Customer Clusterization using Machine Learning Approach

Customer Clusterization using Machine Learning Approach

연구 분야: Artificial Intelligence

학회: MLMI '24: Proceedings of the 2024 7th International Conference on Machine Learning and Machine Intelligence (MLMI)

Understanding customer is crucial for marketing strategies and increasing customer satisfaction in today's business environment. One method to fulfill of marketing strategies is segment customer based on their purchasing habits and demographic characteristics. This study describes a complete approach to customer segmentation based on K-means clustering, an unsupervised machine learning algorithm. There are three stages namely preprocessing to select feature and variable is used to develop clustering model, clustering model implementation, and validation of model. There are four clusters that compare the relationship of marital status and recency to the grocery purchases (product) made by each customer to find out which ingredients we will use to make better products for customers.