Media planning has long focused on defining and reaching audiences at scale. That approach assumes stability in consumer behavior and media consumption.

That assumption is becoming harder to maintain.

Consumer behavior now moves fluidly across content, platforms, and screens. Someone researching recipes, watching holiday content, and comparing grocery options in a short time may not fit with a single segment. At the same time, the signals available to marketers have become more fragmented, particularly as identity-based approaches face limitations. Industry research, including Lumen Research’s 2025 report “The Attention Economy,” points to the importance of combining multiple signals to better understand engagement and improve outcomes.

Attention has become a more prominent metric in media evaluation. It indicates whether content is being seen and engaged with. However, attention alone offers limited context. It does not explain how interest is developing or what actions may follow.

Signal-based approaches are gaining traction. A 2025 FreeWheel survey found that 59% of advertisers say audience engagement signals would increase their interest in buying streaming inventory programmatically.

Signals reflect real-time behavior, including what consumers are watching, researching, and engaging with. Rather than assigning users to fixed categories, signal-based models interpret emerging patterns, offering an immediate view of interest and intent.

This shift is how campaigns are planned and executed, particularly around key moments of increased consumer activity.

During the 2025 holiday season, King’s Hawaiian, a US-based bakery brand known for its sweet rolls, focused on identifying behavioral signals tied to grocery planning and meal preparation. Instead of relying on predefined audience segments, the campaign aligned media activation to periods when consumers engaged with relevant content like recipe searches and holiday preparation.

This approach allowed the brand to connect with consumers as interest was building, rather than after it peaked. The result was measurable engagement and commerce activity, including click-to-cart interactions and increased purchase intent during key shopping windows.

This illustrates a shift in timing and interpretation, not format.

Planning is moving away from static audience definitions toward models that account for evolving behavior. Signals help understand that evolution, allowing marketers to identify when interest is increasing and where to engage.

Attention is important, but no longer sufficient on its own. Its value increases when paired with signals that explain what that attention represents and how it should inform the next step.

As media environments fragment and consumer behavior becomes less predictable, real-time signal interpretation will play a larger role in defining and activating audiences.