AI in Advertising Research

The Artificial Intelligence (AI) revolution in advertising will have a seismic impact on how ads are created and effectiveness is measured, bringing about significant reductions in production and research costs. Yet without considered Human Intelligence (HI) these cost reductions could come at a price of creativity and effectiveness. 

The advent of Generative AI means that machines powered by models can now create text, audio, images, and video with human prompting, saving significant human labor time, in turn increasing productivity. AI tools also improve the speed and cost of measurement, with Analytical AI models able to create a near real-time cycle of creation, measurement, selection and optimization of the most effective ads.

The pursuit of these AI productivity gains, in both advertising development and measurement, also poses a risk to the soul of advertising as we know and love it.

But for all the productivity gains they may bring, AI tools also introduce the risk of drops to creativity – and by extension drops to effectiveness in terms of sales lift and market share growth. 

Using insights from our AI ad evaluation solution Creative|Spark AI, we explore these risks and outline a vision for how AI ad evaluation tools can be more connected to human creativity, used more widely in advertising research, and in turn, help brands to get to more effective advertising. Read more about: 

• Why AI models risk falling short of the MISFITS approach and undervaluing empathetic experiences and unique ideas and thinking. 
• How Human Intelligence (HI), advertising research expertise and leading-edge Generative AI processing can help AI models bridge the creativity gap, leading to increased prediction accuracy of human responses. 
• When it’s appropriate to use AI models – even with HI improvements – based on based on the media investment risk and strategic campaign direction. 
• How HI and AI will work together, complementing each other to evaluate more ads and support more business decisions to drive effectiveness.

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