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CUSTOMER SEGMENTATION OF A MALL USING MACHINE LEARNING
Customer Segmentation is the division of potential customer in a given market into discrete groups, which is based on customers having similar needs and buying characteristics such as gender, age, interests, and miscellaneous spending habits. While the most companies possess enough market knowledge to predict which customer segments are the company’s most profitable. The leaders of those businesses also know that scaling a business is not best left to guesswork. That’s why, in a customer segmentation process, it’s very important to develop customer segment hypotheses and variables, and then validate them with a well-developed, scientific research process. The project study and examines customer data and applies unsupervised machine learning methods such as K-Means and Hierarchical clustering to segment customers. The study also consolidates related work in the field of customer segmentation.
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