Key Drivers of Retail Store Performance Revealed

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This study explores retail store modelling by analysing factors influencing revenue using clustering and prediction methods. Based on data from 1,650 stores, preprocessing techniques like categorical encoding and scaling were applied. K-Means cluster analysis identified store performance differences, while linear regression and random forest approaches evaluated the statistical impact of key features and accuracy metrics. The findings highlight operational and physical factors driving...