Walter Lash

5 Reasons Why Your Contact Center Needs Conversation Analytics

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analyticsCustomer service has always been a fundamental part of any business. However, it may be more important than ever for several very important reasons. First, thanks to the Internet, mobile technology, and same-day service, customers have become accustomed to getting fast service. They have less patience than ever before and will quickly move to a competitor if they offer faster, more convenience service. Second, it now only takes one disgruntled customer to post an angry message on Facebook or other social media channel to cause a brand-tarnishing incident that can shoo away many current and potential customers. In other words, there is no longer any margin for error when it comes to the customer experience (CX). It has to be consistently exceptional to sustain competitiveness.

To keep customers happy, you need to be able to anticipate their needs. This requires analytics. Thanks to advanced contact center technology, there are many types of analytics that can be leveraged to improve CX. These include performance analytics that can measure the effectiveness of your workforce, self-service analytics that evaluate the customer experience on self-service channels, and web analytics that help to understand a customer’s activity before they even reach the contact center.

Conversations can also be analyzed across voice channels – phone and/or interactive voice response (IVR). More than half of all contact centers currently use some form of speech analytics tools to analyze conversations taking place on voice channels. This percentage is growing quickly because companies are gaining a better understanding of the importance of voice within today’s multi-channel contact center environment.

So how can companies best utilize conversation analytics? Here are just some of the ways this valuable data can be leveraged.

Improve First-Call Resolutions
With conversation analytics, contact center agents can access valuable information and context about the customer to personalize their CX. While not always considered to be a workforce optimization tool, conversation analytics can go a long way to support contact center agents by reducing repeat calls and customer frustration.

Conversation analytics can also be shared with agents to help them improve their ability to effectively communicate with customers. By seeing specific data, agents can gain substantial insight into what they are doing right and where they can make improvements.

Identification of High Risk Customers
By reviewing the rich data collected from conversation analytics, you can identify key reasons for customer churn. Technology has improved to such as degree that it can now identify the most commonly spoken words prior to a customer making the shift to a competitor. With this information, it’s now possible to identify and reach out to a disgruntled customer who is likely to jump ship if they are not taken care of in a personalized, proactive way.

Proactive Cross-Selling and Upselling
Along with being able to identify customers who are less than pleased with the service they’ve received, conversation analytics can also help you pinpoint those who may be interested in learning about new products, services, or offerings. Outreach can be tailored to these customer based on the information derived from the analytics. For example, customers who have been identified as showing interest in joining a loyalty program based on a prior conversation with an agent can receive a proactive promotional email that describes the benefits and features of the program. When it is automated and timed correctly, proactive outreach based on conversation analytics can be a big revenue booster.

Identification of Business Trends
While there is the evaluation of conversations at the micro-level to provide more personalized, proactive service, the data collected and analyzed can also be used to identify trends that may be impacting the contact center and your company as a whole. With this broader, more macro perspective, trends can be identified, and decisions can be made on them.

The Challenge Is Integration
When it comes to conversation analytics, they cannot be evaluated in a vacuum. Today’s contact center is multi-channel with both assisted and self-service channels. Customers often move between channels, even during a single interaction, and having an understanding of every part of the customer journey is now essential to providing CX that meets today’s standards.

Thus, conversation analytics must be able to be pulled from all voice channels and then integrated with other forms of analytics to offer true value. These analytics also need to be accessible conveniently by agents who are on the frontlines with customers. Only then, can they be used in real-time to truly provide agents with a higher level of engagement.

What’s Next?
With customers more likely than ever to use self-service channels, they are increasingly using voice assisted-service only when they want to escalate an issue. This means that the volume of complex and challenging calls coming into the contact center is growing. Being able to understand what customers are saying and doing in previous calls and on others channels is now more important than ever.