“Humanizing” Market Research with AI

The Boon and Bane of AI

The increasing and widespread utilization and demand for Artificial Intelligence have been met with both excitement and reservation.  Excitement for the possibilities AI’s implementation unlocks, oftentimes steps ahead of the curve or beyond expectations; reservations not only stemming from the risks over its unethical and unchecked use, but also the ramifications for human involvement now that intelligent machines represent an optimized and economical choice for completing tasks and processes.  But can there be a middle ground somewhere where AI and human engagement coexist and collaborate? 

The “Humanization” of Market Research

“Capturing the Human Element in an Artificial World” by Eric Tayce (Quirk’s Marketing Research Review, Sep-Oct 2024) posits that such a midground is possible, especially in market research.  An industry that’s all aware of its excessive dependence on technology to necessitate a push to “humanize” research data, it saw a dramatic shift from “data-intense tomes and clinical-sounding slide titles” to “streamlined, narrative-style reporting” focused on “the unique motivations and experiences that drive customer behaviors.”  The latter “humanized” approach is able to communicate business goals while connecting and engaging on an emotional level.  However, generative large language models (LLMs) cast a shadow on this “humanized” approach by offering synthetic outputs and progressive algorithms. 

But combining both AI and efforts to “humanize” research can result in the whole being greater than the sum of its parts.  The article shared that AI can help collect more unstructured data from survey research by employing conversational chatbots to create a natural, richer experience for the respondent.  That unstructured data in turn can potentially provide more organic, more human insights with AI-powered algorithms, an undertaking that was once considered too complex or time-consuming.  AI can also build multifaceted perspectives through context by linking survey records with a broad range of data sources.  And in lieu of traditional static deliverables, data and insights can be presented in a vibrant and interactive narrative by an AI-powered persona. 

The “Human” Element

All these interesting prospects can only be achieved when AI is tempered by high-quality human input and thoughtful implementation considerate of ethical and moral implications.  Aside from AI mistakes and hallucinations existing, AI has been observed to be too helpful and excitable.  Human oversight and input remain key in ensuring AI models are trained, fine-tuned and grounded with quality and relevant datasets while having enough flexibility to engage appropriately in open-ended interactions. 

There’s no denying just how transformative AI is in reshaping industries today, including market research.  Despite concerns of machines taking over jobs, one can look at it with the perspective of roles changing and adapting.  AI with its generative and synthetic capabilities can elevate the “humanization” of market research, but to get to that point we simply can’t forget that humans are indispensable to the whole process. 

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