Speech Analytics for Actionable Insights: Current Status, Recommendation, and Guidance

J. P. Shim, Aaron M. French and Bikesh Upreti

Foundations and Trends(R) in Information Systems, 2020, vol. 4, issue 3, 213-274

Abstract: In today’s hypercompetitive customer-centric marketplace, every enterprise strives to gain competitive advantage through customer loyalty, high customer satisfaction and low customer turnover. Through the use of a combination of tools such as analytic technologies, and data-mining techniques and access to real-time data, companies are now able to place a greater emphasis on customer engagement and satisfaction. Today’s increased enforcement of standards and stricter legal compliance rules have led call centers to take proactive steps to ensure that enforcement is in compliance with regulations through the use of speech analytics. In the realm of analytic technologies, speech analytics is quickly becoming one of the most demanded technologies in customer engagement optimization and the fastest growing technology in call centers. Organizations have been searching for ways to translate this wealth of information into holistic, accurate, and actionable insights. The nascent technology is increasingly in more demand as its features become more relevant for call centers, and as organizations seek to capture the voice of the customer (VoC), or the customers’ wants and needs, and improve first call resolution (FCR) through post-call and real-time solutions. Speech analytics is a complementary approach for organizations driving optimization, personalization and targeting across their digital channels. Since the latest real-time voice/speech analytics technology can mine 100% of the company’s voice contacts, organizations can now be much more successful in capturing and tagging the reasons for the customers’ call. Given today’s ubiquitous computing trends, such as mobile voice and digital data stream, post-call and real-time applications are solutions to capture the voice of the customer, and improve operations and efficiency, customer experiences, and improve customer loyalty.

Keywords: Speech and spoken language processing; Audio signal processing; Interdisciplinary influence: Artificial intelligence and the user interface; Information systems and organizations: Business analytics; Customer Relationship Management (search for similar items in EconPapers)
Date: 2020
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