Artificial Intelligence for Customer Relationship Management : Keeping Customers Informed / by Boris Galitsky.

Format:

Book

Author/Creator:

Galitsky, Boris, Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Human-computer interaction series 2524-4477

Human-Computer Interaction Series, 2524-4477

Language:

English

Subjects (All):

User interfaces (Computer systems).

Human-computer interaction.

Customer relations-Management.

Artificial intelligence.

Computer simulation.

User Interfaces and Human Computer Interaction.

Customer Relationship Management.

Artificial Intelligence.

Computer Modelling.

Local Subjects:

User Interfaces and Human Computer Interaction.

Customer Relationship Management.

Artificial Intelligence.

Computer Modelling.

Physical Description:

1 online resource (XI, 445 pages) : 261 illustrations, 147 illustrations in color.

Edition:

1st ed. 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

This research monograph brings AI to the field of Customer Relationship Management (CRM) to make a customer experience with a product or service smart and enjoyable. AI is here to help customers to get a refund for a canceled flight, unfreeze a banking account or get a health test result. Today, CRM has evolved from storing and analyzing customers' data to predicting and understanding their behavior by putting a CRM system in a customers' shoes. Hence advanced reasoning with learning from small data, about customers' attitudes, introspection, reading between the lines of customer communication and explainability need to come into play. Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers' frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently. Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals. .

Contents:

Introduction

Distributional Semantics for CRM: Making word2vec Models Robust by Structurizing Them

Employing Abstract Meaning Representation to Lay the Last Mile towards Reading Comprehension

Summarized Logical Forms for Controlled Question Answering

Summarized Logical Forms based on Abstract Meaning Representation and Discourse Trees

Acquiring New Definitions of Entities

Inferring Logical Clauses for Answering Complex Multi-hop Open Domain Questions

Managing Customer Relations in an Explainable Way

Recognizing Abstract Classes of Text Based on Discourse

Conversational Explainability for CRM.

Other Format:

Printed edition:

ISBN:

978-3-030-52167-7

9783030521677

Access Restriction:

Restricted for use by site license.