A fuzzy clustering approach for segmenting Indian retail market based on store image

Store image is defined as the overall attitude towards the store based upon the perceptions of relevant store attributes. Store image segmentation provides guidelines for a retail firm's marketing strategy and can increase profitability. The foremost theme of this research is to utilise the subtractive clustering concept for defining the market boundaries in the fuzzy-based segmentation. Researchers often use clustering analysis as a tool in market segmentation studies, the results of which often ends with crisp partitioning form, in simple words, where one member cannot belong to two or more groups. This indicates that different segments overlap with one another. This study integrates the concept of application of subtractive clustering in fuzzy C-means clustering for profiling the customers who perceive the retail store based on its image. Fuzzy clustering is also compared with hard clustering solutions. We have predicted the model using discriminate analysis. Further it concentrates on answer tree model of segmentation to identify the best predictor.