The integration of generative artificial intelligence into the market research sector is profoundly redefining the industry's methodologies and business models. Clément Fages recently published a detailed analysis of these transformations, a summary of which we offer here, enriched by our own reflections.
Six key dimensions of transformation
1/ Process Transformation
AI enables large-scale data processing, radically changing our approach to focus groups and verbatim analysis. This ability to extrapolate and query data opens doors to new ways of gaining insights.
2/ From correlation to causation
One of the holy grails of research is to move from simple correlation to causality, with an even greater ambition for prediction. AI brings us closer to this goal, enabling deeper and more predictive analysis of behaviors.
3/ Limitations of AI
Despite its advances, AI cannot predict randomness or generate disruptive ideas on its own. The most valuable insights often come from irregularity and unpredictability, areas where human intuition still plays a crucial role.
4/ Impact on business models
Tools like Ogilvy's BrAInjuice challenge the traditional need for costly and time-consuming focus groups. How should research institutes evolve to remain relevant?
5/ The crucial role of human expertise
Expertise in formulating questions and interpreting data in context remains essential. The real added value lies in our ability to combine human skills with the power of AI.
6/ Collaboration between AI and humans
The future of market research lies in a synergy between AI and human expertise, maximizing the strengths of each to deliver deeper, more strategic insights.
Our analysis
- A legitimate question arises regarding the new added value of research institutes (historically, it was the field of study that created the value, but this has been automated and then the analysis is beginning to be replaced; what remains is expertise).
- Communication agencies that have neglected studies have the opportunity to integrate this function
- A cautious stance on the use of virtual profiles in qualitative research, except perhaps for opinion issues which are more easily modeled than feedback (self-administered data is very complementary to AI).
- The concept of augmented creative intelligence allows us to evoke the dialogue between humans and machines:
Augmented creative intelligence. How does dialogue with AI enrich the human creative process?
- There is also much to be done in "desk research" with AI tools which not only have a capacity for synthesis and extraction but also a library of methods, concepts, models, ideas, stories…
To learn more:
No responses yet