Machine Intelligence in Customer Relationship Management in Small and Large Companies

Author:

Sawal Ainul Balqis1,Ahmad Muneer2,Muralitharan Mitra Anusri1,Loganathan Vinoshini1,Jhanjhi N. Z.3ORCID

Affiliation:

1. Universiti Malaya, Malaysia

2. Universiti Malaya, Malaysia & School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan

3. Taylor's University, Malaysia

Abstract

The current problem with CRM is weak marketing, as there is no individualization strategy, low productivity, and blurred marketing objectives. Next, companies are failing to completely capitalize on and extract useful information from a vast collection of databases. Organizations were also unable to adequately evaluate consumer behaviors and customer expectations that contribute to poor vendor-customer relationships and decrease customer loyalty. Most companies are seeking innovative ways to develop their CRM as it helps to challenge new ways of marketing and growing income, as customer loyalty and sales rely on one another. Whereas some businesses are incorporating data mining techniques in the management of CRM, there are several disadvantages in the market basket analysis, and one of the main drawbacks is that it is difficult to distinguish interesting patterns, as the number of rules obtained is very high. However, we might assume that it is computationally efficient as a minimum support value of 60% with a minimum confidence value of 80%.

Publisher

IGI Global

Reference22 articles.

1. Akhmedov, R. (2017). Implementation of CRM Strategies to Increase Customer Loyalty, Case of Kazakhstan Companies. Academic Press.

2. The Development of a Strategic CRM-i Framework: Case Study in Public Institutions of Higher Learning

3. Customer Relationship Management System: A case study of Floor Mills Bahawalpur District.;A. G.Awan;British Journal of Marketing Studies,2014

4. Bezabeh, B. B. (2017). The application of data mining techniques to support customer relationship management: the case of ethiopian revenue and customs authority. arXiv preprint arXiv:1706.10050.

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