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

H. S. Chiranjeevi, Manjula K. Shenoy, Syam S. Diwakaruni

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)21-39
Number of pages19
JournalInternational Journal of Electronic Customer Relationship Management
Volume12
Issue number1
DOIs
Publication statusPublished - 01-01-2019
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)

Fingerprint Dive into the research topics of 'Evaluating the satisfaction index using automated interaction service and customer knowledgebase: A big data approach to CRM'. Together they form a unique fingerprint.

Cite this