Improving Service Quality Using Consumers’ Complaints Data Mart which Effect on Financial Customer Satisfaction

Author:

Khalaf Hamoud Alaa,Noori Hussien Hisham,Akram Fadhil Arwa,Raad Ekal Zahraa

Abstract

Abstract One of the best ways to enhance the performance of all companies and manage Customer Satisfaction is to get the consumers’ complaints and analyze them in order to fix them. These complaints represent the consumers’ behavior to the companies and how these company’s response to them. Besides, customers’ satisfaction is the main goal of all companies and this goal cannot achieve if they do not handle the customers’ complaints. The paper represents a framework of complaint data mart construction where the source data are thousands of complaints about services and financial products of companies. The data mart represents the first step to implement an enterprise data warehouse (DW) to support strategic decisions. Reports are constructed to help analysts and decision-makers to support their decisions related to consumers’ complaints and how to improve service quality. Two different categories of on-line analytical processing (OLAP) reports are used, offline and web OLAP reports. The two types of reports provide a deep view of the data and present the analysts with flexible charts that can be used in supporting strategic decisions. SQL Server Management Studio (SSMS), SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), SQL Server Reporting Services (SSRS) 2014 beside SQL Server Data Tools (SSDT) 2013 is used to build the data mart staging table, schema, cube, and OLAP reports. MS Excel Pivot table 2010 is used also to import the cube and build offline reports and implementing OLAP processes. This data mart can be utilized by consumers themselves besides decision-makers and analysts. The data mart can measure how the companies fix complaints issues and prevent them from occurring again and identify the factors that influence financial customers’ satisfaction.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference39 articles.

1. A Methodological Approach to Data Quality Management Supported by Data Mining;Grimmer,2001

2. Investigating the post-complaint period by means of survival analysis;Lariviere;Expert Syst. Appl.,2005

3. Enabling customer relationship management in ISP services through mining usage patterns;Li;Expert Syst. Appl.,2006

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