Illustration of business man listening to four speaking customers
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The use of technologies like natural language processing (NLP) and artificial intelligence (AI) are giving Voice of the Customer (VoC) programs greater capabilities to derive deeper insights from customer experiences and the emotions they express. 


A February report by IT research firm Gartner revealed that by 2025, 60% of organizations with VoC programs plan to add voice and text analytics to traditional survey approaches.


Organizations recognize that speech and text analytics tools like NLP can offer insight with post-transaction analysis. However, these tools also provide real-time insight that can be used to impact CX.


As Deborah Alvord, senior director analyst with Gartner's global customer service and support research group, explained, there is speech analytics, which a lot of the call recording or interaction recording platforms offer, and text analytics.


“What these tools do is look through the speech and pull out key words, so if you wanted to know areas of effort of your customers, you can use the tool to data mine for repeat calls, second time calling or third transfer,” she explained. “These tools will look at the speech and the text and you, as the user, have to input what is it that I'm looking for out of these interactions.”


She said these types of analytics offer a wealth of brand perception and competitive information, going beyond just Voice of the Customer, and allowing organizations to understand underperforming agents.


“With NLP, the platform understands what the customers are saying, and it gives you that feedback, so you don't have to ask the customer repetitive questions,” she said. “You can also use data mining in all of your interactions to find out which of these interactions were repeat calls, which is an indicator of effort and negative sentiment.” 

 

Related Article: 4 Ways to Drive Better Voice of the Customer Feedback


Speech, Text Analytics Help Avoid Bias, Uncover Trends 

 

Daniel Ziv, Vice President of Speech and Text Analytics, Global Product Strategy for Verint, explained when unstructured analytics like speech and text are used, it is possible to avoid creating initial bias that comes with structured questions.


He said voice of the customer platforms can also identify not only what was said in an individual interaction but uncover trends across multiple VoC touchpoints. 


“Within minutes or sometimes hours, you can see an emerging issue that's bubbling up,” Ziv said. “Sometimes even before you'll see it appearing in social media, which is already so noisy. There are many important trends you may not see in social that are relevant for your customer base. You can glean those insights by mining voice analytics data.”


Verint's Vice President of Go To Market Strategy, Eric Head, added that voice analytics provides more emotional and sentiment context.


“There's a lot more fidelity, for example nuances like being able to tell when an agent is talking over a consumer, which can lead to more frustration,” he said. “There's simply a lot more detail in speech analytics.”


Head explained whether it's direct survey input or unstructured through text and speech analytics, all that data needs to come together in one place to be truly useful.


“You need to make sure everyone in the organization is on the same page relative to what the customer input is,” he said. “The data must be brought together and normalized, and also you need tools in place to extract the insights and distribute those insights to the key stakeholders in the organization.”


Voice of the Customer Analytics Turn Call Centers Into Intelligence Hubs 


Alvord explained that voice of the customer analytics help turn contact centers into intelligent hubs and make them more strategic.


“The data that you get is a wealth of information — gold nuggets, left and right for product teams, for marketing teams, for sales teams and for the web team,” Alvord said. “So many times, the customer service teams fight to demonstrate their value.”


She added that often customer service resources are seen as costly necessities because all businesses have customers with problems and questions.


“Too many times I see companies focusing on getting speech to text analytics and thinking it will solve all their problems, but you've got to have the human behind it to clarify what it is you're looking for and to make sense of that data,” Alvord said. 

 

Related Article: How Customer Data Platforms Can Benefit the Call Center


Voice Analytics Augment EDM, CDP Insights 


Head added that the complexity of consumers is greater than ever, compounded by the global pandemic, and the imperative is how organizations maintain or improve customer experiences.


“They are the ones looking for capabilities to better understand how they're performing in the eyes of the customer, where are the opportunities to take action, to improve and really being able to prioritize investment,” he said.  “These different automation technologies can support that.”


Ziv explained that the combination of voice and text analytics with enterprise data management lets organizations merge data, including survey information, and augment it with information from customer data platforms and other systems.


“The richest source of information you have is the conversations customers have with the organization,” he said. “Customer expectations continue to rise, but the resources are not growing, and you need to have a platform to get the data and act on it in a cost-effective way. To really take action, you need the unstructured data.”