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Market segmentation plays a crucial role in design and development of the product. It separates a large number of customers into meaningful groups who share similar characteristics, requirements and behaviors. This is mainly used to match diverse customer needs or to deploy resources effectively. Hence, it enables companies to increase the opportunities of market success. Market segmentation can be implemented based on the customer pain point. It contains customer's inconvenience, annoying or frustration towards a product. The BCBimax algorithm of biclustering technique is introduced to conduct market segmentation using customer pain points. However, during segmentation there occurs maximum overlapping so congestion occurs among biclusters and loss of information during discretization. In this study, the author proposed similarity score with BCBimax algorithm for market segmentation to overcome the problem associated with the existing work. The proposed method extracts more reasonable and meaningful customer and customer pain points where grouped together.