This post was created in partnership with Monks
Key takeaways
- Marketing can be more predictable when data silos are broken down across teams.
- Consumers are still researching products, but in a different way.
- Even with AI efficiencies, human judgment remains critical for brands.
Keeping pace with consumers has become a demanding assignment for marketing teams. New tools give marketers more ways to create and test, while the speed of change keeps forcing them to reconsider how they work.
During an ADWEEK House Advertising HQ group chat co-hosted with Monks, industry leaders discussed how marketing and technology teams are adapting together.
Keeping up with change across tools and teams
When asked how teams are navigating changing consumer behavior, James Stephens, EVP of North America at Monks, acknowledged the strain of frequently rethinking how teams work.
Some things hold steady, like people’s natural desire to connect. But modern media consumption has accelerated “the speed at which we move on from things,” he added, which changes how brands communicate product benefits and hold consumers’ attention.
Whitney Magnuson, head of brand and media at Zoom, saw opportunity in that constant change. Zoom’s expansion beyond video conferencing into other products already required the company to reevaluate its marketing. And shifts in tools, behaviors, and discovery mechanisms now give marketers more permission to take big swings.
“I think there’s a lot more acceptance and willingness to go out and do something that would be unexpected for a brand in your specific category or industry,” Magnuson shared.
But inside organizations, change isn’t happening at the same speed everywhere, according to Eric Matisoff, principal evangelist at Adobe. Engineering teams can now build and iterate faster, while product marketing and product management often still work to catch up. That puts more pressure on colleagues to overcommunicate and proactively seek information.
Connecting data across teams is also critical. Nikolett Vilmos, head of marketing and AI transformation at Christie’s International Real Estate for Dubai, described bringing together previously siloed government transaction data, product information, and performance analytics. Campaign dashboards only reflect choices teams have already made, she said, so combining them with market and product data helps identify opportunities those choices may have missed.
When AI comes between brands and buyers
These shifts also require new education, Magnuson noted. For example, her team has had to explain declining website traffic in a zero-click environment to stakeholders outside marketing. She explained that consumers still research and arrive with greater purchase intent, even if that research no longer happens on the brand’s site. That changes how teams across the enterprise interpret demand and model conversions.
There’s a related change in affiliate marketing. Joe McCambley, CMO at Saatva, said large language models (LLMs) now recommend products directly, so shoppers skip affiliates. To adapt, his team has focused on schema, which lets them share unlimited product, pricing, FAQ, and review details. He also stressed that consistency across platforms matters. If schema pricing doesn’t match the page, or an affiliate describes a product differently, LLMs may distrust the brand.
Manny Flores, head of performance and AI at Ipsos, added that brands are losing control over distribution, which makes relevance more important than reach. Algorithms now build audiences from real-time behavior, so insights, media, and distribution cycles that once ran separately now overlap.
AI can make marketing more predictable, but not fully
The discussion then turned to whether AI can make marketing more predictable. Flores said faster learning and iteration can improve forecasts, while human behavior keeps complete predictability out of reach. “I think human behavior has an uncanny way of humbling large language models,” he noted.
McCambley argued that marketing is more predictable than most people think, but silos get in the way. When teams keep separate data sources and define terms like “revenue” or “conversion” differently, he said, AI can’t analyze that data in a way that supports predictions. The first step is consolidating data and agreeing on a shared dictionary of terms.
“Once you have a dictionary, you can’t write Shakespeare just because you have a dictionary,” McCambley explained. Shared definitions alone aren’t enough. Departments also have to explain how each one uses those terms, so AI can follow how teams actually work. That process can take a year or two, he said, but it can make a business surprisingly predictable.
Vilmos added that human judgment is essential. Well-known brands need people to remember them the right way, and that’s especially true in luxury. She explained that AI can generate a thousand personalized variations for different personas within minutes, but personalization alone isn’t enough. “It still needs to stay on brand,” she said, which is why keeping human judgment in the process is so important.
Data grounds AI, while experiences build brand advantage
When the conversation turned to data, Flores argued its value has only grown. “I think data’s never been more valuable because it’s the grounding that AI needs in order to perform,” he said. Synthetic data still depends on real human behavior, which keeps evolving, so marketers need an always-on read of real people.
Matisoff added that working with data and AI calls for a new skill: taste. “The people that I want to hire and work with should have good taste,” he said. That means recognizing quality, whether in an analysis, a campaign plan, or creative.
For Magnuson, though, the lasting advantage is an elevated brand experience. That’s why Zoom is investing in brand experiences, which people remember longer than an ad.
Featured Conversation Leaders
- Manny Flores, Head of Performance and AI, Ipsos
- Liz Kneebone, VP, Community Programs and Development, ADWEEK
- Whitney Magnuson, Head of Brand and Media, Zoom
- Eric Matisoff, Principal Evangelist, Adobe
- Joe McCambley, CMO, Saatva
- James Stephens, EVP, North America, Monks
- Nikolett Vilmos, Head of Marketing and AI Transformation, Christie’s International Real Estate Dubai
