Onstage and off- at the three-day event, media agency execs discussed the potential of machine learning and generative AI. However, they also confessed to plenty of healthy skepticism.
AI gives answers, but not always the right ones, said Marilois Snowman, founder and CEO of media services agency Mediastruction and SaaS platform FutureSight. Speaking onstage about media mix modeling, Snowman said AI can help extract, transform and load data faster and more efficiently. But she pointed out it's important to use tools judiciously to make sure the outputs are accurate.
"We're still thinking more about machine learning algorithms because we can understand how they got to the answer," Snowman said. "These outputs are only as good as the data that they're given, so if we want to understand where things went awry we're following the margin of error of what our models are forecasting and what's actually happening. And if we're finding that margin of error is just not improving, with ML models we can better understand why that is."
In a keynote conversation that kicked off the summit, Kamran Asghar, CEO and co-founder of independent media agency Crossmedia, said clients are eager to test new AI tools for media buying, insights and content creation.
"We use AI in some predictive modeling in order to understand where our next best dollars should be spent once we have evidence that things are working," Asghar said. "So having it by your side, but not be the end-all be-all is the standard step."
There's also the challenge of potential platform bias with AI tools. Asked about the revelations from the Google ad tech antitrust case, Snowman said lost trust creates a problem for measurement: "We have to play in their sandbox -- pun intended -- but we don't have to rely on them for measurement," she said.
Warnings against over-relying on automated ad-buying was a key theme throughout the summit. Tucker Matheson, co-founder of the digital strategy firm Markacy, said the past decade of digital media has created a bias toward platforms. Large advertisers have the resources for media mix modeling but that's not always the case for smaller brands. Matheson also it might not be wise to anchor media budgets based on what platforms provide in terms of traffic acquisition costs or return on ad spend.
"It's just so easy to get into Meta and Google and see the data and click buttons," Matheson said. "Platform metrics still are important, but I think they need to be looked at a little bit differently. Like for us, we all know the proliferation of creative testing on Meta and TikTok. I think those platforms give you good click data to support creative testing."
(Coincidentally, Google this week also debuted new ad features for Performance Max and search campaigns including new ways to optimize campaigns and track performance. The updates for Google Ads API version 18 include new ways to query placement-specific data and content metrics for display, demand gen and video campaigns.)
Meanwhile, AI's growing presence in creative ad generation is being felt across the marketing spectrum. Balancing brand voice and accuracy is key for customer-facing uses of AI, said Kevin Rettig, Marriott's senior director of marketing platforms & privacy. In a conversation about personalization, Rettig mentioned Marriott hasn't done much yet with generative AI ads. However, it is experimenting through a recently rolled out virtual assistant powered by ChatGPT and open-source outlets. Another challenge is maintaining brand voice across the hotel giant's dozens of brands that each have their own brand voice.
"When you think about AI and content generation, each brand is very protective of what their brand voice is," Rettig said. "We have to balance that with the automation and someone else writing or doing the creative piece. I'm not saying we wouldn't do it and I think all brands have that sensitivity, but with 30 brands that really feel their brand voice is unique, we have to be really mindful of that too."
Outside of AI, the hotel giant is exploring plenty of ways to personalize marketing through its Bonvoy loyalty program and other data sources, said Rettig. He noted the company uses first-party data to understand customer hotel preferences, power targeted promotions and enable ads bought through the Marriott Media Network. While Marriott is exploring ways to expand its data pool through third-party data sources and clean room partnerships, it also uses data verification tools like Neutronian and Truthset.