and across individual brands as well.
There are several ways we have seen advertisers use this predictable relationship to their advantage. In one example, instead of using broad category averages as “norms” for comparing the pre-testing scores, some advertisers are setting pretesting goals based on desired sales outcomes. Other advertisers are using this relationship for dynamic allocations of media spend between campaign executions. And still others are using it in the boardroom and executive suite to secure approval for larger media budgets when they have ‘killer’ pre-test scores. Regardless of how it is deployed, this relationship provides enhanced actionability for brands, with the potential to result in real, monetary payoffs that until now were difficult to achieve. The resulting conclusion is that creative pre-testing represents a critical component for optimizing ad spend and maximizing the financial return from advertising investments.