AI In Market Research Today

With 90% of the world’s data created in just two years time between 2021 and 2023 and the global data volume standing at 149 zettabytes by 2024, it’s understandable why AI would be readily adopted by the market research industry.  Traditional methods of data collection and analysis would hold a place in market research but they simply aren’t as powerful as AI when it comes to handling all that staggering volume of data.  But is AI powerful enough to take the place of human researchers?  

AI enables research teams to move, process and analyze massive datasets with speed and accuracy, efficiently handling all the repetition and scale involved in the research process.  From drafting questionnaires to monitoring survey data quality, from analyzing open-ends to formulating dashboards and charts, AI fully automates the research process leading to faster and better decisions at a scale beyond the capabilities of human researchers.  

But is AI the endgame for market research? Does it make human researchers obsolete?  

Image: geralt

Cascade Strategies and AI

Cascade Strategies conducted a member perceptions study for a company looking to develop and implement a brand typology.  The overall goal of the study was to help them better understand their different customer type’s overall motivations and aspirations for more effective engagement.  As part of the study, we conducted an online survey with over 1,500 of their randomly selected members.  We then utilized an AI-assisted Self-organizing Map (SOM) to run all the cases recursively, sometimes millions of times, until it optimizes the separations among the groups.  The SOM produced a 6-group solution, with each group having a dominant passion that is served well or poorly by the company, ranging from proclivity for deals and new brands to yearning for customization and connection with other users.  

The AI has done the heavy lifting of scanning all that dataset, surfacing themes, and summarizing the respondents.  It has done enough to structure the story of each group but not enough tell or paint the whole picture.  

This is where the human researchers at Cascade Strategies step in.  We came up with names for each group that best described their dominant passion, names resonant enough that they not only convey an immediate idea of what they’re most passionate about but makes them fundamentally relatable even if one doesn’t necessarily share the same propensities: Shopper, Seeker, Learner, Sharer, Individualizer and Intellectual. 

In isolation, each group achieves the study’s goal of guiding the company on the most effective way to engage with them.  Their sum, however, grants the company an overview on how to improve and further develop its platform by considering and introducing new features that matter to one particular group, but would essentially benefit its membership base as a whole when implemented.  For example, the Sharer would appreciate increased opportunities to connect and interact with other experts and enthusiasts of the same interests in the platform by making it easier to make reviews and share content.  

AI surfaced all those patterns and signals from all that survey data, but it lacked the judgment and context to elevate it into a meaningful and coherent narrative.  Human researchers, on the other hand, saw what story can be told from all those themes and by layering in human understanding, they’re able to tie them down to actionable business decisions.  

Image: Christina Morillo

Leveraging AI In Market Research

So would AI replace human researchers?  We’d like to frame our response to this question with the words of Joseph Weizenbaum, one of AI’s early researchers:  “We can count, but we are rapidly forgetting how to say what is worth counting and why.”  

Yes, AI is powerful enough to handle large amounts of data to identify patterns, cluster themes, and summarize respondents, but it generates outputs rather than insights.  Outputs foster decisions rooted in logic and reasoning, but insights spring from judgment and context.  Outputs can provide directions and surface themes from which stories can be framed, but insights take it one step further by asking what matters and why it matters, adding depth and resonance to the story.  

In addition, Weizenbaum posits that computer programming can make decisions but it can’t ultimately choose.  Just like insights, choosing requires judgment which takes in emotions, values and experience.  

We at Cascade Strategies are among a growing number of proponents who believe that AI works best as a tool and extension of human intelligence and talents.  AI strips the friction from manual, repetitive work without compromising methodological rigor and accuracy, but rather than adopting it for the sake of automation, we choose to see it as a freeing and empowering agent that enables researchers to focus more on interpreting data with the context of human understanding and values, translating insights into sensible and confident business decisions.  Just as quantitative and qualitative research can coexist in the same study, we choose to live in a world where AI and human researchers work together towards the same goal of finding and crafting meaningful and relevant stories worth telling.  

Image: Pavel Danilyuk

Featured Image: Ron Lach

Top Image: kc0uvb

Read more