Abstract
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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