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Title: Evaluating the satisfaction index using automated interaction service and customer knowledgebase: a big data approach to CRM

Authors: H.S. Chiranjeevi; Manjula K. Shenoy; Syam S. Diwakaruni

Addresses: Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, 576104, India ' Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, 576104, India ' IBM India Private Limited, Hyderabad, 500032, India

Abstract: Organisations need to understand their customer's requirements to outlive in this competitive world. Today, the customer interaction bots, which can handle multiple customers anywhere-anytime are attracting many business communities to have better customer relationship management (CRM). Searching for specific information seems to be interesting to provide a real value to customers, but the challenge is to get the reliable information for the customer's queries. The implementation of customer interaction bot is carried out using text document dataset. We have used LUIS, which provides a platform to build intelligent customer-computer applications that can understand the customer's requirements and responds to their queries. Text document data is indexed; the database is connected to direct line bot framework. The knowledgebase is implemented for customer queries based on needs, expectations, wants/desires, and complaints/problems. The proposed system evaluates the customer satisfaction based on customer bot interaction knowledgebase to achieve a better CRM.

Keywords: automation; big data; customer relationship management; CRM; customer satisfaction index; entities; intelligent learning; intents; interaction bot; knowledgebase; language understanding intelligent service; LUIS; Microsoft bot; utterances.

DOI: 10.1504/IJECRM.2019.098976

International Journal of Electronic Customer Relationship Management, 2019 Vol.12 No.1, pp.21 - 39

Received: 14 Oct 2017
Accepted: 22 Sep 2018

Published online: 21 Mar 2019 *

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