Consumer research models lag as AI and hidden influencers drive purchases: Report

Consumer intelligence is undergoing a shift as traditional research methods fail to reflect how purchasing decisions are formed today, according to a new report by Consumr.ai.

The report, titled ‘TwinSights: The Consumer Intelligence Trends Shaping 2026,’ says static consumer personas and post-campaign analysis are increasingly used to explain outcomes after they occur, while actual consumer behaviour has become fragmented, context-driven and spread across multiple touchpoints.

The report notes that consumer journeys are becoming less linear and more influenced by audiences that are not always visible to brands, as well as by artificial intelligence systems. As a result, insight models based on fixed assumptions are falling behind, it said.

Commenting on the report findings, Vivek Bhargava, Co-Founder, Consumr.ai, said, “We are witnessing a paradigm shift in the consumer research framework as predictive simulation, which marks a turning point for consumer intelligence. Instead of reporting on past outcomes, brands can now anticipate behaviour and test decisions in real time. That shift, from hindsight to foresight, is what meaningfully reduces decision risk, enabling brands to test creative, messaging, and strategic decisions before committing budgets.”

The report identifies several trends reshaping how brands understand consumers. It says people who influence purchase decisions are often not captured by standard targeting or attribution models. It also points to the growing importance of first-party behavioural data as third-party data becomes less reliable. Future growth will increasingly come from what it calls ‘invisible audiences,’ who often influence purchase decisions without being the final buyers.

These groups are likely to drive disproportionate growth and brand impact in 2026. 

According to the report, AI is also changing how consumers discover products and make decisions. Many consumers now rely on AI tools for guidance and recommendations, making it important for brands to understand how AI-generated responses shape trust and purchase intent. Consumers are increasingly turning to AI tools such as ChatGPT, Gemini and Perplexity for advice and recommendations, making discovery less neutral. The report introduces the concept of ‘Answer Engine Influence,’ which it says affects trust and purchase intent before consumers visit websites or see advertisements.

TwinSights also argues that consumer intelligence is shifting away from periodic research toward a continuous system informed by real behaviour and AI-based analysis.

As third-party data signals weaken, the report says first-party behavioural data is becoming more important. Brands that rely on observed behaviour are better positioned to influence decisions earlier in the consumer journey and to be interpreted accurately by AI systems that now mediate discovery.

The report concludes that consumer insight is no longer a one-time exercise tied to campaigns or annual planning. Instead, it is becoming a continuous system shaped by real behaviour, predictive simulation and AI-driven analysis. As 2026 approaches, growth will favour brands that can anticipate consumer behaviour rather than explain it after the fact.