Extensive behavioral research on ad performance reveals a clear pattern: simplicity is superior. Creatives with multiple storylines, clutter, and excessive detail create cognitive load and reduce effectiveness. The best-performing ads feature a single, clear message that is easy for the human brain to process quickly.

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The debate over ad "quality" is often based on subjective opinions of brand fit. A more effective definition of quality is its ability to achieve the primary business objective: selling the product. Unconventional creative that drives sales, like Olay's "cat with lasers" ad, is by definition high-quality.

The true power of AI in marketing is not generating more content, but improving its quality and effectiveness. Marketers should focus on using AI—trained on their own historical performance data—to create content that better persuades consumers and builds the brand, rather than simply adding to the noise.

Relying solely on data leads to ineffective marketing. Lasting impact comes from integrating three pillars: behavioral science (the 'why'), creativity (the 'how' to cut through noise), and data (the 'who' to target). Neglecting any one pillar cripples the entire strategy.

Contrary to the belief that messaging should be universally simple, Hexagon discovered that using specific, technology-oriented terms led to higher user engagement, dwell time, and click-through rates. This suggests users prefer concrete language over vague, high-level concepts, even if not every term is relevant to them.

AI can now analyze video ads frame by frame, identifying the most compelling moments and justifying its choices with sophisticated creative principles like color theory and narrative juxtaposition. This allows for deep qualitative analysis of creative effectiveness at scale, surpassing simple A/B testing.

Stop treating content as a purely artistic endeavor. The most successful creators apply rigorous scientific testing and investment to creative elements like thumbnails. They understand 'the science of the art,' using data to ensure creative work performs, rather than relying on trends or intuition.

Conventional engagement metrics like likes and shares are often misleading. A more valuable indicator of content quality is dwell time. In an environment where users can easily skip content, their choice to spend more time with an ad is a powerful behavioral signal that the message is resonating.

Imposing strict constraints on a creative process isn't a hindrance; it forces innovation in the remaining, more crucial variables like message and resonance. By limiting degrees of freedom, you are forced to excel in the areas that matter most, leading to more potent output.

Human vision has two modes: sharp central focus (foveal) for details like text, and wide peripheral vision that scans for general signals like shape, color, and movement. Since peripheral vision detects things first but cannot read, visual marketing must grab attention with imagery before communicating details with text.

Traditional ad testing relies on surveys, which are unreliable as respondents may not be truthful or self-aware. A more predictive method is to measure actual consumer behaviors like attention and emotional response using neuroscience and AI. These are more direct indicators of an ad's potential sales impact.