Traversing the Perception Maze: Delving into the intricate terrain of potential customer perceptions in the realm of organic foods through the application of Text Mining

This paper aims to delve into detailed reviews using text mining to support the perception of potential customers toward organic foods. We attempted to analyze more than 1500 reviews comments, and reviews on social media and e-commerce websites and suggest appropriate marketing strategies that can help organic food vendors in effective sales. The study used a descriptive research design, and data relevant to the study objectives were collected using secondary sources, including YouTube, e-commerce sites, and the Scopus database. Text mining was used to collect data relevant to the research objectives, suitable text analysis was performed using KH coder, and a co-occurrence network was used to present the results. The inferences on the perception of potential customers were analyzed, and key terms such as pesticides, chemicals, way of farming, natural fertilizers, health consciousness, price, quality, comparisons, time, and health were all predominant factors that led to their perception. By analyzing customers' perceptions, this study provides relevant suggestions for the organic food market, which would help in designing a customer-centric strategy to promote organic food products effectively.