Improving Data Quality in Intelligent eCRM Applications

Improving Data Quality in Intelligent eCRM Applications

Copyright: © 2018 |Pages: 11
DOI: 10.4018/978-1-5225-2255-3.ch140
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Abstract

Today most of the businesses are in continuous search of sophisticated tools and techniques to progressively grow their business. And therefore, the use of intelligence systems has found its pace in the global market. The intelligence systems has mostly effected the E-CRM as it is the most critical and central part for the growth of the business. The E-CRM approaches have enhanced drastically with an integration of the business intelligence systems and organizations are now diligently striving for excellence by gaining benefit from these integrated systems. However, there are many organizations which lag behind in escalating their progress and growth as they have not yet understand how to improve the data quality by using business intelligence systems and therefore used it for decision making. Hence, the following research is conducted to study the implementation trends of Intelligence E-CRM in business process and how the business intelligence systems could help in improvising the data quality and the business processes.
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Background

Various studies have been done before by a number of scholars as far as the quality and accuracy of data in e-CRM systems are concerned. Research on optimising the value of e-CRM application in E-commerce aims at determining the responsive prospect of customers to E-commerce applications (Ahmed, Maati & Al Mohajir, 2015a). The study revealed that customers often become frustrated if the e-CRM system is redundant and incapable of meeting their needs and expectations. A revelation from the study is that quality of data goes far deeper to include ergonomic relationships (Ahmed, Maati & Al Mohajir, 2015a, pg. 150). As such, any design or approach to improve data quality must measure and ascertain that the implementation of an e-CRM system meets the ergonomic conditions. With the study aiming to determine whether potential customers can respond to the e-CRM application, the researchers established that culmination of the application should deal with all customer-related issues. Such issues include customer services facilitation, sales and marketing, and field support (Ahmed, Maati & Al Mohajir, 2015a, pg. 152).

In addition to data quality issues, companies embracing e-CRM systems face difficulties in developing effective technological infrastructure considering the limited time and resources (Ahmed, Maati & Al Mohajir, 2014, pg. 214). A recent study revealed that 66 percent of loaded orders are discarded before checkout, and only 5 percent of customers who visit organisations’ online stores become customers (Ahmed, Maati & Al Mohajir, 2014, pg. 214). The aim of the research was to show that E-CRM is not limited to internet data but includes other devices such as phones, set-top boxes, pagers and so forth.

In another research by same authors, Ahmed, Maati, and Al Mohajir on how to improve the E-CRM intelligence by using CRM data analytic tools such as OLAP, data mining and web analytics, it was established that CRM analytics tools not only contribute to exceptionally productive customer relationship as regards sales and service delivery but in the development of adverts, planning, and the analysis of customer data as well (Ahmed, Maati & Al Mohajir, 2015b, pg. 7). As such, it is evident that real experience for an online client is dependent on an intelligent, concise, and convenient application.

Key Terms in this Chapter

Organization: Place where operator Intelligence of E-CRM systeme such as institutions and companies etc..

E-CRM.Systems: Electronic Customer Relationship Management system encompasses all the CRM functions with the use of the net and organizations environment.

Data Quality: The level of quality of data from E-CRM application (this is our subject).

Intelligence: One of the features that have E-CRM systems and their process.

Process: All about related of business generated from Intelligence of E-CRM application.

Business: Business envirement which operates in Intelligence of E-CRM.

Relationship Management: Strategy in which a continuous level of engagement is maintained between an organization and Intelligence of E-CRM application.

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