Abstract
This paper proposes a method that predicts customer value by focusing on purchasing behavior. The method generates a relevance model for purchase days and amount in each period between customer value and purchasing histories beforehand based on a consumer panel survey. The authors adopt the random forest method to generate the prediction model. The proposed method facilitates the provisioning of smart customer management to each customer according to level such as suggesting products or services.
Original language | English |
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Title of host publication | Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018 |
Editors | Leonard Barolli, Tomoya Enokido, Marek R. Ogiela, Lidia Ogiela, Nadeem Javaid, Makoto Takizawa |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 320-326 |
Number of pages | 7 |
Volume | 2018-May |
ISBN (Print) | 9781538621943 |
DOIs | |
Publication status | Published - 2018 Aug 9 |
Event | 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018 - Krakow, Poland Duration: 2018 May 16 → 2018 May 18 |
Other
Other | 32nd IEEE International Conference on Advanced Information Networking and Applications, AINA 2018 |
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Country/Territory | Poland |
City | Krakow |
Period | 18/5/16 → 18/5/18 |
Keywords
- Customer Level Prediction
- Purchasing Data
- Random Forest
ASJC Scopus subject areas
- Engineering(all)