In response to your inquiry : Automatic e-mail answer suggestion in a Dutch Contact Centre

Abstract

In the past years, the number of service requests through e-mail has shown an explosive growth, forcing companies and government to set-up contact centres in order to handle these e-mails. Equal to most telephony services handled by call centres, 80% of the incoming e-mails is about 20% of the subjects, making it worthwhile to compose standard answers for at least the 20% most popular questions. Personal answering (each e-mail answered by a human agent) is simply too expensive and not necessary due to this 80-20 rule: well formed predefined answers can cover a significant part of the questions. By using IR and text classification techniques combined with Natural Language Processing, the process of finding the correct answer for a request can be (partly) automated. In this paper we will describe an answer suggestion system using IR based classification and NLP techniques. A practical study using an e-mail corpus of 17,000 incoming e-mails (collected and categorized in a Dutch contact centre), has shown that this approach is able to present the correct answer within a ranked list of 5 possible suggestions, for almost 88% of all incoming emails. Furthermore, we will show that this approach can be used as well for spoken content by combining the categorization techniques with the recognition result of the answer on the famous first question: ”Hello, how can we help you?”.