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W H I T E P A P E R
© 2017 Persistent Systems Ltd. All rights reserved. 3
www.persistent.com
1. Introduction
Customer relationship and support is key for companies and enterprises to succeed. Companies spend hours
and hours training resources to handle and improve customer support and interaction. This however is muted to
certain extent by training cost, lack of extensive domain knowledge and business process, outsourcing
challenges and infrastructure challenges.
Having elaborate FAQs, user manual on websites is no longer amuse customers. People prefer phone calls to
reading long FAQ or interacting over web. Companies and enterprises are adopting to innovative ways to
interact with customer and improve relationship and service. “Chatbots” have surged in recent past that assist
users in common day to day activities ranging from getting information, booking a ticket to placing food order.
More and more providers are making available cognitive services powered by machine learning to reduce gap
and improve human-machine- interaction. More and more questions get asked to Siri, Google Now and Cortana
across countries, multiple languages and regional dialects.
Voice and natural language is the new way of interacting with machines. Using voice and natural language
understanding makes it possible to reach to a larger audience, simplify operations and build a more lasting
relationship with users and customers.
This white paper discuss and presents various options as how traditional IVR (Interactive Voice Response)
systems can be made smarter to make use of cognitive services, natural language understanding and natural
language processing. Typical use of IVR systems is in customer service and helpdesk and varies across various
industries like banks, automobiles, telecom, consumer electronics andmany more.
2. ProblemStatement
The IVR systems have evolved over time. Integrated with enterprise apps, customer support agents can
address customer issues and concerns with greater confidence. The integrated IVR systems makes customer
context available to the customer service agent which helps address customer issues and concerns in a better
way. However this does not scale always resulting in longer wait time for customers, call switching and call
transfers adding to customer frustration and insufficient or inadequate domain knowledge to address concerns
or queries.
The IVR systems are also rigid in terms of services that are provided to end customers. Hierarchical menu
selection to get to the desired service level is always a pain point for customer.
In this white paper we will discuss about the transformation for customer interaction using voice agents without
altering the traditional ways i.e. users call in for help. This works great with old as well as younger user-base as it
makes use of existing infrastructure like telephone systems and users need not adopt and learn about any new
technology to reach out for support.