Data Mining Assignment: XL Miner Analysis and Customer Segmentation

This assignment solution delves into data mining techniques, specifically focusing on association rules and clustering methods. It utilizes XL Miner to analyze customer data, deriving association rules to understand buying patterns and identify rule redundancy. The solution explores hierarchical and k-means clustering to segment customers, highlighting the importance of data normalization and its impact on cluster formation. The analysis identifies distinct customer segments, such as "Middle Class Flyer," "High Networth Flyer," and "Non-frequent Flyer," based on flight transactions and bonus miles. The assignment compares the results of both clustering techniques, notes discrepancies, and suggests targeted offers for each segment to enhance customer engagement and business outcomes. References to relevant literature support the analysis.