Observed Signal · Oct 26, 2026 · Market Signal · Source: Neurons · Impact: 2/5
The New Rules of Creative Effectiveness: 5 Myths, Put to the Test
Kantar and Neurons test five creative effectiveness myths. Discover what drives brand impact, sales, and creative bravery, plus how to use predictive AI.
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Consistency beats novelty: creative drives brand growth
Kantar, in partnership with Oxford Saïd Business School, presented findings from 'Creative Consequences' at Cannes showing that high-quality, consistent creativity is a major driver of long-term brand growth. Speakers from Kantar, Mars's Royal Canin and Oxford Saïd outlined a two-way relationship: great advertising strengthens brands, and strong brands enable better creative performance. The research warns that frequent agency changes often break creative momentum (only ~30% lead to improvement when changed) and cautions against using generative AI to scale low-quality content. Panelists emphasized that creativity accounts for roughly 70% of advertising effectiveness versus 30% for media buying, and recommended prioritizing creative consistency over chasing novelty.
Real-time systems redefine creative marketing
At Cannes Lions, executives from Monks argued that real-time marketing systems — not simply volume-driven generative AI — are reshaping how brands create and optimise creative. Monks leaders (Henry Cowling, Sneha Ghosh, Bonnie Preece) told The Drum that continuous data ingestion, performance learning and tighter integration between creative and data teams produce more relevant, purpose-specific assets. Amazon Ads’ Lauren Anderson framed AI as a tool, not a replacement for human creativity. The article highlights Monks.Flow, which predicts creative performance for algorithmic feeds, and notes Monks’ collaboration with Amazon Web Services and Amazon Ads to build a cloud-based marketing operating system that combines generative creative, infrastructure and precise media delivery. Key organisational challenges remain: breaking silos between data, media and creative, and adopting rigorous testing to convert AI-driven variants into meaningful learning and business outcomes.
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