Author: Claudia Quintanilla, member of the Research-Thematic Area Group in Responsible Production, Commercialization and Consumption of the Business School of Tecnológico de Monterrey.
Two months after one year since the OpenAI company launched the demo of the Artificial Intelligence (AI) tool ChatGPT (Chat Generative Pre-trained Transformer) on the market; It already has 100 million monthly users according to Statista (2023). This leads us to ask ourselves, how has its use changed the dynamics of the Consumer Intelligence industry?
ChatGPT, as an AI tool, is being used in designing questionnaires for market research. With its help, the questions to be included in a survey can be designed, which speeds up the design process; However, it is important to align the questions generated with the objectives of the study.
Those of us who have used the ChatGPT application know that it works based on “prompts”, which is the instruction or question with which we interact with the AI or chatbot. To generate a questionnaire aligned with the objectives of the study, it is necessary to be very clear and specific about what you want to measure with that questionnaire, and even how to measure it; that is, with open or closed questions.
After several iterations with the chatbot, in which it can be provided with the topics that the study is intended to cover, the questions are refined. Once information is collected, generating valuable insights into consumer behavior requires data analysis.
AI is being used largely for the processing of large amounts of text and images, mainly benefiting the interpretation of qualitative data.
Currently, Consumer Intelligence is an area of Marketing that evolved from Market Research thanks to the development of technological tools and cutting-edge methodologies that allow us to understand the behavior of our customers in a deeper and more dynamic way.
It is not just about observing what consumers do, but about understanding why they do it, how they feel and what drives them to behave that way.
The richness of using AI tools lies in processing large amounts of data that not only describe current behavior patterns, but also help predict future behavior.
Understanding digital consumer behavior is one of the main applications of AI. “Social Listening” studies, which identify trends in what customers talk about brands online.
It is not only understanding what they are talking about, but also analyzing these conversations, which generally happen on social networks, blogs, news portals and customer service channels, in order to know if the communication is positive, negative, or neutral, which It is known as “Sentiment Analysis”.
With these studies, a general evaluation of the perception of a brand is obtained and the themes in the negative comments are delved into, mainly, to detail what “hurts” the brand. Know if they are complaints about the quality of a specific product, and take measures from its design and production; or if they are complaints with the service experience, which can cause the loss of dissatisfied customers.
“Sentiment Analysis” studies of the competition can also be carried out, and based on the comparison with our brand, take advantage of market opportunities.
By leveraging AI technologies, market researchers achieve speed, agility, and depth in generating consumer insights more efficiently to make informed decisions.
However, we must consider that the use of AI has limitations and therefore it is advisable to question, for each task we ask of it, the limitations that its response may have.
Furthermore, even if the information base to which the AI tool has access is updated (which is not the case in the current version), and is not restricted to data up to a certain date in time, it is essential to combine the work it generates with human experience to ensure that results align with business objectives.
The responsibility that the Consumer Intelligence areas in companies now have is to lead the design of studies with the use of these new tools, prioritizing the data sources that should be used, what data to collect and how to guarantee its quality.
Originally published in El Financiero.