Demographic and Psychographic Customer Segmentation for Ecommerce Applications

E-commerce transactions are not a new concept anymore. E-commerce is a popular method of shopping, and many businesses utilize it to market and sell their goods. As a result, clients perceive an overabundance of information. Information overload happens when consumers are given too much information about a product and get perplexed. Personalization will help to solve the overloading issue. Personalization techniques may be applied to marketing to draw in new consumers and increase revenue. In e-commerce applications, Customer segmentation is crucial to marketing because it enables managers to identify new clients and steer clear of pursuing the incorrect ones. E-commerce businesses may adjust their offers to better fit the requirements and preferences of their consumers and increase customer satisfaction and loyalty by studying and using demographic and psychographic client segmentation. It enables businesses to comprehend client demands and make efforts to meet them. By coming up with the best marketing plan, it seeks to establish a connection with the most lucrative clients. This research study segments the consumers using K-means clustering and selects the best clustering technique. After clustering, SVR (Support vector Regression) is used to classify the data. The findings of this study can help e-commerce businesses to better target and engage their customers by giving them useful information.