In recent years, an element of CRM; eCRM has become a topic of major importance. However, the wireless medium as an element of CRM is rarely taken into consideration and the literature concerning mCRM is scarce. In an attempt to fill this void, this dissertation provides insights into mCRM and data mining solution for mining customer’s information from customer opt-in database. We divide the dissertation into two segments. The first segment investigates a new data mining technique and compares….
Contents
Chapter 1
Introduction
Motivation for Data Mining
CRM
Internet CRM (eCRM)
Mobile CRM (mCRM)
Complexity of CRM
Research focus
Demarcations
Outline of the study
Chapter 2
Introduction to Data Mining
Data Mining
Classification
Association Rule Mining (ARM)
Apriori
Associative Classification
Main Differences between ARM and AC
AC Main Steps
Classification Based on Associations (CBA)
CBA (2) (Classification Based on Associations)
Experimental Work
Design of AC Algorithm based on Apriori Candidate Generation
Main Aim of the Implementation
The Proposed Rule Discovery Algorithm
Experimental results
Results of Apriori for Weather dataset
Results of New Propose Approach for Weather Dataset
Chapter 3 Mobile CRM
Objectives of CRM systems
Introduction
Initiation Stage of Mobile CRM (mCRM)
Trust
Identification
Permission
Value Chain Creation for mCRM
Contents
Cross-media Marketing
Campaign Management
Customer Database
Carrier Co-operation
Building value to mobile service
Movement awareness
Moment awareness
Networking
Personalized Service
Cost effectiveness of mCRM
Spamming
Permission marketing as a CRM strategy
Looking ahead
Chapter 4
Conceptualization
Research Methods
Chapter 5
Research Findings
Analysis of some important survey questions
Examining a Statistically significant difference
Final Conclusion
Appendix
Appendix A
References
Author: Mohammad Turk
Source: Blekinge Institute of Technology
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