Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm
In the world of retailer, customers typically patronize multiple shops thus making loyalty programs a favorite among retailer to retain their customers. Loyalty programs are utilized across many different businesses as a marketing strategy to encourage customers to continuously shop or patronize the...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.sunway.edu.my/1207/ http://eprints.sunway.edu.my/1207/1/Angela%20Lee%20Decision%20Tree.pdf |
| _version_ | 1848801998647853056 |
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| author | Lee, Angela Siew Hoong * Zuraini Zainol, Ng, Claudia Chan, Khin Whai |
| author_facet | Lee, Angela Siew Hoong * Zuraini Zainol, Ng, Claudia Chan, Khin Whai |
| author_sort | Lee, Angela Siew Hoong * |
| building | SU Institutional Repository |
| collection | Online Access |
| description | In the world of retailer, customers typically patronize multiple shops thus making loyalty programs a favorite among retailer to retain their customers. Loyalty programs are utilized across many different businesses as a marketing strategy to encourage customers to continuously shop or patronize the services provided by a certain organization. However, one of the biggest problem faced by these businesses is customer churn. The purpose of this research was to build a predictive model, which could predict customer churn, where visualization of data was generated to better understand the existing members and see the patterns and behavior demonstrated by members of the loyalty program. Through these, meaningful insights about the businesses’ analysis on customers could be gathered and utilized for better actions which could be taken to address the issues which the company faces. At the end, based on the issues found, strategies were proposed to address the issues found. For this research, SAS Enterprise Miner was used to perform predictive analysis while Tableau was used to perform descriptive analysis. |
| first_indexed | 2025-11-14T21:16:22Z |
| format | Conference or Workshop Item |
| id | sunway-1207 |
| institution | Sunway University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:16:22Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | sunway-12072020-10-07T04:57:55Z http://eprints.sunway.edu.my/1207/ Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm Lee, Angela Siew Hoong * Zuraini Zainol, Ng, Claudia Chan, Khin Whai QA76 Computer software In the world of retailer, customers typically patronize multiple shops thus making loyalty programs a favorite among retailer to retain their customers. Loyalty programs are utilized across many different businesses as a marketing strategy to encourage customers to continuously shop or patronize the services provided by a certain organization. However, one of the biggest problem faced by these businesses is customer churn. The purpose of this research was to build a predictive model, which could predict customer churn, where visualization of data was generated to better understand the existing members and see the patterns and behavior demonstrated by members of the loyalty program. Through these, meaningful insights about the businesses’ analysis on customers could be gathered and utilized for better actions which could be taken to address the issues which the company faces. At the end, based on the issues found, strategies were proposed to address the issues found. For this research, SAS Enterprise Miner was used to perform predictive analysis while Tableau was used to perform descriptive analysis. 2019-09-24 Conference or Workshop Item PeerReviewed text en cc_by_nc_4 http://eprints.sunway.edu.my/1207/1/Angela%20Lee%20Decision%20Tree.pdf Lee, Angela Siew Hoong * and Zuraini Zainol, and Ng, Claudia and Chan, Khin Whai (2019) Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm. In: Soft Computing in Data Science: 5th International Conference, SCDS 2019 Proceedings, August 28–29, 2019, Iizuka, Japan. https://link.springer.com/chapter/10.1007/978-981-15-0399-3_2 |
| spellingShingle | QA76 Computer software Lee, Angela Siew Hoong * Zuraini Zainol, Ng, Claudia Chan, Khin Whai Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm |
| title | Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm |
| title_full | Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm |
| title_fullStr | Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm |
| title_full_unstemmed | Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm |
| title_short | Decision Tree: Customer churn analysis for a loyalty program using data mining algorithm |
| title_sort | decision tree: customer churn analysis for a loyalty program using data mining algorithm |
| topic | QA76 Computer software |
| url | http://eprints.sunway.edu.my/1207/ http://eprints.sunway.edu.my/1207/ http://eprints.sunway.edu.my/1207/1/Angela%20Lee%20Decision%20Tree.pdf |