Customer Segmentation using Tableau Method

Computer Science and Engineering

There is lot of competitions among businesses to attract new customers and hold on to existing ones as a result of the creation of numerous competitors and entrepreneurs. Because of the aforementioned, outstanding customer service is required, regardless of the size of the company. Any company will also benefit more from targeted customer services and the creation of unique customer care strategies if it can comprehend the wants of both of its clients. Structured customer service makes it feasible to have this understanding. Customers from each segment are similar in conditions of market characteristics. In contrast to traditional market analytics, which frequently fail, especially when the customer base is too broad, big data concepts and machine learning have increased the acceptance of the automated customer segmentation strategy. The Tableau clustering approach is employed in this paper to achieve this. The softwareis trained using a two-factor dataset of 100 patterns gathered from the retail industry and was created using the sklearn package for the Tableau approach (available in the appendix). Features of the average monthly customer visits and average monthly customer purchases.

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