Voice and Digital Transformation in 2021

What Is Natural Language Processing and Natural Language Understanding?

Natural Language Processing (NLP) is a form of artificial intelligence that enables computers to make sense of human language, process it for information, and use it to take action. NLP covers a wide range of capabilities including speech recognition, text categorization, and machine translation.

Natural Language Understanding (NLU) is a subform of NLP focused specifically on comprehending text and speech: getting the computer to analyze things like sentiment and extract meaning. NLU is essential to achieving NLP — in order to process the language and take action, the computer must first understand it.

If you’ve ever called a customer service center, the first message you probably heard was, “This call is being recorded for quality assurance, internal training, and compliance purposes.” Organizations leveraging Natural Language Processing are not only automating these functions and conversations, they’re using them to get better customer experience insights, lower operational costs, and scale their services company-wide.

The True Power of NLP: Way More Than a Virtual Assistant

When we think of Natural Language Processing being used in call centers, we typically think of chatbots or even a virtual assistant — an automated voice replacing a human one to handle our customer service needs. While a virtual agent tool can be a powerful resource, the reality is that many of NLP’s functions are designed to strengthen human capabilities, not replace them. Narayana highlights three areas in which NLP, NLU, and voice solutions are having a significant impact:

• Quality audits: Humans alone could never monitor all of the calls coming into a call center. By utilizing NLP to analyze unstructured data, quality assurance teams can perform audits 10 times faster, with call data automatically coded and organized for them so they can easily extract valuable insights.

• Real-time guidance: Rather than usurp the contact agent’s role, NLP can provide the representative real-time guidance while they’re on the phone with a customer to help them be more effective. One of the most exciting developments is speech analytics, in which the AI analyzes a conversation and provides actionable insights.

• Improved oversight: The agent isn’t the only one who benefits. As organizations use machine learning to leverage voice data sets, contact center supervisors can monitor more calls faster — enabling them to manage more agents and readily scale their operations.

The Rise of AI in Customer Service

While we often think of 2020 as a catalyst for digital transformation, Narayana reveals that there were actually three ‘transformation events’ throughout the year that changed the landscape. In addition to digital transformation, there was a massive cloud migration in 2020 as companies scrambled to move their data and their services onto the cloud to operate remotely. On top of that was an AI transformation, as businesses turned to artificial intelligence to solve some of the new problems they encountered while transitioning to offering services virtually 

Meanwhile, the demand for customer service skyrocketed. “Typically, there are two Black Friday events in a year,” Narayana explains, alluding to times when customer service engagement is at an all-time high. “In 2020, there were 120 of these events.” Such a need led to a rapid expansion of customer service teams. Instacart, for example, doubled its customer service team last April when demand grew by 300% in just one week.

This acceleration of AI innovation, combined with the sudden need for virtual customer service, has driven companies to adopt Natural Language Processing and other voice solutions to achieve digital transformation and deliver a better customer experience.

Using Voice Solutions to Manage from a Distance

In Narayana’s view, one of the biggest transitions in 2020 — the shift to remote work — is also one of the biggest opportunities for the customer service industry. “25% of an organization’s cost is their real estate,” says Narayana. “When they no longer have to pay that, they can use the money they’re saving on real estate to invest in new smart technologies.”

With agents working from home, contact center supervisors had to change the way they managed their teams. They needed a way to provide oversight from a distance. That’s where NLP and voice solutions have stepped in. Enterprises started leveraging solutions like 3CLogic and tools like Observe.AI to help their agents “self-learn” what they’re doing successfully and where they can improve their skill set.

Not only do these tools help supervisors manage from a distance, they also unify their workforce under one tool, give managers deeper insight and visibility into their agents’ calls, and, ultimately, help organizations scale much faster.

How Companies Are Mining Voice Data for Better Insights

Another way in which AI technology is helping contact centers improve is by enabling them to analyze their biggest data set: their customer service calls.

Ten years ago, analyzing voice data was complex and prohibitively expensive. Companies had to spend millions of dollars to understand what their customers were expressing on the phone. Today, that’s changed as AI tools for mining voice data have become increasingly sophisticated and accessible. 

Some companies, Narayana explains, still assume it’s too expensive. Instead, they try to understand customer sentiment by analyzing disparate data sources like their Twitter feed that only account for a sliver of their customer base. 

Leading companies, however, have jumped at this opportunity, investing in mining voice data from their customer interactions to inform their decisions. This trend is only growing. A recent Fortune Business Insights report projects the global speech and voice recognition market to reach $28 Billion by 2026.

The Role of Voice Solutions in 2021 & Beyond

As NLP, NLU, and voice solutions become more widely adopted, contact centers should be looking for opportunities to leverage these tools and be aware of what’s coming next. 

• Customer service engagement is on the rise. One of the biggest trends Narayana sees is that the volume of customer service interactions is growing significantly. This means contact centers will need to be ready to handle a higher volume of interactions. 

• Every channel is growing, including voice. As customer service demand grows, we’re seeing growth across every channel: chat, email, voice, and more. Organizations need an omnichannel solution for their customer service, with voice playing a central role.

• AI will enhance existing workflows via native integrations. Organizations are increasingly choosing to optimize their customer and employee workflows with contact center solutions that integrate natively with ServiceNow and other service management platforms, helping to improve performance at every step of the customer journey.

Unlock the Power of Natural Language Processing

As the volume of customer service engagements increases and Natural Language Processing grows even more intelligent and powerful, enterprises that adopt voice solutions with NLP and NLU will rise to the top. Visit 3CLogic to learn how you can leverage NLP and an array of voice self-service solutions.

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