Evaluation of e-Word-of-Mouth through Business Intelligence processes in banking domain

Abstract

Social networks and Internet discussions are valuable sources for a company’s marketing research and public relations management. The Internet is full of public communication in an unstructured form and reflects recent movements of contributors' perception of the company, brand, products, competitors or whole market. As one of the approaches to achieve a better view we propose to design metrics which should be followed in order to get valuable insight where the company stands in terms of its customers. This paper focuses on obtaining an e-Word-of-Mouth in the banking sector using publicly available data. The main goal is to design metrics and dashboards evaluating customers’ perception of a bank’s services based on the analysis of public Facebook sites and web discussions related to several banks in the Czech Republic. We studied several approaches to unstructured data analysis. Thus we present complementary findings in classification of the unstructured data analysis presentation as a set of summarised metadata, top peaks of primary qualitative data and results of automated semantic analysis of the unstructured data. Based on the result we discuss the possible value of an unstructured data analysis and related systems. We find out that the value could be in the identification of opportunities and threats in the market by unexpected movements in public opinion of the Internet crowd, which we suggest to explore in future research. The benefit of this report is to describe the processing of data that can be obtained with emphasis on their content, their further enrichment, and their users.

Integration of textual VoC into a CX data model for business intelligence use in B2C

“…The customer interacts with the company and its other customers or prospects through different channels. An example of the process of collection of initial data from two different sources through web crawling and application interface is described in Šperková, Škola and Bruckner (2015). The data are transferred in a clearly defined format suitable for storage in the relational database.…”

“…The proposed CX data model follows and builds on the author's previous research on the integration of VoC into BI in the banking domain (Šperková, 2014;Šperková andŠkola, 2015a, 2015b;Šperková, Škola and Bruckner, 2015;Vencovský, Bruckner and Šperková, 2016). The model exploits data from analytical CRM.…”