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Holistic Cross-Media Measurement
Brendan Kroll – VP Performance Measurement, Nielsen
Anne Ori – Measurement Lead, CG&E, Google
Daniel Sacks – Incrementality Lead, US Agency, Google
Brendan Kroll of Nielsen and Anne Ori and Daniel Sacks, both of Google, explained that their study’s objective was to identify potential improvements to marketing mix models by utilizing enhanced prior beliefs (priors) based on sales lift studies and exploring the resulting changes in campaign-level sales lift once those priors were incorporated. Incrementality experiments are widely accepted as the gold standard for causal measurement. Calibrating individual channels via experimentation ensures optimization of model outcomes. However, the results of incrementality experiments are often not part of marketing mix model (MMM) design. Nielsen utilized NCS sales lift studies as the source of the experimental data for this analysis. NCS determined the causal effects of advertising on incremental sales while controlling for targeting and other co-variates. The study design involved 10 brands with existing MMMs and available NCS results for corresponding periods, model re-estimation using NCS lift priors, refinement of the priors and scaling. This study showed that applying this methodology to a YouTube campaign resulted in significant sales lift, as well as revenue and ROAS increases, including a 2.6x median increase in the effectiveness in the adjusted model. The adjusted model showed greater marketing contribution overall; therefore, marketers are at risk of undervaluing their overall marketing if experimental results are not included.
Key Takeaways
- Brands can effectively leverage experiment-based priors to strengthen marketing mix models.
- For nascent channels, the inclusion of experimentation results proved fundamental, especially if those campaigns showed strong initial results, since MMMs cannot rely solely on historical anchoring to measure true impact.
- When experiments reveal high performing channels or campaigns, the use of testing can aid more accurate MMM measurements as investment scales.
- Even for channels with long histories and relative stability, experimentation can serve as a way to validate models and may give models a chance to remain flexible in case of strategic shifts and/or changes in consumer behavior.
