How many CMOs can cite tangible examples of how AI drove business outcomes, either top line or bottom line? Probably not many. CMOs are already struggling to defend their department because they can’t demonstrate how their team generates revenue. Quantifying the impact of AI, much less establishing causal links between investments in marketing AI and business growth, seems like an impossible task.
This was the raison d’être of the Consortium for AI Personalization, an ambitious research project formed late last year by five marketers and the trade association MMA Global. With investment in AI growing, the group wanted to better understand how marketers can profitably deploy it—and at scale.
For their first pilot, the consortium used machine learning to personalize display ads for a new Kroger Co. grocery delivery service in the Florida market. The results?
After six weeks, Kroger’s web pages experienced a 259% surge in traffic, which translated to a 16% increase in sales. Based on MMA Global’s analysis of the data, if Kroger were to apply the same level of AI-powered hyper-personalization to all its digital marketing efforts, the company’s valuation could rise to 5%.
“This has changed and influenced our learning agenda for 2023,” Kay Vizon, media director for Kroger, told Adweek. “We want to continue to test and iterate and do [AI personalization] at an increasingly larger scale to really prove out the value of all this. If it’s still proving out, we would look to implement it across all our bigger initiatives.”
While personalization-driven marketing campaigns have historically performed well for Kroger in the past, the returns did always justify the cost of execution, Vizon said. Machine learning changes that.
“This was the first time we actually saw a big lift in performance and the first time we actually saw it play out in terms of business outcomes,” Vizon said of Kroger’s personalization campaigns.
To be sure, one pilot does not automatically translate into sustainable success. Some AI marketing campaigns will produce great results while similar ones might not. In the worst case, Kroger and MMA Global’s experience provides the consortium with a powerful incentive to keep testing and learning with AI. In the best case, however, it offers the groundwork for a powerful, flexible, new model for scaling AI. Here are three lessons that the team has learned so far.