Data clean rooms have become a major topic of discussion amid ongoing regulatory changes and evolving industry policies. As advertisers navigate these shifts, it’s important to take a step back and understand what’s available – and how to select the right partners to solve real business challenges.
Advanced and generative AI are transforming marketing from fragmented workflows into an engine of profitability and growth. Yet, despite AI’s promise, many in marketing remain trapped in outdated systems that fail to deliver.
The next wave of the boom isn’t going to come from the same online corners as it has over the past five years.
The need for addressability has been a rallying cry among advertisers for the past five years. But clinging to outdated notions of addressability means overlooking the broader needs of today’s modern media landscape.
Amid shifting habits in media consumption, live sports have demonstrated significant staying power. Over the past five years, the NFL has consistently claimed at least 70 of TV’s top 100 telecasts, and 2024 saw record-setting viewership for major sports events like the Olympics and MLB World Series.
Once considered the “old reliable” next to programmatic advertising, contextual targeting is having a resurgence – and this time, it’s powered by AI. AI is redefining how contextual targeting works, making it smarter, more scalable and more effective. And the timing couldn’t be better, as marketers navigate a landscape increasingly shaped by privacy regulations and the demand for relevance.
I’ve spent nearly a decade in marketing mix modeling (MMM), and I can tell you this: MMM starts with the model and proves itself in product and growth. An MMM without growth is like a car without fuel; it simply doesn’t work.
If the past few decades have proven anything, it’s this: Consumers and businesses expect constant innovation, and brands must evolve or perish. Mediocrity won’t cut it. That’s where AI can help, even if it brings a sense of uncertainty.
As the lines between the gaming and non-gaming worlds continue to fade, gaming publishers are unlocking a massive opportunity: non-gaming advertisers. We’re already seeing a surge of in-app advertising (IAA) spend from non-gaming advertisers, but we’re about to see the flood gates opened by a major tech innovation: modern machine learning (ML) algorithms that turbocharge the formerly slow, resource-intensive and relatively unscientific process of finding audience overlaps.
The last five years saw our industry’s conventional models of ad targeting and measurement evaporate with the regulatory and cultural shift toward privacy. But out of these ashes, the advance of clean room architecture is enabling a deeper level of measurement and insights, which is moving us toward something much better than ever before.
