Research on Consumer Preferences and Potential Users of Vacuum Cleaning Robots-Based on Text Mining and Questionnaire Surveys

Abstract

With the advancement of technology, online shopping has gained immense popularity, resulting in the generation of copious amounts of e-commerce data. Previous studies have delved into the examination of online reviews in relation to consumer behavior. However, there exist significant challenges in selecting appropriate methodologies and comparing them to traditional market research, as well as assessing their accuracy and representativeness. In light of these challenges, we conducted an empirical study that analyzed consumer preferences for robotic vacuum cleaners by employing text mining techniques and questionnaire surveys. By utilizing data extracted from a prominent Chinese online shopping platform and conducting a team survey, we were able to ascertain the specific preferences of consumers regarding floor sweeping robots and segment the potential user market accordingly. The empirical research findings indicate that consumer attention towards product characteristics varies among different brands. While consumers generally prioritize product performance in their preference for products within the same category, there are still differences in attention given to products from distinct brands. Furthermore, consumers with lower personal characteristics have higher requirements for product purchases and lower corresponding purchase desires. Our research underscores the importance of understanding consumer preferences in the vacuum cleaning robot market and the potential for exploring untapped markets, while integrating new data elements with traditional statistical research methods.