StackAdapt, the leading AI advertising and orchestration platform, has released its annual State of Programmatic Advertising 2027 report. The research finds that top-performing marketers are taking on more complexity than their peers and managing it more effectively. They are expanding across channels, data, measurement and AI while keeping those capabilities working together, with connected customer data emerging as a key performance driver.
Based on a global survey of 885 senior marketing and advertising professionals in addition to anonymized StackAdapt platform data, the report defines top performers as marketers reporting significantly stronger year-over-year performance. Leading marketers are taking on more channels, data, and measurement while reducing fragmentation.
"More channels, better customer data, and AI are expanding what marketers can do, but they're also making marketing more complex," said Ryan Nelsen, CMO of StackAdapt. "Our research shows that the strongest performers are making those moving parts work together more effectively."
Measurement is one area where that coordination pays off. Only 7% of marketers say they have a fully unified measurement strategy, and most are using several methodologies at once. Marketers using cross-channel attribution report stronger year-over-year performance than non-users at 75% vs 60% and greater confidence connecting ad investment to results at 66% vs 47%.
The research also shows that marketers are investing in reach. Eighty-three percent have added channels to their marketing mix over the past two to three years. The opportunity now is coordination: 10% say they almost always run truly omnichannel campaigns, and 42% estimate that more than 20% of their programmatic budget is wasted because of siloed or fragmented channel execution, rather than the channels themselves.
At larger budgets, the challenge shifts from access to alignment. According to StackAdapt platform data, advertisers spending more than $10 million annually are more likely to use measurement capabilities at 69% vs 56% and adopt a broader set of platform features. High-spend marketers cite organizational silos at 28% vs 16% and technology limitations at 23% vs 17% as barriers to omnichannel strategy more often than mid-spend marketers.
Connected customer data is emerging as a clear performance divide. Only 45% of marketers say their first-party customer and prospect data is mostly or fully connected across acquisition, conversion, and retention. Among those marketers, 74% report stronger year-over-year performance, compared with 59% of marketers with less connected data.
Connected data and measurement also shape how much value marketers get from AI. Among marketers with mostly or fully connected customer data, 79% say AI has improved cross-channel coordination, and they agree that AI only delivers value when the underlying data and measurement are connected and trusted.
"Marketers are navigating a rapidly shifting media landscape defined by channel proliferation, greater access to data, and expanding AI capabilities. Yet the challenge has moved beyond gaining access to these resources to integrating them into strategies and systems that improve decision-making," Jacob Bourne, Analyst, Technology, EMARKETER. "StackAdapt's research highlights where that transition is creating friction across media, measurement, data, and operations, and why coordination will be an essential capability for marketers heading into 2027."
Looking ahead to next year, the report identifies four priorities for managing growing complexity: connecting customer data across the lifecycle, coordinating execution across channels, establishing trusted measurement practices, and aligning teams and workflows.
About StackAdapt
StackAdapt is the leading AI advertising and orchestration platform marketers rely on to drive brand growth and revenue. Built entirely in-house with an easy-to-use interface, StackAdapt unifies programmatic and owned channels—including CTV, DOOH, display, native, audio, email, and more—into one seamless experience.
