Voice-Based Data Can Be a Strategic Asset if Used Properly

Contact centers are key to any business intelligence strategy, yet they've traditionally been treated as a cost center rather than a valuable business asset. In today's knowledge-driven business environment, it's understandable that marketing might find it easier to rely on customer feedback from social media than call center conversations. However, these call center conversations capture critical business insight by providing access to the true voice of the customer, something that should be part of any business intelligence strategy.

While email has traditionally played an important role in communication with customers, text conversations through Facebook, Twitter, LinkedIn, and website chatbots are becoming increasingly pervasive. Thanks to text-based analytics, you can easily monitor and review these two-way conversations to learn more about customers. While they are important data sources, they only provide a small part of the customer puzzle.

Data from contact centers significantly sharpen the picture. Think of the thousands or tens of thousands of hours that your customer support team spends on the phone with customers every day. If you could hear what the customers said, you would know which products and services were of interest to them and how these can be improved, what they think about your pricing policies, what they are hearing from competitors, and more.

Most companies, however, don't realize the value of all their call center data. Incredibly, less than half of 1 percent of all recorded contact center calls on average are heard and analyzed. Why is this business insight left on the table? Unfortunately, it has just been too hard and too costly to get it.

But this has changed. Now, automated speech-to-text (STT) technology is available to transcribe data from customer interactions accurately and cost-effectively. In addition to capturing the content of what is being discussed, this technology can glean more information from the call, such as determining a speaker's gender, assessing vocal characteristics to understand a customer's emotion, and evaluating words and phrases to understand a customer's sentiment.

Optimizing Call Center Operations

In addition to using the data to evaluate and optimize the customer experience, you can use it to improve call center and agent operations. It can help you identify and address inefficient processes, boost employee performance across multiple lines of business, and ensure compliance with regulations. The insight from the data can support your overall workforce management strategy, ensuring your contact center is properly staffed with the right number of agents and that these agents have the right blend of skills needed to handle a variety of customers and their concerns, while supporting your company's business goals.

At the end of every call, most agents type notes into a CRM system, summarizing their conversations for future reference, which can be a time-consuming and expensive process. The usefulness of each of these summaries depends on the agent's memory and perception, and unfortunately, often they don't document customer sentiment and emotion. But, by automating the process, companies can easily capture all of this information in a consistent manner.

Leading companies have unlocked a gold mine of data through automation and are using it in innovative ways. Some are transcribing several years of archived call recordings retained for compliance purposes and analyzing the data to understand churn and uncover trends. Forward-thinking contact centers are using predictive analytics, which combine statistical techniques and machine learning, to anticipate how customer behaviors could affect their businesses.

With the proliferation of smartphones and the growing use of web searches, the majority of customer interactions occur during a multichannel, multi-event journey. Companies can get a 360-degree view of these interactions by mining their data from call center transcripts, texts, emails, chatbots, support channels, and social media posts and using voice- and text-based analytics to understand their customers' needs and interests and what led to their actions. Companies then can use that insight to improve their customer experience and CRM initiatives.

Multichannel data collection can help alleviate some of the difficulties customers have in navigating support. For example, to reduce the expense of staffing customer support lines, companies typically rely on call deflection methods, using gated support pages on websites and chatbots to resolve as many problems as possible before they are escalated to calls with live agents. This can be a very frustrating experience for customers. Imagine how annoyed a customer might feel if he spends 10 minutes trying to find an answer to a question on a support page or through a chatbot with no success.

Now, problem escalation no longer needs to be gated. When text data is connected with analytics in a CRM, an agent can be alerted to search history events and contact a customer proactively via a pop-up window. In the example where a customer is trying to search for information on the website, an agent might send a friendly message such as, "Hi, Pat, I see you were looking for cloud-based storage solutions. Would you like me to help you estimate your usage needs?"

By proactively taking ownership of the conversation, the agent can defuse a potentially stressful interaction before the customer becomes frustrated and before it gets escalated to a call. The agent can do this by showing readiness to help, an understanding of the customer's needs, and compassion for her frustration.

Multichannel Data and the Mind of the Customer

The future points to increased integration between different types of data. According to H. John Oechsle, president and CEO of Swiftpage, voice-activated CRMs and analytics will soon enable system users to interact with email, set up activities, and advise contact center agents on which customers to handle next based on the compatibility of agent and customer personality profiles. Also, agents will be able to rely on spoken commands to complete tasks, similar to apps like Apple's Siri, Microsoft's Cortana, and Amazon's Alexa. All of this will make the lives of agents easier and multichannel integration more attractive.

To be most effective, company CRM strategies should be holistic, gleaning data across all of their channels and systems to better understand the minds of their customers, proactively address their needs, and connect with them where and how they want to be reached. Thanks to advanced technology, all of this is now possible. Companies can easily get access to all of their customer data, analyze it, and apply insights to optimize sales and support efforts. This provides invaluable business intelligence and a competitive advantage, keeping customers happy and loyal, while furthering business objectives.

Wayne Ramprashad is chief product officer at Voci Technologies.

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