Design with AI in mind

The approach Kroger and the MMA team used for this test—dynamic creative optimization, or DCO—personalizes ads based on the specific consumer viewing the ad. Inputs such as geolocation, weather, electronic device, shopping habits and browsing history help create ads that are more relevant and targeted—and often outperform traditional static ads, which appear the same no matter who is viewing them. When you add in AI, the results can be extraordinary, as Kroger and MMA discovered.

But few marketers design with AI in mind. The process typically goes something like this: Marketing teams develop a creative brief for their agency, the agency creates multiple versions of an ad to be placed in different locales and for different consumers, and then the conversation about how to execute hyper-personalized campaigns using AI begins. One success factor of the Kroger experiment is that the designers designed with AI in mind and for diversity of message.

The ads not only featured subjects from diverse ethnic backgrounds but also different design concepts. One ad featured a refrigerated delivery truck, while another showed a delivery person carrying a bag of groceries. Briggs and Vizon said the team wanted the ads to look and feel different and speak to different people with different motivations.

“The creative process is different—and more effective—when you are designing with AI in mind from the very beginning,” Briggs said.

Embrace imperfect data systems

Most marketing leaders know they need to scale AI technology to stay competitive, but too many of them fail to move beyond the experimentation stage. MMA Global research indicates that this failure has little to do with the complexity of the technology itself. Few companies have built a robust business case for AI (only 19% have), the ownership of the AI vision and strategy is fragmented and AI is built on imperfect data systems.

While free-flowing data unencumbered by departmental silos is a key success factor for any data-driven organization, marketers can still make progress even before they have all their data and cleaning processes nailed down.

As Briggs explained, often companies delay the financial benefits of AI by thinking they need to have everything in place. In fact, AI personalization doesn’t require any data besides what comes in from regular digital advertising and a KPI (e.g., visiting a web page or buying something online or via an app).

For Kroger’s part, there is a need to both embrace the imperfect and exercise caution at the same time. “AI is already here,” Vizon said. “We’re going to want to be at the forefront to understand its best applications and use cases. But as a part of that, we also want to understand its limitations and risks so that we could plan for it appropriately and put those guardrails in place.”