By: Brooke Hempell
“Work” as we know it is undergoing a profound transformation, and market research is about to undergo a significant shift of its own. AI, specifically large language models (LLMs) like ChatGPT, Claude, and Gemini have suddenly given researchers the ability to synthesize large quantities of unstructured information almost instantaneously. Researchers that are able to grasp and leverage this shift in data collection and synthesis have a unique opportunity to be on the cutting-edge of what comes next.
For decades, market researchers have relied heavily on numeric scores and ratings to understand audience preferences and behaviors, largely out of a need to create standardized scales for categorizing people’s thoughts, opinions, and experiences into more objective figures. Developing “verified” scales is practically a sport in academia, where researchers labor to craft and test questions and response options that capture deep-rooted perspectives that have consistent meaning across broad populations and can reliably represent a range of experiences.
And consumers (yes, we’re all consumers) have become fluent in ratings and surveys. Most have come to expect the follow-up customer satisfaction survey, for instance: “On a scale of 1 to 10 how satisfied are you with our services today?” This method is useful for collecting and organizing large swaths of information, but it can also force a square peg into a round hole by diluting subjective experiences into a single objective rating. The result: we lose nuance for the sake of simplicity.
Enter LLMs. These tools are highly sophisticated at synthesizing and categorizing, meaning they can aid researchers in finding themes and throughlines in more subjective data sets–in rapid time. The implications of this technology is massive for those of us who revel in data sets and graphs. AI allows researchers to dive deeper into their audience’s psychology, getting faster and more significant data without the translation to and from numbers.
However, as AI becomes more ubiquitous, our media landscape will only become more saturated with content. LLMs can be integrated as a useful tool in audience research and communications landscaping, but they can’t replace research teams’ expertise. In fact, businesses need human researchers to meaningfully contribute to messaging and campaigns now more than ever.
Beyond the Numbers: Unlocking Human Insights with AI
Unlike humans, who reflect and synthesize ideas through lived experience and context, AI processes information by rapidly identifying patterns across large datasets. It can generate insights quickly, but without true understanding or awareness. Experienced researchers know how to pore through and understand data sets and distill them into actionable takeaways for their clients. They also have the intuition, empathy, and contextual understanding to explore the “why” behind the survey responses and provide a complete picture of the research and its implications.
Using LLMs to help expedite data analysis also gives researchers more time to focus on thorough qualitative methods like interviews and focus groups. Standardized tests and scales often force complex experiences and nuanced perspectives into predefined categories that don’t tell the whole story. With better synthesis tools, researchers can conduct thorough interviews and focus groups where their sample groups have the space to freely express their thoughts, and use LLMs as an aid for summarizing and extrapolating the critical information.
How LLMs Help Us With Strategic Communications
In my role as a researcher in strategic communications, branding, and marketing at Pinkston, I’ve worked with many clients in highly politicized spaces – such as nonprofits that are dependent on donors for funding and policy-centered organizations in nuanced sectors like immigration and energy. In these situations in particular, how we phrase and communicate messaging to their audiences can make or break a story or campaign. For example, the word “sustainable” can carry vastly different meanings and connotations across groups. It’s the researcher’s critical role to understand these interpretations and ensure that messaging truly resonates. By increasing researchers’ ability to understand and apply qualitative findings, LLMs can help us hone into language that resonates with intended audiences as well as client stakeholders. Giving researchers more time and insight into that language becomes a strategic advantage in communicating a company’s message.
Integrating Research: An Essential for Every Strategic Decision
AI is only the most recent transformative development in the legacy of technological advances that streamline access to people and information. With each development, research is easier and more efficient than ever. And, as research becomes both more accessible and applicable, organizations have little excuse not to leverage it. In fact, with the introduction of LLMs, organizations have a valuable opportunity to integrate research into every strategic decision to help directly analyze their field and audience.
Investing in research helps companies add broader perspectives and a human element to strategic decision-making. By using qualitative data to deeply understand an audience’s diverse viewpoints, researchers are uniquely positioned to craft recommendations that are not just data-driven, but also inherently people-centric and actionable. Basing these recommendations off of such rich information is key to uncovering valuable insights and building genuine affinity, and ultimately, it’s how organizations and campaigns achieve lasting success.
Ironically, artificial intelligence is enabling research to become more personal and less transactional. We have the capacity to explore a fuller depth of individual experiences, beliefs, and opinions, rather than just condensing them into one-dimensional data points. But while AI provides unprecedented speed in data synthesis, research findings can only be maximized with the guidance and insights of humans to use their critical thinking, lived experiences, empathy, and strategic foresight to transform insights to effective solutions. Take heart, researchers, you are needed now more than ever!
