{"id":7435,"date":"2026-09-17T08:43:21","date_gmt":"2026-09-17T08:43:21","guid":{"rendered":"https:\/\/borderlessaccess.com\/blog\/?p=7435"},"modified":"2026-09-17T08:44:41","modified_gmt":"2026-09-17T08:44:41","slug":"ai-concept-testing-research","status":"publish","type":"post","link":"https:\/\/borderlessaccess.com\/blog\/ai-concept-testing-research\/","title":{"rendered":"Modernizing Concept Testing in the AI Era: What Really Works for Insights Professionals"},"content":{"rendered":"Reading Time: <\/span> 6<\/span> minutes<\/span><\/span>\n

The gap between what a consumer thinks and what they feel is where most product concept testing goes wrong.<\/em><\/p><\/br>\n\n\n\n

Here is something that should make any brand strategist uncomfortable. According to a recently published report in the Journal of Consumer Psychology<\/em><\/strong>, consumers can give positive feedback to a concept that has no genuine impact on their purchase intent, and negative feedback to a concept that would have driven real behavioral change. The rating scale and the purchase decision are, more often than we admit, operating on different frequencies.<\/p><\/br>\n\n\n\n

This is not a new observation. It has been quietly understood in research circles for years. What is new is that the tools to bridge this gap have finally arrived at commercial scale, and the brands moving fastest to adopt them are redefining what concept testing<\/a> can actually deliver.<\/p><\/br>\n\n\n\n

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