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Published in:
Chatbots for CRM and Dialogue Management Read chapter Read first chapter

2021 | OriginalPaper | Chapter

5. Concluding a CRM Session

Author : Boris Galitsky

Published in: Artificial Intelligence for Customer Relationship Management

Publisher: Springer International Publishing

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Abstract

We address the issue of how to conclude a CRM session in a comprehensive manner, to satisfy a user with the detailed extended answer with exhaustive information. For a question-answering session, the goal is to enable a user with thorough knowledge related to her initial question, from a simple fact to a comprehensive explanation. In many cases, a lengthy answer text, including multimedia content compiled from multiple sources, is the best. Whereas comprehensive, detailed answer is useful most of the times, in some cases, such an answer needs to defeat a customer claim or demand when it is unreasonable, unfair or is originated from a bad mood. We formulate a problem of finding a defeating reply for a chatbot to force completion of a chatbot session. Defeating a reply is expected to attack the user claims concerning product usability and interaction with customer support and provide an authoritative conclusive answer in an attempt to satisfy this user. We develop a technique to build a representation of a logical argument from discourse structure and to reason about it to confirm or reject this argument. Our evaluation also involves a machine learning approach and confirms that a hybrid system assures the best performance finding a defeating answer from a set of search result candidates.

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previous chapter A Virtual Social Promotion Chatbot with Persuasion and Rhetorical Coordination
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Metadata
Title
Concluding a CRM Session
Author
Boris Galitsky
Copyright Year
2021
Book
Artificial Intelligence for Customer Relationship Management

Print ISBN: 978-3-030-61640-3

Electronic ISBN: 978-3-030-61641-0

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-61641-0_5