Data-Driven Market Segmentation: K-means Clustering and STP Analysis in Mainland China's Sportswear Industry
DOI:
https://doi.org/10.62051/ijgem.v4n1.02Keywords:
Sportswear Market, Mainland China, Market Segmentation, Target Market, Market Positioning, K-means algorithmAbstract
Post-Covid-19, mainland China's economy is gradually recovering, leading to increased sportswear sales. This study integrates STP theory (segmentation, targeting, positioning) with the K-means clustering algorithm to analyze the sportswear market in mainland China. Consumer data was collected via a questionnaire survey, pre-processed, and cleaned before applying K-means clustering to segment consumers into four distinct groups. The analysis reveals significant differences in purchasing habits across these segments. This data-driven approach offers sportswear companies insights for targeted marketing strategies, enhancing the precision and effectiveness of their marketing efforts in mainland China.
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[1] Khandelwal, K., Jakhar, T., Khandelwal, T. (2020) Segmentation, Targeting, and Positioning. International Research Journal of Engineering and Technology, 7(5): 1509-1514.
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[5] Cui, M. (2020) Introduction to the K-Means Clustering Algorithm Based on the Elbow Method. Geoscience and Remote Sensing, 3: 9-16.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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