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|Title:||Customer retention via data mining|
Multiple level association rules
|Source:||Ng, K., Liu, H. (2000). Customer retention via data mining. Artificial Intelligence Review 14 (6) : 569-590. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1006676015154|
|Abstract:||"Customer Retention" is an increasingly pressing issue in today's ever-competitive commercial arena. This is especially relevant and important for sales and services related industries. Motivated by a real-world problem faced by a large company, we proposed a solution that integrates various techniques of data mining, such as feature selection via induction, deviation analysis, and mining multiple concept-level association rules to form an intuitive and novel approach to gauging customer loyalty and predicting their likelihood of defection. Immediate action triggered by these "early-warnings" resulting from data mining is often the key to eventual customer retention.|
|Source Title:||Artificial Intelligence Review|
|Appears in Collections:||Staff Publications|
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