Using the data generated by the persona, Flores shared that the team was able to pinpoint when and where it was most effective to deploy push notifications and discount codes to increase the chances of conversion. AI can then apply a layer of personalization to ensure the tailored messaging based on past consumption patterns is seen.

That level of targeting and nuance, powered by autonomous AI decision-making, creates an end-to-end experience design that feels intuitive to the consumer. But, Flores noted, the learnings a brand can get from experimenting with synthetic personas are only as good as the data driving them.

Designing backward to achieve business outcomes

The discussion ended with a reality check on the guardrails and strategy required for autonomous AI marketing systems to succeed. Most importantly, Flores argued, brands should define desired results and design backward, building systems that allow their team members to focus on the pieces of the work that need deep focus, collaboration, and human expertise.

“When it comes to using AI for that collaboration, you need to sit down with all those different campaign stakeholders in the room and say, ‘OK, here’s the 80% of stuff that none of us here want to do. How can we put that on autopilot so that the rest of the time we can focus on that 20%?’”

 “It’s about actually having the time to focus on the things that matter that make a difference in your day-to-day,” he continued.

And staying realistic about a few targeted goals may be more effective than doing everything at once, he added.

“Just because AI is hyper-intelligent, it doesn’t mean that it’s going to solve every single problem you have,” he said. “So my biggest advice is have a purpose for why you want to use it.”