Customer relationship management with RFID : a dynamic pricing approach for personalized promotion
This project researches on the usage of data mining and dynamic pricing to implement personalized promotion for Customer Relationship Management (CRM) in realtime with the usage of Radio Frequency Identification technology (RFID). The project draws on established theories and algorithms in CRM, da...
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sg-ntu-dr.10356-396302023-03-04T19:01:20Z Customer relationship management with RFID : a dynamic pricing approach for personalized promotion Tan, Wil Sern. Lee Ka Man, Carman School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering This project researches on the usage of data mining and dynamic pricing to implement personalized promotion for Customer Relationship Management (CRM) in realtime with the usage of Radio Frequency Identification technology (RFID). The project draws on established theories and algorithms in CRM, data mining, dynamic pricing and RFID to establish a system for personalized promotion dynamic pricing. Data mining techniques such as Cluster Analysis, Association Mining and Sequential Pattern Mining are utilized to obtain information about customer shopping behaviour. Subsequently, dynamic pricing strategies such as Goal-Directed strategy and Derivative-Following strategy are employed for the dynamic pricing module of the system. RFID is used mainly as an interface for real-time customer identification and tracking purposes. The Personalized Promotion Dynamic Pricing System is proposed in this project. The system integrates the data mining and dynamic pricing modules and takes into account customersʼ purchase history and current purchasing pattern to predict the customersʼ needs and provide personalized promotional discounts. This information is then relayed to the customer via the various customer touch points. As the project requires in depth skills and knowledge from diverse fields of studies such as IT, marketing skills, systems engineering and software programming, which the author do not possess, the report focuses only on the conceptualization and modeling of the system rather than the implementation. Among the foreseen benefits of implementation of the Personalized Promotion Dynamic Pricing System in businesses include a seamless and holistic customer shopping experience, improved customer loyalty and increased organization sales revenue. This project offers an insight into how data mining, dynamic pricing and RFID can be integrated to provide a real-time customer relationship management, which would provide customers with a better shopping experience and benefits organizations in terms of increased customer loyalty and sales revenue. Bachelor of Engineering (Mechanical Engineering) 2010-06-02T00:46:28Z 2010-06-02T00:46:28Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/39630 en Nanyang Technological University 96 p. application/pdf |
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DRNTU::Engineering::Mechanical engineering Tan, Wil Sern. Customer relationship management with RFID : a dynamic pricing approach for personalized promotion |
description |
This project researches on the usage of data mining and dynamic pricing to
implement personalized promotion for Customer Relationship Management (CRM) in realtime with the usage of Radio Frequency Identification technology (RFID).
The project draws on established theories and algorithms in CRM, data mining,
dynamic pricing and RFID to establish a system for personalized promotion dynamic
pricing. Data mining techniques such as Cluster Analysis, Association Mining and
Sequential Pattern Mining are utilized to obtain information about customer shopping
behaviour. Subsequently, dynamic pricing strategies such as Goal-Directed strategy and
Derivative-Following strategy are employed for the dynamic pricing module of the system.
RFID is used mainly as an interface for real-time customer identification and tracking purposes.
The Personalized Promotion Dynamic Pricing System is proposed in this project.
The system integrates the data mining and dynamic pricing modules and takes into
account customersʼ purchase history and current purchasing pattern to predict the
customersʼ needs and provide personalized promotional discounts. This information is
then relayed to the customer via the various customer touch points.
As the project requires in depth skills and knowledge from diverse fields of studies
such as IT, marketing skills, systems engineering and software programming, which the author do not possess, the report focuses only on the conceptualization and modeling of the system rather than the implementation.
Among the foreseen benefits of implementation of the Personalized Promotion
Dynamic Pricing System in businesses include a seamless and holistic customer shopping
experience, improved customer loyalty and increased organization sales revenue.
This project offers an insight into how data mining, dynamic pricing and RFID can
be integrated to provide a real-time customer relationship management, which would
provide customers with a better shopping experience and benefits organizations in terms of increased customer loyalty and sales revenue. |
author2 |
Lee Ka Man, Carman |
author_facet |
Lee Ka Man, Carman Tan, Wil Sern. |
format |
Final Year Project |
author |
Tan, Wil Sern. |
author_sort |
Tan, Wil Sern. |
title |
Customer relationship management with RFID : a dynamic pricing approach for personalized promotion |
title_short |
Customer relationship management with RFID : a dynamic pricing approach for personalized promotion |
title_full |
Customer relationship management with RFID : a dynamic pricing approach for personalized promotion |
title_fullStr |
Customer relationship management with RFID : a dynamic pricing approach for personalized promotion |
title_full_unstemmed |
Customer relationship management with RFID : a dynamic pricing approach for personalized promotion |
title_sort |
customer relationship management with rfid : a dynamic pricing approach for personalized promotion |
publishDate |
2010 |
url |
http://hdl.handle.net/10356/39630 |
_version_ |
1759854314247946240 |