Opinion

Political advertising has always evolved alongside media consumption. But the shift from linear television to streaming has introduced challenges that campaign managers are still working to navigate. While connected TV (CTV) promises precision and flexibility, the reality facing political advertisers today is far more complex and less standardized.

Bold, accountable leaders who publicly embrace conflict and challenge industry fraud are essential to spark innovation in digital advertising and ad tech, writes Alessandro De Zanche.

Don’t ask whether any other company has created a similar product to yours; the answer is probably yes. But there are other ways to stand out.

Viewers aren’t just watching streaming content anymore; they’re living in it. And while they’re streaming, they’re telling us something important about how they want to experience advertising. They want to do more than watch; they want to engage.

The era of “managed decline” is over; the era of existential clarity has begun. Publishers are no longer guessing what the post-platform world looks like. We are living in it.

Programmatic media buying is expected to account for the majority of growth in the CTV market in 2026. This year alone, over 90% of CTV ad dollars were transacted through programmatic pipes. That data isn’t surprising. Programmatic has solved a real problem by helping brands reach TV viewers with targeted precision at much lower costs.

Unauthorized ID stuffing, rampant reselling and misaligned signals inflict incredible damage on the programmatic ecosystem. If publishers want to compete with the walled gardens, we must raise our standards. 

CTV isn’t an emerging channel anymore. It’s a fully established, essential part of the media mix. Advertisers now understand its reach, flexibility and ability to drive measurable outcomes.

AI shopping agents are breaking the traditional attribution loop. Marketers must ensure that AI is aware of their brand and track how that awareness influences ecommerce outcomes.

Almost everything in AI feels big. But are you looking at the next Gangnam Style or the birth of a new industry? Here’s how to assess whether an AI vendor is likely to matter in two years.

Marketers used to wait for obvious signals, like a product page view, a cart add or a keyword search, before triggering campaigns. But in today’s fractured landscape, those signals can arrive too late.

For years, MFA was a mostly web-based problem. Now, generative AI has supercharged the made-for-advertising model, and it’s infecting social media feeds and vertical video platforms.

Mobile apps are now at the center of the consumer relationship. They’re where customers browse, buy, stream, check balances and redeem loyalty rewards. However, app measurement remains one of the weakest links in modern marketing.

There’s a paradox at play in how marketers are adopting artificial intelligence.

Eighty-seven percent of US advertisers say they plan to increase AI usage over the next 12 months. But only 45% feel confident in their understanding of how AI-powered technologies work. That 42-point gap is an indicator of early friction in AI adoption.

Broadsign may actually be building a platform that will make an attractive acquisition target down the road. And one of the major cross-platform Big Tech players feels like the most likely buyer.

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.

Consumers don’t experience media in silos. They might stream a live game on their TV, scroll social feeds during halftime and research products on their mobile device later that night.

Confusion in CTV isn’t a natural byproduct of a maturing market; it’s an outcome of how distributors protect their pricing power.

The real challenge is drawing a clear line between the AI-generated content that adds value and the kind that erodes trust and leads to significantly lower ad effectiveness.

As the digital advertising industry enters a new phase of maturity, so does its relationship with data. Going into 2026, marketers’ long-standing obsession with scale is giving way to something more grounded: a push for smarter, actionable, owned data.

Social CPMs have risen. The ability to find incremental audiences on social platforms has declined. Add the growing brand-safety concerns, and the equation looks even worse.