In a media ecosystem defined by velocity, variability and vast amounts of noise, one thing has become increasingly clear: Attention is the new currency. Not impressions. Not clicks. Attention.
Once upon a time, viewability reigned as the gold standard for campaign effectiveness. If an ad was seen, it counted. But today’s marketers are realizing that simply being seen is no longer enough—it’s about how long and how deeply consumers engage. Enter attention metrics, the rising star of advertising measurement. And with the growing adoption of artificial intelligence (AI), the ways we define, generate, optimize and measure attention have shifted dramatically.
From Viewability to Veracity: The Rise of Attention Metrics
Attention metrics provide a richer, more behaviorally grounded lens for evaluating ad impact. Rather than relying on whether an ad merely entered the viewable window, attention metrics dig deeper: How long did a user linger? Did they hover, scroll, click or swipe? Did they turn the sound on or pause to absorb the message?
This nuance reflects a more accurate proxy for real-world impact and brand resonance. But capturing, interpreting and acting on these data points requires more sophistication than ever. This is where AI comes in—not just as a tool but as a force multiplier.
Creative Iteration Meets Generative AI
Speed and scale are the enemies of traditional creative production. In a programmatic world—one where, according to eMarketer, 90% of display advertising budgets worldwide will be programmatic by 2026—we need more ad variants than ever. Creative fatigue is real, and audience expectations for personalization are higher than ever.
Generative AI transforms how we approach this challenge. With the right training data and brand guardrails in place, marketers can now use AI to spin up dozens or even hundreds of creative variations. These aren’t just cosmetic tweaks. AI can tailor everything from color palettes to messaging tone to visual storytelling—each aligned to specific audience segments, contextual cues and performance signals.
What once took weeks now takes minutes. More importantly, we can test and iterate faster, which leads us to the next evolution.
Optimization in Real Time With Predictive AI
The magic doesn’t stop at generation. Predictive AI enables us to actively monitor performance across attention metrics and course-correct on the fly.
Imagine serving an ad variant and seeing it start to underperform in terms of scroll depth or time-in-view within hours. Predictive models, trained on historical and real-time data, can pinpoint what’s not resonating—maybe it’s the call-to-action or the background imagery—and automatically recommend or implement changes to optimize results.
This level of agility transforms static campaigns into living systems, constantly learning and adapting to drive incremental lift.
Measurement Reimagined
Perhaps the most profound impact AI has had is in the realm of measurement. Attention is inherently qualitative—something we used to think of as abstract or anecdotal. But AI allows us to quantify it in meaningful, scalable ways.
Computer vision models can analyze how users interact with video content frame by frame. Natural language processing can evaluate sentiment and engagement across social comments. Sensor data from mobile devices can feed into models measuring tactile engagement, like tilts, taps or dwell time.
This level of measurement granularity empowers marketers to correlate creative features with business outcomes. What kind of motion graphics actually lead to more conversions? What brand tone inspires longer engagement?
With AI, we’re not just guessing anymore. We’re modeling.
Practical Tips for Marketers
- Start With the Right Data Stack: AI thrives on good data. Ensure you have unified access to attention signals from media platforms, user behavior and CRM systems before diving into modeling or generation.
- Test, Don’t Assume: Use AI to create variants, but don’t just pick the one that “feels right.” Let performance data, especially attention metrics, drive your decisions.
- Build Feedback Loops: Design systems that allow AI models to learn over time. Train on your own brand data. Continually optimize creative and targeting based on real-time outcomes.
- Blend Human + Machine Creativity: AI can generate ideas, but it’s human insight that sets the strategic vision. Use AI to augment, not replace, creative teams.
- Think Holistically: Attention is not just a media metric but also a proxy for brand strength, message relevance, and creative quality. Align your KPIs accordingly.
Final Thought: It’s About the Right Attention
Attention metrics are only as valuable as the insights they unlock. We don’t just want people to watch an ad: We want them to remember it, to act on it, to talk about it.
AI is redefining how we understand, design and optimize for attention. It’s about what was seen and about what made someone pause, engage and connect. Marketers who use AI to translate attention into insights and insights into action will set the pace for what modern marketing can achieve.
Scott Blessman is the VP of Analytics and Insights at Goodway Group.
Network
