Don't treat evals as a mere checklist. Instead, use them as a creative tool to discover opportunities. A well-designed eval can reveal that a product is underperforming for a specific user segment, pointing directly to areas for high-impact improvement that a simple "vibe check" would miss.

Marketers should use AI-driven insights at the beginning of the creative process to inform campaign strategy, rather than solely at the end for performance analysis. This approach combines human creativity with data to create more resonant campaigns and avoid generic AI-generated content.

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.

Foster a culture of experimentation by reframing failure. A test where the hypothesis is disproven is just as valuable as a 'win' because it provides crucial user insights. The program's success should be measured by the quantity of quality tests run, not the percentage of successful hypotheses.

Creativity thrives not from pressure, but from a culture of psychological safety where experimentation is encouraged. Great thinkers often need to "sit on" a brief for weeks to let ideas incubate. Forcing immediate output stifles breakthrough campaign thinking.

One-off creative hits are easy, but replicating them requires structure. Truly creative marketing integrates storytelling into a disciplined process involving data analysis (washups, SWAT), strategic planning, and commercial goals. This framework provides the guardrails needed to turn creative ideas into repeatable, impactful campaigns.

Instead of asking an AI tool for creative ideas, instruct it to predict how 100,000 people would respond to your copy. This shifts the AI from a creative to a statistical mode, leveraging deeper analysis and resulting in marketing assets (like subject lines and CTAs) that perform significantly better in A/B tests.

Brands miss opportunities by testing product, packaging, and advertising in silos. Connecting these data sources creates a powerful feedback loop. For example, a consumer insight about desirable packaging can be directly incorporated into an ad campaign, but only if the data is unified.