Enabling Customer Reward with a Hybrid Intelligent System (Case Study: J&J Shopping Mall)
@article{Uko2017EnablingCR, title={Enabling Customer Reward with a Hybrid Intelligent System (Case Study: J\&J Shopping Mall)}, author={Okon E. Uko and P. Enyindah and Enefiok A. Etuk}, journal={International Journal of Computer Applications}, year={2017}, volume={168}, pages={15-22} }
A reward program (also known as a loyalty program) is a marketing technique often adopted by some companies to appreciate customers who frequently make purchases with such companies. Normally, this kind of program leads to giving a loyal customer gifts in forms of customer free merchandise, coupons, rewards and advance released products. In most situations, reward programs in these companies are often biased due to the mechanism employed in determining a loyal customer. Hence, this article…
References
SHOWING 1-10 OF 14 REFERENCES
Classifying the segmentation of customer value via RFM model and RS theory
- Business, Computer ScienceExpert Syst. Appl.
- 2009
A Model for Detecting Customer Level Intentions to Purchase in B2C Websites Using TOPSIS and Fuzzy Logic Rule-Based System
- Business
- 2014
This paper presents a model using TOPSIS and fuzzy logic for detecting the level of customer intentions to purchase against factors affecting the intention to purchase in business-to-customer (B2C) websites based on customer’s perception of B2C websites.
Building comprehensible customer churn prediction models with advanced rule induction techniques
- Computer ScienceExpert Syst. Appl.
- 2011
Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty
- BusinessExpert Syst. Appl.
- 2010
Analytical Customer Relationship Management for Garage Services Recommendation Using the Generalized Sequential Pattern Method
- Computer Science
- 2015
GSP Algorithm is implemented in this study in order to find customer service pattern both sequentially and simultaneously in order for management’ precise decision making base to be found.
Customer churn prediction using improved balanced random forests
- Computer ScienceExpert Syst. Appl.
- 2009
Concurrent Reinforcement Learning from Customer Interactions
- Computer Science, BusinessICML
- 2013
This paper presents the first framework for concurrent reinforcement learning, using a variant of temporal-difference learning to learn efficiently from partial interaction sequences, in applications in which a company interacts concurrently with many customers.
ID3 Algorithm to Identify Customer Loyalty Factor at Semarang Ceramics Company
- Business
- 2013
The result of this research is Responsiveness attribute and its indicator quick service to the customer is the main factor which is influence the customer loyalty.