AI’s new role in marketing outcomes
Artificial Intelligence (AI) is often celebrated as the ultimate solution to advertising efficiency, helping brands plan better, work smarter and save time. It’s the headliner at every industry event and a hot topic in boardrooms. And so far, AI has proven a valuable asset in streamlining the planning process. But the next big question is: Can AI drive measurable impact after the planning phase has passed? And how could you possibly have enough data to measure every touchpoint and control for enough external factors to truly find out?
Quantify AI’s bottom line impact
Google sought to uncover the bottom line impact of their latest AI-powered solutions across YouTube and Search by putting them to the ultimate test: measuring over 50,000 brand campaigns and over 1 million performance campaigns in the U.S. across their AI tools.
AI’s unproven track record
Measuring the performance of AI-powered solutions is a new challenge in the marketing ecosystem. Google needed a measurement solution that could isolate the distinct impact of AI from manual campaigns and also access rich category-level data to effectively capture their wide campaign footprint. In order to prove whether AI-powered solutions moved the needle on return on ad spend (ROAS) and sales effectiveness, they needed a marketing mix modeling (MMM) solution with the ability to answer their research questions robustly.
Connecting the dots on performance
Google’s over 50,000 brand campaigns and over 1 million performance campaigns, controlled for external factors, and used advanced modeling techniques to aggregate digestible and accurate insights. Due to Nielsen’s extensive data categorization and data partnerships, Nielsen was able to provide the deep cuts of data needed for granular and speedy analysis.