Are You Leveraging the Voice of the Customer Holistically—Across All Touch Points?

As we’ve mentioned in previous articles about UC Analytics, analytics is a powerful complement to a UC solution, effectively tying in with CEBP and business processes, that better enables and empowers companies to take action on all types of customer and operational information gathered. As Jim Burton noted in his podcast with Steve Williams, Vice President of Sales for Desktop and Process Analytics, Verint Systems, “Those of us who have been following Unified Communications for a long time have realized the important role that analytics play in Unified Communications. It's one of the important values that you get when you can look at information and figure out how to make critical decisions in the Unified Communications environment.”

Recently, Verint added to its UC Analytics offerings with the introduction of “Customer Interaction Analytics,” which speaks to the combination of speech, text, and data analytics and customer feedback surveys. While Verint has been aggressive in developing and rolling out these capabilities, it won’t be the only vendor providing these capabilities, and we expect others to follow shortly. As an element of UC Analytics, Customer Interaction Analytics helps organizations identify and address sales, service, and operational issues based on analysis and intelligence derived from all customer touch points (voice, email, blogs, social media, etc.) across the enterprise. This is ever more important in today’s digital age, where enterprises need to consider all types of customer interactions and embrace the varying customer-preferred communication modes and methods to get an accurate representation of the voice of the customer and the business intelligence needed to drive process improvement.

Most of our discussions about UC Analytics to date have been around speech analytics, but there are numerous other elements of a UC Analytics solution. One such element is desktop and process analytics, which Steve Williams covered in the recent podcast. Another element, one that is gaining more and more traction by businesses looking to holistically understand the customer experience and related processes, is text analytics. For example, Verint’s Impact 360 Text Analytics lets users mine customer interactions and feedback across virtually all text-based customer communications channels, including email, web chat sessions, blogs, review sites, and social media. Moreover, since these interactions are often cross-functionally relevant, the outcomes can be routinely shared to improve and shape both inner and interdepartmental processes throughout the enterprise—from the contact center to marketing to the back office.

Going a step further, by combining text analytics with speech analytics (which mines the content of voice interactions), data analytics (which mines the context of voice interactions), and customer feedback (which provides both quantitative and qualitative customer insight), enterprises can listen to and understand the voice of the customer in its entirety. This provides not only a means to uncover communication bottlenecks and process issues today, but proactively addresses developing problems and negative customer sentiment. 

Customer Interaction Analytics

There’s been an explosion of different types of channels by which customers can interact with an organization and with each other. While this isn’t new per se, what is new is the role of the customer’s voice and the influence it can have in the world of Twitter, Facebook, YouTube, blogs, etc. Customers today have much wider spheres of influence, and one nasty tweet or YouTube video can easily go viral and ultimately harm a company’s reputation and brand equity.

One of the key pain points companies have been experiencing is how to get an early warning signal when there is an issue, and how to stay ahead of things before the issue “goes viral” and becomes a major problem. One way to overcome this challenge is by deploying analytics to mine data collected from social networks, call centers, and other interaction sources in order to identify and address potential issues before they grow larger. The information collected and analyzed can be used throughout the organization to help make more informed decisions about everything from marketing messaging, product design and development, and back-office applications such as billing and collections to business processes to mitigate potential problems.

The plethora of interaction types, whether email, blogs, phone calls, customer surveys, or tweets, create and generate a wealth of information about the customer. Some of this data is structured, such as customer surveys and contact center quality scores, while some is unstructured, such as email, chats, blogs, social media, review sites, etc. While it’s difficult to mine the unstructured data, it more often than not is the richest source of information and the portent to the root cause of business issues. With “Customer Interaction Analytics,” Verint has introduced an integrated way to capture and analyze the myriad of interactions to provide meaningful insights to enterprises. As mentioned, Verint is staking out an early leadership position in the market, others will follow with their own offerings and methodologies.

The first step in Verint’s methodology is to link interactions across channels, providing an aggregated, unified perspective of how customers speak to and about your business. Verint does this through its Customer Data Joiner capability, which, regardless of channel, creates unique customer interaction summaries about each customer. The Customer Data Joiner analyzes text-based multimedia such as email, chat, and Web sources (e.g. blogs and review sites) to discover the people talking about your company and products, consolidating common interactions by customer to provide insights into the various interactions and the nature of the interactions. The result is a customer interaction summary that assesses the complete customer experience at the individual level based on comprehensive roll-up reports and dashboards. With this, companies can do a deep-dive analysis across channels from a unified data set.

The next step is to establish an early warning system. With Verint’s Customer Behavior Indicator capability, organizations can stay ahead of the buzz by leveraging internal and external sources for unbiased customer behavior. Customer Behavior Indicator helps organizations more effectively mine interactions from different channels and surface terms and phrases that may be indicative of specific trends. For example, a company introducing a new fee for its financial services offering receives a number of calls into its contact center related to the topic. However, the spike is not significant enough to draw any conclusion regarding an existing or pending issue. At the same time, emails and online activity such as blogs referencing the new fee also rise. This too does not bubble up an issue since the increase in activity across the mediums is not correlated. With Verint’s Customer Interaction Analytics’ Customer Behavior Indicator and Customer Data Joiner capabilities, the spike in calls and text-based indicators can not only be easily identified, but correlated so the company can visibly detect and address the trend before it significantly impacts customer loyalty and retention. 

Next, understanding the voice of the customer must take into account customer sentiment, emotions, and behavior drivers. This helps analysts more effectively categorize interactions, detect root causes, and track customer sentiment. This step involves categorizing interactions and then performing root cause analysis and sentiment scoring. By looking at the various interactions about a specific trending topic, companies can get a sense for what the interactions were about and use Verint’s Customer Interaction Analytics’ “Tell Me Why” functionality to automatically drill down to root causes. This is extremely useful when you’re conducting a business process study and want to use customer interactions as a data source. Companies can use the findings from the analysis of customer interactions across touch points to understand and further analyze where a billing process breaks down. It can be used for product development improvement to understand exactly what people are saying about the product, for example, on the Web. Customer sentiment can be scored on various categories, with companies able to see where they’re scoring better or worse and, most important, why.

The last step is to take action with the information gathered. Traditional workforce optimization technologies that tightly integrate customer interaction analytics like Verint’s Impact 360 suite, among others, can be used to provide a workflow for delivering interaction data and analysis to decision makers. This can be done via a number of means, such as reporting, alerting, dashboards, and scorecards, giving the tools and intelligence to the people who can take action to affect change.

Unified communications is about integrating multiple channels of communications, and using these channels to optimize business processes. UC has focused primarily on integrating the channels of communications workers use to interact with customers, partners, suppliers, etc. However, it’s also important that we look at how customers use these various channels to interact with companies, and how companies can analyze these voice, text, and data communications to optimize business processes.

Customer Interaction Analytics lets companies better understand customer behavior and where trends are emerging that require your attention before they escalate and hurt, rather than help, your UC strategies and goals. This is a new concept and may be difficult for some enterprises to grasp. Companies like Verint will need to work with enterprises and do some evangelyzing to help them understand the value of Customer Interaction Analytics and Unified Communication Analytics. The enterprises that “get it” and start implementing these tools will have a head start against their competitors, and would be wise to start investigating these tools now.

This paper is sponsored by Verint.