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Finding the Right AI Research Opportunities

As industries across the board can feel the disruption from AI, market consolidation and consumers being savvier around where they spend their money, there are opportunities for the taking, too. This session dove into market research innovations that have had true material impact while also covering what is hype. Hear Iudica’s perspective as well as early lessons on how to approach the AI explosion, ensuring it’s done responsibly and with your consumer’s voice at the heart of what you do.

Market Research’s History of Innovation

Disruption has been prevalent in all our lives over the past couple of years, from the great recession moving over to COVID, moving over to conflict in different areas within the world, there is a constant level of disruption. Of course, in today’s environment there has been a lot of attention paid to the new innovation that is artificial intelligence.

“AI is having a pretty profound impact on a lot of different industries and how we do the things that we do,” says Iudica. “But what I’d love to be able to do today is maybe not focus so much on the negative but really provide you with some tools on how to be able to leverage artificial intelligence in the research that you do on a day-to-day basis and finding where there might be opportunities for us to really execute on.”

Looking briefly at the history of innovation within market research, we see that in the 1970’s, we had call research, and that was really the main focus. Some of the innovations in the eighties were one-to-one focus groups and all these different types of interviews. During the nineties, it was online surveys and then in the 2000’s it was really leveraging this whole new vehicle to be able to speak to audiences with social media.

Iudica observes, “I was also looking at mobile research and really opening up opportunities for us to learn more about our customers in truly unique ways, that really weren’t possible, in the years prior to that. In the 2010’s, as a result of all of that innovation, as a result of everything that we learned, all the data that we were imbibing now through social media and through mobile, it generated huge amounts of datasets that exist out in the marketplace.”

He adds, “It’s really thinking about big data analytics, and then kind of the advent of AI as we know it, machine learning models, to help us process these intense amounts of, of data, all the way to the present, where we talk a lot about predictive analytics. We talk about forecasting predictions, and, really, AI is all part of those things, and even virtual and augmented reality. How can we leverage some of those new innovations to be able to get to know our customer a little bit better?”

Leveraging New AI Technology

Ultimately, all of these innovations have a very common thread, Iudica notes. It’s all about driving efficiency. It’s all about driving automation, and it’s all about leveraging some of the new technology that is out there to be able to understand who our customers are and why they make the decisions that they make.

“If we can automate those processes, ultimately, it’s all about freeing up time, and all these innovations have served to free up time in our busy days to really be able to think and to build strategy and to build insights into all of this data,” says Iudica—and AI can play a key role in that.

He adds, “Let’s take pause, understand the technology a bit better. I’m not a neuroscientist by any stretch of the imagination, but I am a researcher, and I’ve known how to validate data over time. So really taking a critical eye to each one of those innovations is super important because, ultimately, we can lean into those skill sets that we know and have learned over the course of our careers to really help us understand whether or not all of these new disruptive tools are actually going to benefit us in the long run, really help increase efficiency, improve accuracy, and streamline data analytics.”

“Where we are today has been accelerated because of this very simple sense of generative AI. The ability to create very unique queries, and query databases in a much more dynamic way than we’ve ever known before with all these incredibly advanced LLM models. But it’s an innovation that has been tremendously effective and tremendously productive for so many of us already in the space.”

Recognizing the Challenges in AI

Ultimately, with every technology and all these new different types of innovations, there are, in fact, challenges. For AI, there are ethical challenges, such as responsible development, transparency and privacy.

Iudica notes, “How do you get what goes into the data modeling? How do we actually build that? Is it truly a closed loop from a privacy perspective? And finally, infringement of the personal brand. We’ve all heard of deep fakes and what AI can do from a visual perspective where it can embed you in different places and all this other stuff. There’s a lot of challenges that we’re facing, and these are all challenges that we need to confront head on.”

“But, obviously, there’s a tremendous amount of upside and opportunity. Whether it’s NLP, advanced analytics using unstructured and previously unusable data. There’s so much data out there, and companies maybe who didn’t focus so much on data cleanliness and can now suddenly look backwards in time and actually cleanse some of the data or be able to marry some different disparate data sources to build really impactful insights.”

Iudica continues, “There’s huge opportunities within that space, whether it’s advanced data and automated stats analysis, whether it’s from simple coding queries to formulating advanced analytics. The idea of coding and building code is something that is becoming more and more steadily democratized. That can only be a good thing because more people can build insights. Finally, changing methods. Open text, voice, biometric methods, they’re all going to become more prevalent, as we’re looking to avoid online or mobile survey responses. Those methods are going to evolve.”

“Ultimately, I think AI is seen as a force for good, generally, by market research,” he says. “They think it’s going to have a positive impact on the market research industry. And so we’ll see if this continues moving forward. How we leverage AI is going to become really important. It’s important to go through this process of growth and have a very critical eye, because that’s ultimately going to help us come through the back end of this as we’ve done with all these other innovations and using this new tool to really help us get closer to our customer.”

Watch the complete video as David Iudica discusses embracing AI, the right approach to vendor partners who are embedding AI into their solutions, and touches on topics such as data source and security, and the quality and transparency of insights.

Contributor

  • Matt Kramer

    Matthew Kramer is the Digital Editor for All Things Insights & All Things Innovation. He has over 20 years of experience working in publishing and media companies, on a variety of business-to-business publications, websites and trade shows.

    View all posts

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