How Speech Analytics Can Remove the Stigma From Self-Service


Colin Whelan of Aspect Software shares how speech analytics can be used to improve service quality.

What springs to mind when you think of self-service? It is understandable why some consumers feel sidelined when they are passed on to an outdated switchboard that tries to categorise their problem into four or five options to choose from.

Traditionally, consumers would zone out when ambushed with these systems, and would do their best to get hold of a live operator as soon as possible. This largely comes down to a general perception of self-service, as previous systems have put operational efficiency ahead of customer service and satisfaction.

But this stigma is being shattered by a new generation of technologies that make self-service truly productive, and in many circumstances preferable. Developments in speech analytics have played a massive role in this, equipping machines with a sophisticated understanding of language and the capacity to truly listen to customers’ queries.

Just a few years ago, voice recognition accuracy was only at around 70%, but technological advances mean that this figure now sits at 95%. This makes a world of difference when it comes to the ability to extract valuable information and offer immediate solutions to customers.

Such is the pace of change that people are now actively choosing to integrate these systems into their everyday lives. Take for example, Amazon’s Alexa or Apple’s Siri. These personal assistants add real value to peoples’ lives by listening and responding to complex instructions in real time. This means that by now, just about everyone has had a positive experience with speech recognition, resulting in a new image of talking to a computer.

This new relationship between humans and machines must not be ignored by businesses, particularly when you take into account its vast implications on customer service.

Self-Categorisation

One of the main ways in which speech analytics is improving customer engagement is through intelligent categorisation of phrases and language.

Early examples of speech analytics would require systems to know categories and typical enquiries in advance and operated by listening for assigned words and phrases.

New systems are able to automatically understand these phrases, however, and discover underlying trends in speech without manual intervention or planning. This greatly opens up the capabilities of self-service, and enables more complex and irregular problems to be solved with ease.

This means that a customer’s query is far more likely to be solved by a self-service system, resulting in higher first call resolution rates and contributing to overall customer satisfaction.

Automated Agent Scoring

Identifying calls that do not meet company standards and addressing the root cause of what happened is of utmost importance.

However, no contact centre has the time or resources to manually monitor all interactions between agents and customers and flag where a mistake has been made.

By being proactive in identifying skill gaps or broken internal processes, organisations can remain one step ahead and address areas where improvement is needed far more effectively.

Developments in speech analytics mean that calls can now be monitored and automatically scored based on an organisations’ key performance indicators (KPIs) for quality. This is advantageous as it greatly reduces the resources and time needed for monitoring, removes supervisor bias and covers 100% of interactions, rather than just a minority.

Reduced Agent Stress

It is clear that happy agents result in better interactions, and consequently happier customers.

Research shows that some of the most prevalent causes of agent stress include pace of work being too fast, complaints and problems, complexity of work and personality conflicts. It is human for these annoyances to affect employee morale and quality of service, and it is a manager’s responsibility to identify these problems and work with the agent to find a solution.

Speech analytics provides an excellent mechanism to do this, by identifying specific stress inducers, such as the nature of frequent complaints and problems. Once known, these problems can be addressed by working with the agent and putting in place targeted coaching and adjustments where necessary.

Furthermore, these systems enable employees to access the same quality management data as their supervisors, empowering them to manage their own development and reducing the risk of any overbearing micro-management.

Making the Most of These Technologies

As these technologies continue to redefine self-service, businesses must act quickly to take advantage of them or risk being left by loyal customers that are increasingly exposed to higher standards of service.

Colin Whelan

Colin Whelan

Human to customer engagement will always play a pivotal role in customer service, and speech analytics can greatly aid the call-handling process, enabling solutions to be provided at unprecedented speed and convenience.

Businesses should consider this evolving image of self-service and re-evaluate their engagement models accordingly to avoid becoming an outdated annoyance to their customers.

To find out more about Aspect Software, visit: www.aspect.com

Published On: 19th Jul 2018 - Last modified: 24th Jul 2018
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