Opinion

CTV spending is flattening, performance is plateauing and buyers are hesitant to push budgets further. The reason is not complicated. When buyers cannot see what they are buying, they cannot commit their spend with conviction.

As artificial intelligence transforms advertising analytics, many organizations are rushing to adopt AI tools, hoping for a “magic button” that instantly democratizes data access.

Performance marketers are turning to AI to navigate rising costs, data loss and increasingly complex shopper journeys – and it’s working. Creative is more personalized, targeting is sharper and optimization happens in real time.

Generative AI is the new ad land obsession: a shiny promise of a fully autonomous world of self-driving advertising.  But behind the hype lies the costly delusion that automation can replace judgment and more content somehow means better marketing. We’ve entered the age of machine-made abundance, where content can be generated faster than it can […]

Take a moment to think about how your day sounds. Maybe you start with the sound of your alarm, followed by a quick news briefing from your smart speaker while you scroll through emails. Your favorite podcast keeps you company during your commute. Your to-go playlist helps you get in the zone at the gym.

With privacy under unprecedented attack by data brokers and social media, it is the wrong time to weaken CIPA’s private right of action protections, as has been proposed in California Senate Bill 690.

AI has raised the bar for what qualifies as “good data.”

The conversation is no longer about how much data marketers can collect but how well that data reflects reality. In this new era, success depends on data that is accurate, fresh, consented and interoperable – principles that ensure AI models learn from accuracy.

When it comes to complex techniques like media mix modeling, the field is awash with false promises about the benefits that AI can offer.

Every conversation about addressability eventually lands on the same word: fragmentation. But the real symptom of that fragmentation isn’t just operational complexity; it’s also declining match rates. That single number explains why marketers are struggling to make their data work.

Most of what’s sold as “contextual” today still runs on the same keyword logic we used a decade ago. The industry didn’t reinvent contextual targeting; it simply replaced one keyword with a cluster.