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.
Marketing leaders pressured to adopt AI are discovering the primary obstacle isn't the technology, but their own internal data infrastructure. Siloed, inconsistently structured data across teams prevents them from effectively leveraging AI for consumer insights and business growth.
The differing styles of holiday advertising reflect distinct economic realities. The UK's focus on emotional, brand-building "mini-movies" contrasts with the US's faster-paced, transactional approach, which is driven by a more competitive, crowded market.
The perceived success of the emotional John Lewis ad is backed by data from Zappi. Viewers reported the emotion "love" at 44%, double the 22% norm for UK ads. This demonstrates that subjective emotional impact can be quantified and benchmarked against a large dataset.
The best use of pre-testing creative concepts isn't as a negative filter to eliminate poor ideas early. Instead, it should be framed as a positive process to identify the most promising concepts, which can then be developed further, taking good ideas and making them great.
AI in creative doesn't have to dilute a brand. Coca-Cola's successful holiday ad used AI, but its high brand recall (83%) was driven by focusing on iconic assets like Santa. The AI execution was effective because it was largely invisible, proving the creative idea still drives the ad, not the tech.