In today’s era, many companies are actively building their own digital platforms and mining valuable insights from big data. They also expect that market research can also use data to obtain more representative results. Therefore, with the rapid development of AI, many market researchers have begun to use this technology to effectively conduct data cleaning, in-depth predictive analysis, and data mining (Quantilope, 2023). Although from the above application scope, some people may mistakenly think that AI is limited to the field of quantitative research, in fact, AI can also exert excellent performance for qualitative research.
Qualitative research collects and analyzes non-numeric data to understand people’s experiences, attitudes, behaviors, and interactions (Pathak, Jena, Kalra, 2013). Therefore, researchers can use facial coding technology to deeply analyze the micro-expressions and emotional responses of respondents, providing deeper insights into their emotional states and consumer behavior (Srinivasan, 2023). This is an advanced AI algorithm that can carefully capture the subtle changes in the face and the intonation differences in the voice (Srinivasan, 2023).
In addition, qualitative research is often criticized for being too subjective, and sentiment analysis technology may be able to alleviate this concern. This technology can systematically help researchers delve into the hidden emotional aspects of written or oral feedback, allowing them to more thoroughly understand the emotional response that activities, products, or services bring to consumers (Srinivasan, 2023). Sentiment analysis tools based on AI can provide objective and in-depth insights and reduce personal bias that may be caused by manual review (Amazon Web Services, 2023). It can not only handle large amounts of data analysis but also provide results in real-time, allowing us to grasp the context of information instantly (Amazon Web Services, 2023).
In addition to the previously mentioned technologies, the applications of AI in qualitative market research are quite diverse. It can assist and enhance our ability to analyze subjective data. Therefore, I believe that AI will become an important tool in qualitative market research.
Reference
Quantilope. (2023, December 9). How AI Continues To Disrupt Market Research, for the Better. https://www.quantilope.com/resources/how-ai-is-disrupting-market-research.
Pathak, V., Jena, B., Kalra, S. (2013). Qualitative research. Perspectives in Clinical Research, 4(3), 192-194. https://doi.org/10.4103/2229-3485.115389.
Srinivasan, S. (2023, May 22). AI Has Taken Over Qualitative Market Research. Here’s What That Means for Your Business. https://www.entrepreneur.com/science-technology/how-ai-is-transforming-market-research/450593.
Amazon Web Services. (2023). What is Sentiment Analysis? https://aws.amazon.com/what-is/sentiment-analysis/?nc1=h_ls.
