Title: Analyzing the customer's personality to provide the best services Using decision tree
Authors: Nibras Talib Mohammed,
Volume: 9
Issue: 8
Pages: 1-12
Publication Date: 2025/08/28
Abstract:
This research will analyze a dataset containing 22 important customer attributes, such as education, marital status, income, and the amount spent on various products on a regular basis, such as fruits, meat, and gold. The dataset also includes whether a promotion or discount affects customers, as well as the number of purchase sources customers use, such as catalogs, stores, and locations. Using decision tree analysis is a powerful tool that can be used to analyze customer personality and understand their behavior. This technique helps in deducing relationships between various attributes and assessing how these relationships might influence responses. By examining the results extracted from the decision tree analysis, it is clear that there is a variation in positive behavior among different customer groups. Some nodes showed high gain rates when asked specific questions about responses or indicators, indicating that the groups within these nodes were the most responsive. Optimistic are the common characteristics of these customers. All customers in these nodes, which are generally more responsive, have similar characteristics and may share common needs or consumption patterns. Identifying and capitalizing on these characteristics can represent a significant opportunity for a company when developing marketing and communication s strategies. On the other hand, there are other nodes with low profitability but a large number of customers. These nodes may represent customer groups with different structures or characteristics that make them less likely to respond. It may be useful to study these nodes in more detail to understand what motivates these people and learn how to attract them.