The increasing role of AI in market research is a hot topic for many people in our industry. Some research teams are all in on AI; some are taking a more cautious approach.
To help insight pros better understand the AI landscape we recently hosted a thought leadership webinar focused on showcasing new AI innovations and real-life experiments. The special guest speaker was Dale Evernden, Head of UX and Innovation at Rival Technologies.
A recording of the webinar is now available. Here's a quick recap of some of Dale's most notable insights.
Embracing AI for Market Research
Dale pointed out that many researchers have an awkward relationship with AI. Many recognize that AI has potential to help them, but many are also worried that it might replace them someday.
To avoid becoming obsolete, researchers must engage with AI tools in a more meaningful way. After all, it is very unlikely that AI will replace you. Other humans using AI are more likely to replace humans that don't.
A Systematic Approach to AI Innovation
One of our strategies in navigating AI in market research is setting up a dedicated innovation function. At Rival, we set up a new division called Rival Labs that is focused on rapid ideation and agile iteration.
Dale revealed that the goal is value creation and to ultimately help researchers elevate their impact.
The Role of Collaboration and Prototypes
Collaboration is critical in maximizing the impact of AI for market research. A crucial step for this, Dale pointed out, is the creation of tangible assets like prototypes. These can help inspire vision as you're talking with key stakeholders and developing new AI features and products.
Leveraging AI Probing for Deeper Insights
It's not enough to merely adopt AI though. To get it right, you need a measured approach so that both researchers and participants benefit.
Dale shared used the example of AI Probing to illustrate this point. This feature involves AI asking intelligent follow-up questions based on user responses to garner deeper insights. The team at Rival Labs also layered in the concept of Thoughtfulness Score to make AI Probing more useful, powerful and compelling.
Ranging from 0 to 10, a Thoughtfulness Score evaluates the quality of user responses based on ten dimensions of thoughtfulness. If an initial response in a conversational survey from the participant scores below 7, then AI will automatically ask follow-up questions to get more context and information. Once the Thoughtfulness Score exceeds 7, no additional probing questions are asked.
This combo of Thoughtfulness Score and AI probing enables researchers to capture deeper insights without negatively impacting the participant experience. When combined with other AI innovations like the AI Summarizer, this capability makes "qual at scale" a reality. Collectively, these AI tools can make it super easy and fast to make sense of all the unstructured, qual data coming from your insight community.
This proof of concept of AI Probing and Thoughtfulness Score was recently tested by Rival customer OURA, and they presented their experience with it at Quirk's New York. We're really excited about this POC and we're continuing to iterate on it so we can make it more widely available on the Rival platform.
Consideration of AI Limitations
While it's important to experiment, researchers need to acknowledge that AI is not without its limitations. AI's effectiveness can vary based on many factors.
The solution, according to Dale? Make sure a human is in the loop. This enables you to maintain oversight and catch any potential mistakes.
The Importance of Security and Compliance
Before wrapping up, Dale emphasizes the importance of data privacy and security. Given the sensitive nature of user data in customer insights, maintaining compliance and upholding privacy responsibilities is crucial as you use or develop AI tools for market research.
Ultimately, the goal of using AI is not full automation, but effective augmentation of what you already do as an insights professional. As we dive deeper into the AI-powered future of market research, prioritizing ethics, privacy, and human involvement will be paramount.
To learn more, check out our full webinar, "AI for Market Research: How to Ideate, Iterate and Collaborate to Drive Innovation."
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