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

Organisations need to understand their customer’s requirements to outlive in this competitive world. Handling customer service is a key challenge for the organisations. Today the customer interaction bots with an automated customer service, 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 major problem in customer-computer interactions is the ability to understand the reliable information of the computer to the customers’ requirements. Many organisations maintain the data in the text form. The implementation of customer interaction bot is carried out using a data set created for text document data. The interaction bot receives customer query, send request for correct analysis and responds to customers with the required information. We have used Language Understanding Intelligent Service (LUIS), a cognitive service and bot emulator, which provides a platform for developers 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 knowledge base is implemented for customer queries based on needs, expectations, wants/desires, and complaints/problems. The proposed system evaluates the customer satisfaction index to achieve a better customer relationship management.