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Marketing has long been more art than science. Conventional wisdom was that thoughtful, engaging creative mixed with the right media plan would lead to revenue growth for the brand.
Today, artificial intelligence is beginning to measure what marketers once considered intuition. Through creative-scoring systems, predictive heatmaps, and attention modeling, AI can analyze the emotional and visual mechanics of an ad and estimate its effectiveness before launch. This data is transforming the creative process, allowing teams to test dozens of variations and learn from near-real-time feedback.
Yet the deeper value lies not in automation but in reflection: AI reveals the hidden patterns of human attention and preference, teaching creators how audiences actually experience their work. The new creative brief is no longer a hypothesis, it is a living model continuously trained on performance.
Modern advertising has already taken some steps in this direction. Most brands know that they aren’t trying to reach the audience, but the right audiences. Brands don’t have a single monolithic customer base, but instead have different core groups that may be interested in a product or service. The complicating factor is that each of these groups may respond differently to creative messages.
For example, tourism organizations may be looking at many very different types of vacation preferences. There are people looking to be active and explore, people looking to sit by the pool, or families that have a variety of needs and interests. Each of these audiences might need different creative. There will likely be different campaign flights. And they may even have different campaign outcome goals. Executing a campaign with this much sophistication kind requires a lot more than intuition.
This is where AI is likely going to lead to major change across the ad industry. It’s now possible to calculate an ad’s cognitive ease score before it runs, as well as while a campaign is in flight. What’s a cognitive ease score? It’s a metric capturing how easy it is for the audience to to focus on or understand what’s happening within the creative, where AI simulates where a consumers’ attention will go within the creative.
These scores could be used to fine-tune the creative messaging to maximize engagement and overall campaign efficiency. Changes could range from something as simple as making a logo larger, down to more nuanced adjustments, like changing the mood of the ad.
At its core, this is not a new tactic, but something advertisers have been pursuing for decades. Advertisers have developed many different ways to stand out from the noise and capture attention, ranging from higher volume TV commercials, pop-up ads, animated billboards, and forced video views. The unfortunate thing is that all of these tactics create more noise. Consumers learn to tune them out in time, forcing advertisers to come up with new attention-grabbing ideas.
Consider a forced view pre-roll ad. A brand may know that they are getting 98% view-through on these, but that stat isn’t actionable. Yes, 98% of the audience may have sat through the ad, but it’s possible that 100% of those who saw it immediately forgot the message, or were never aware of it in the first place. What matters is how the ad was understood and if it drew any engagement.
AI shows advertisers how well an ad is understood and which components within the creative are going to appeal to the needs and tastes of the target audience. In short, it’s dropping the attention grabbing gimmicks and instead learning what makes messages that are clear, easily decipherable, and appealing. This is only scratching the surface of what’s possible when it comes to understanding the nuance of how ad creative is perceived and embraced.
Going forward, this kind of measurement can be brought into advertising’s emerging frontiers as well. Creative scoring can be applied to things like creator media, where creators have a sense of what their audience likes and how different brands, products, and ad creative will resonate. This scenario actually combines creator intuition with AI heatmapping to open the door to performance predictability.
Perhaps best of all, this use of AI has the potential to change perceptions about advertising itself. Ads that appeal to consumer taste aren’t really about pushing a product, but about helping the audience discover something new. When the message is combined with the credibility of a trusted creator, it increases the possibilities of high-performing creative.
