Research on the Demand Hierarchy of E-Commerce Products Based on Text Mining and the IPA-KANO Model

Anyi Chen

Authors

Anyi Chen Walmart E-commerce Search Team, Wal-Mart Associates Inc., Bentonville, Arkansas, 72716, USA Author

Keywords:

e-commerce, text mining, IPA-KANO model, product demand hierarchy

Abstract

In the current era of rapid growth in e-commerce, understanding consumer demand is crucial and also the core of enhancing market competitiveness. This study integrates text mining technology and IPA-KANO model to create a comprehensive system for analyzing the demand hierarchy of e-commerce products. This study uses text mining to collect, process, and analyze consumer evaluation data, uncovering the basic needs of consumers. By integrating the IPA matrix and KANO model to analyze user needs, basic needs, necessary needs, and attractive needs are distinguished. The text analysis results are combined with the IPA-KANO framework to construct a hierarchy of needs and response mechanisms, providing specific data support for product iteration. Research shows that this method helps to uncover users' deep-seated needs, assist e-commerce companies in customizing precise marketing plans and product upgrade paths, and strengthen the e-commerce platform's ability in market competition.

References

1. J. Lu, et al., "BSTC: A fake review detection model based on a pre-trained language model and convolutional neural network," Electronics, vol. 12, no. 10, p. 2165, 2023, doi: 10.3390/electronics12102165.

2. Q. Peng, C. Wang, and M. Goh, "Green financing strategies in a low-carbon e-commerce supply chain under service quality regulation," Environ. Sci. Pollut. Res., vol. 30, no. 2, pp. 2575–2596, 2023, doi: 10.1007/s11356-022-22329-w.

3. M. Yan, et al., "An empirical investigation of the impact of influencer live-streaming ads in e-commerce platforms on consumers’ buying impulse," Internet Res., vol. 33, no. 4, pp. 1633–1663, 2023, doi: 10.1108/INTR-11-2020-0625.

4. T. Kojo and T. Yoshikawa, "Comparison of Location Potential for Customer Attraction of a Central Business District and a Large Suburban Shopping Mall Considering Residents’ Behavior When Shopping in Multiple Stores at a Time," Urban Reg. Plan. Rev., vol. 12, pp. 102–125, 2025, doi: 10.14398/urpr.12.102.

5. J. Wang, "Cost control problems and countermeasures of e-commerce enterprises under the background of big data and In-ternet of Things," J. Comput. Methods Sci. Eng., vol. 23, no. 6, pp. 3135–3145, 2023, doi: 10.3233/JCM-226931.

6. E. Aldhahri, "The Use of Recurrent Nets for the Prediction of e-Commerce Sales," Eng. Technol. Appl. Sci. Res., vol. 13, no. 3, pp. 10931–10935, 2023, doi: 10.48084/etasr.5964.

7. R. E. Widodo and T. A. Napitupulu, "Exploring the Impact of Live Streaming for E-Commerce Business: A Systematic Liter-ature," J. Theor. Appl. Inf. Technol., vol. 101, no. 16, 2023.