The use of open AI in marketing research is greeted with suspicion or skepticism by some, but also enthusiasm by others. This is clearly the case for ActFuture founder Isabelle Fabry, for whom we are witnessing the beginnings of a genuine revolution in the insights-hunting business. And she’s proposing new approaches based on a marriage – a fusion – between the most classic qualitative research techniques and AI. She presents them to us and shares her convictions.
MRNews: In every professional sphere, artificial intelligence arouses contrasting attitudes and often fears. What’s your view? Should we be afraid of AI?
Isabelle Fabry (ActFuture): For my part, I’m really into the « Go! » of AI usage, which I’ve integrated into my daily life. This includes finding new cooking recipes or optimizing my own (laughs), but above all as a marketing research professional. Quite simply because these tools enable us to go further and faster, and considerably open up the field of possibilities. Of course, there are fears, and I understand them. AI updates to the power of 2 or 3 the long-standing fear of the machine replacing man. Another major apprehension is that of seeing the development of behaviors that do not comply with ethical rules, whether universal or specific to a profession like ours. But when it comes to these issues, it’s perfectly possible to define a framework and respect it. It’s up to us, and there’s no reason, in my view, to deprive ourselves of such a brilliant tool. For the qualitativeist at heart that I am, I say to myself, now I can finally break out of the confines of craftsmanship, I’ve got a thinking, stimulating matrix, now installed in my workshop! And all this while retaining and even capitalizing on our fundamental expertise, which is strengthened and boosted thanks to this super « sparring partner ».
Is AI a « contribution » like many others in the history of marketing research? Or a real revolution?
I see it as an upheaval or revolution indeed, but one that is largely still to come. I don’t remember who said that people often overestimate the short-term impact of innovations, but underestimate their medium- to long-term impact. It seems to me that this applies very well to the case of open AI, which is a revolution of which we have so far only seen the beginnings. There is likely to be a huge gap between those who will get on board and those who will remain on the platform.
As you said, AI is already part of your business practices. You’re even proposing new approaches that incorporate it. What are they? To answer which questions?
The key principle is to « marry » and even « merge » the research approaches we traditionally use – based on group meetings or individual interviews – with AI. It’s certainly not a question of replacing human intuition, which remains « master on board » and is at the heart of our know-how. But to nurture and boost it, by enabling it to benefit from the speed and openness of AI.
The key principle (of our proposal) is to « marry » and even « merge » the research approaches we traditionally use – based on group meetings or individual interviews – with AI. It’s certainly not a question of replacing human intuition, which remains « master on board » and is at the heart of our know-how. But to nurture and boost it, by enabling it to benefit from the speed and openness of AI.
In fact, we’ve devised two distinct approaches, covering two different types of need. The first is to use ChatGPT to « increase » the number and relevance of insights generated during our group meetings. In practice, as we identify the insights generated by participants, we work on them in real time with ChatGPT, enriching them. Let’s say we’re working on the detergents of tomorrow, and consumers bring up the concept of detergents in sheet form. AI enables us to instantly grasp the points we need to explore with them, and in particular the conditions for success that need to be met. What used to take several hours, or even days, can now be done in a matter of minutes. And the client advertiser, who follows the live generation of insights, can also intervene and have the relevant signals examined in greater depth live.
You integrate into the group animation process an iteration between consumers and AI…
Absolutely! This means we can go much faster and much further than we would have been able to under the usual protocols. We’re not putting off until a later date – possibly in a second study – soliciting consumers to dig deeper into what needs to be done, we’re doing it right now!
The second approach is to use AI not downstream of the participants’ idea generation, i.e. during the group meeting, but upstream. On a given subject, AI is used to capture ideas that are then reworked with consumers. Let’s say I’m looking for the conditions that would best meet the needs of a target group in a given market. AI provides me with elements that I can take further, and on which our consumers will be able to bounce back. Of course, it’s entirely possible to complete this research work by drawing on sources other than AI, the ones we usually use.
In both cases, we orchestrate a form of iteration between consumers and AI, so as to be able to advance our thinking in hyper-accelerated mode and on a very open field. At the same time, we have the latitude, if necessary, to sit down with our contacts on the advertiser side to rule out avenues that it would be pointless to pursue. Or, on the contrary, to zoom in on others.
In both approaches, we orchestrate a form of iteration between consumers and AI so that we can advance our thinking in hyper-accelerated mode and on a very open field.
Do these approaches seem particularly relevant to specific sectors or issues?
It’s easy to think of fast-moving sectors such as fashion or technology. But, in reality, I believe that today everything can move very fast everywhere, and that there are no longer any « flat » sectors!
However, its use presupposes certain « mental » or cultural conditions on the part of advertisers’ teams. Some choose not to set limits too early on in their search for innovations, recognizing that they will have to arbitrate and decide, but preferring to do so after exploring many avenues, even if some of them are a little « disturbing ». Others prefer to limit themselves fairly quickly to what they consider possible. The approaches we’ve just outlined will undoubtedly suit the former better than the latter.
ChatGPT can be « bluffing », particularly in its ability to summarize information. However, it also produces aberrations… Isn’t that a problem?
It’s true, it’s true. It’s even become a reflex for me to confront him with them. Here again, I see a dividing line. For some people, the fact that AI generates aberrations can be a stumbling block. Others don’t, and I’m on that side. I believe that AI is not intended to deliver certainties, but rather to provide a set of hypotheses that we can confront with other sources, test and try out with consumers. It’s a bit like learning to drive… For a while, you have the impression that the car will do what you want, until the day you know you can control it. We can also draw a parallel with working with a design consultant. He’s more or less « good », but it’s up to you to decide what you will or won’t take from what he does. And you’re the one who helps him or her progress!
I believe that AI is not intended to deliver certainties, but rather to provide a set of hypotheses that we can compare with other sources, test and try out with consumers.
Does exploiting AI in this way generate additional costs?
No. It’s part of a document search process that’s completely integrated into our work processes. If these tools enable us to go faster, to provide more information, it’s for the benefit of our customers, and doesn’t cost them any more. But it does imply a form of investment on their part; they need to have the necessary resources to make choices. Studies don’t tell you what to do, they’re there to provide the information you need to make decisions. The more insights we produce, the more important it is to manage them well. But we’re also here to help. Our relationship with our customers is based on partnership. At every stage, we exchange ideas and refine together… And we make adjustments, because we need to be flexible, to know how to abandon certain avenues and take up new ones. It’s all part of achieving the best results.
Is there anything else you’d like to add?
I’m struck by the fact that many people are afraid of AI, of the aberrations we’ve mentioned, or of the ethical issues its use raises. My vision, however, is that it’s still humans who define the rules of the game, the framework within which to act with these tools. I’d like to take this opportunity to point out that Esomar is doing some interesting work on these ethical issues.
I’m convinced that the marriage between qualitative research and AI can produce something really great! But only if we remain true to the very nature of qualitative research, and to the spirit of openness it demands. We’re always on some kind of adventure to explore new ideas. Except that, instead of doing it on foot, we can now take a rocket!
I’m convinced that the marriage between qualitative research and AI can produce something really great! But only if we remain true to the very nature of qualitative research, and to the spirit of openness it demands. We’re always on some kind of adventure to explore new ideas. Except that, instead of doing it on foot, we can now take a rocket!
FOR ACTION
- Interact with the interviewee : @ Isabelle Fabry