Prema Sampath, Group Product Manager at Google, leads a product team that develops measurement applications for brand advertising, including third-party privacy-focused solutions for YouTube ads.
Stephen Mangan is an ROI Measurement Manager at Google, leading research and measurement partner activations to help advertisers improve their media optimization strategies.
Marketing mix models (MMMs) help marketers make apples
To-apples comparisons across all their different gambling data vietnam investments. They provide answers to questions like: What drove sales? What was my ROI? How do I optimize my marketing spend?
But determining ROI requires more than a single calculation. Today’s media landscape is becoming increasingly fragmented and intertwined, presenting MMMs with an unprecedented challenge in predicting future performance.
To make sense of MMM, advertisers often defer to the link building also links websites technical expertise of their measurement vendors. But there’s more to measurement strategy than the science behind the model. Incorporating business context to shape MMM is an art—one with implications for model results and final recommendations. Advertisers who embrace that art can empower their businesses to make more strategic, measurement-driven decisions.
►Start with granularity
Remember that impressions are not equal across all platforms whatsapp filter or even within them. When it comes to video-specific measurements, MMMs will evaluate all of your impressions, but platforms can vary widely in terms of watch time, viewability, and audibility. The same data can produce very different results depending on how it’s fed into the model. Research we commissioned from Nielsen shows that when MMMs for CPG brands evaluated individual video platforms rather than aggregate data, return on ad spend (ROAS) varied by as much as 48%.
Ad formats can vary just as widely. On YouTube, for example, ads can range from non-skippable 30-second videos to a 6-second bumper ad. While both formats can generate ROI, the cost and effectiveness of your impressions won’t be the same.
So make sure you leverage more granular data from your publishing partners, and your model will be able to identify the respective value of different impressions. As with any model, MMM has limits. But each layer of granularity will lead to more informed business decisions.
►Add business context
MMM science can tell you what your ROI was, but it can’t tell you why without context. Getting granular data at the format level is a start, but formats are only one driver of ROI. According to Nielsen Catalina Solutions, creative accounts for 47% of video ROI, yet MMMs aren’t designed to evaluate individual creative assets.