IN AN AI DRIVEN WORLD QUAL RESEARCHERS SHOULD BE SEEKING ONE THING : ORIGINAL VOICE

Hey thanks Craig for asking me to be a part of this important discussion.

Context : almost exactly a decade ago I left corporate world to freelance and got a project from Shiseido that involved doing research in the USA, China, France and Italy … with no time and little budget. Fortunately a friend introduced me to an AI driven platform that uses the whole of the internet as what we now fashionably call a synthetic audience. I was able to do in-depth studies on key issues in all four markets in a week. Detailed analysis of what were the key narratives driving the category, the brands, the reputation of Japan in each market and more.

GREAT results and a great response from the client who used the study to re-write a key strategy document.

BUT even in that first involvement with an AI platform ( it was https://significancesystems.com/ who I still partner with ) I learnt my most valuable lesson. How we used the platform and more importantly how I explained the platform and even more importantly how I presented the results and even more importantly how I used it to create ideas for the clients needed to be done in my own style … my original voice.

Be different, explain different, analyse different.

Because qual research, at least in my 30 years practicing it, has always been about how the practitioner originally voices technique, findings and applications.

Now my own history of being an “AI” unit goes way back. I started my working life as a public librarian in Sydney*. Near a dozen years working the “reference” desk, which actually meant having people, mostly kids, asking me endless questions, and expecting an answer. Just like Google, or GPT or Perplexity or what ever AI platform you are using right now to find out exactly who I am.

And what I learnt … style! Answering a question is good, doing it in a way that people remember is better. Attention, response, memorability. Isn’t that what we want as practitioners ?

Or maybe we should start with the move from what was “secondary” to now what is primary qualitative research.

Over a decade ago we started to see a number of excellent AI ( or more correctly LLM ) driven platforms come on the market that allowed us to enter a subject, qualified by country and language, that then scan, read and analyse the whole of the internet for anything mentioning the narrative around that subject. Platforms like SignificantSystems or SQREEM. Not social media monitoring, which of course is actually just a poll of those that choose to react … qualitative  tools that drew on all internet based content as a proxy for human knowledge.

Literally reading millions of pieces of content on say TESLA in Japan, or “Coming beauty trends” globally or what every. And getting reports that told us what was happening with the subject, how it related to other subjects, what emotions were being driven, what was the future of the subject, how would it increase or decrease in relevance. All in context of a specific market, language, background.

More learned colleagues would be able to explain better than I but I know enough to have recognised that the seemingly new and trendy term “synthetic audience” is actually about something that has been around for statisticians for decades and as a concept for centuries. Using collected data to project what people might think. Old news. As always of heightened interest only when a new technology makes it maybe more accessible.

Now in reality new “artificials”, or technologies that allow for human intelligence enhancement, have always been greeted with cynicism by “the learned”.

Socrates raged against the idea of a uniform alphabet being taught in schools because he felt it would “limit original thinking and only encourage copying”, the intellectual “letter writers” of the late 15th century saw the printing a press as a true threat to the value of new thinking and interpretation because it just made reading other ideas easier, again limiting creativity. The same with say “crib notes” when I was in high school all those decade ago, and of course the same with the introduction of the internet.

Similarly we now see debate raging about the use of various tools in the qual research world. AI driven moderators guides, virtual analysis, summaries, translations, facial tracking, reports writing .. heck, Craig has covered it all.

None, in my experience, are perfect. All are good to experiment with. Learn from. Trial. Afterall qual research has been using tech to enhance itself well since the first time someone use a audio tape recordings to listen back to interviews, or the guys at my old company, McCann, invented eye tracking, or how amazing it was in the early 90s when I first used edited video to create a “report” of a qual project. IT IS NOT THE TECH that matters.

What matters is HOW you use it. Yes you can try to be the first to use a new tool, someone else will have done it already. But you can be the first to use it differently.

Try this :

• don’t worry about how to prompt ( copy someone else’s guide),

• don’t get carried away with efficiencies ( everyone is doing that ) …

• focus on being different.

• use and create new jargon, overlay multiple techniques, re-write any report in a way that seems thought provoking for its style as much as it’s content. 

• Please continue to use human interaction and intuition to aid and increase the value of AI tools ( no platform will ever make the leap from the moderators guide that good qual researcher will make, or draw a conclusion from my writing style as to what I am afraid of )

AI is not the problem for qual research. Just the latest in a loooooong line of tools. Those that win do it with an #originalvoice.

Use the tools. BUT make sure you use your voice to be original.

*Full disclosure : as a trained librarian who only moved in to the market research world in my early 30s I never could and still cannot understand why what we call “secondary research” is called secondary when logically it should be the first and usually primary or only needed form of research. And of course it is purely qualitative. Because whenever you read a collection of reports, documents, articles, books and analyse them it is all a qualitative experience. Valuable lessons in my near thirty years doing 100s of qual projects across asia.

Now in reality new “artificials”, or technologies that allow for human intelligence enhancement, have always been greeted with cynicism by “the learned”. Socrates raged against the idea of a uniform alphabet being taught in schools because he felt it would “limit original thinking and only encourage copying”, the intellectual “letter writers” of the late 15th century saw the printing a press as a true threat to the value of new think and interpretation because it just made reading other ideas easier, again limiting creativity. The same with say “crib notes” when I was in high school all those decade ago, and of course the same with the introduction of the internet.