Market segmentation of clearance sales outshoppers using cluster and classification tree-based approach

This study facilitates the understanding of market segments behind the clearance sales outshopping behaviour. Our concern in this paper is to understand the clearance sales outshoppers in India and segment them based on the shopper's perception on retail area attributes. This study has linked clearance sales for the first time with outshopping behaviour. In this sense, this paper focuses on retail area attributes as a possible criterion to segment the outshoppers. It starts by analysing the existing outshopping behaviour concepts. Then the market segments of clearance sales outshoppers were identified by collection of data across three trading areas. After reviewing the existing concepts of outshopping behaviour, we performed a segmentation analysis of clothing and apparel outshoppers in India. Firstly, a hierarchical cluster analysis was carried out, and then k-means cluster analysis identified two meaningfully differentiated customer groups. Further, a classification and regression tree analysis was performed to identify the retail area attributes that differentiated the clustered groups. Finally, two clusters of clearance sales outshoppers namely store-oriented shoppers and market-oriented shoppers are identified. Main conclusions with implications for retailing management are pointed out.