Mining Association Rules from Customer Behaviors for Hotel Customer Cross-selling

摘要

In this paper we investigate the application of mining association rules from customer behavior data so as to provide a solution to the problem of hotel customer cross-selling. We define and analyze the cross-selling problem in hotel management, and employ association rule mining to find out some interesting rules, which could help hotel enterprises to understand their customers' needs and preferences. When hotel enterprises succeeds in doing so, it can effectively cross-sell many products and services that closely match its customers' preferences. Therefore, the hotel can lower the "churn", increase the number of loyal customers, and obtain a higher customer lifetime valuation. Thus, it enables hotel managers to rapidly establish cross-selling strategies to enhance sales and profits. Although the application described is in the hotel sector, the methodology is generic in nature and can be applied to other commercial domains.