CallFinder Blog Voice Analytics vs. Speech Analytics: Key Differences

Voice Analytics vs. Speech Analytics: Key Differences

July 23, 2018 by Morgan Pulitzer - Last Updated: June 22, 2020

voice analytics software on a desktop

Your business has access to more customer data than ever before, particularly in your contact centers. The key is knowing the best way to extract and utilize that data. Two solutions that are often used are speech analytics and voice analytics. While both solutions analyze phone conversations to gain customer and business insights, their methods are quite different. Understanding these differences is imperative to choosing the call analytics solution that’s the best fit for your business.

Speech Analytics

A speech analytics solution focuses on the actual spoken content of a conversation. A speech analytics engine analyzes the content and context of agent-customer interactions. This is accomplished with phonetic indexing or converting speech into text to organize the content. Speech analytics technology makes it possible to search for and locate specific keywords in customer interactions. This makes it easy to get a glimpse of how the agent handled calls related to certain topics and to uncover the context of the conversation.

For example, a customer may call a business to ask whether an order has shipped and when it’s expected to arrive. A quick search for the words “order” and “shipped” will locate all calls containing those keywords. Call center managers can then dig into each call to determine whether or not the customer received the needed information.

Speech analytics solutions locate keywords and syllables based on a framework series of searches, which is most often set up by the business itself. By revealing the most common words and phrases customers say during a conversation, businesses can get better insights into trends. The business can use that to make more informed decisions, improve agent performance, and ultimately give customers the best experience possible.

Voice Analytics

If speech analytics focuses on the content within agent-customer conversations, voice analytics focuses on how it was said. Voice analytics works by analyzing the audio patterns for certain features, such as tone, pitch, stress, tempo, and rhythm, to derive emotional content. This provides a more accurate reflection of a customer’s mood.

For instance, a customer may use the word “great,” which normally denotes a positive sentiment. However, a voice analytics solution can detect cues, such as sarcasm or anger, which can completely change the meaning of the word. Understanding the emotions behind what customers say is a crucial factor in providing an excellent experience.

Which Solution is Right for Your Business?

Now that you know the difference between speech analytics and voice analytics technology, how do you know which would be more beneficial to your contact center and business. Here are a few important aspects to consider when deciding between the two solutions:

  • While understanding a caller’s true temperament is vital, simply analyzing tone of voice may not always be the most accurate indicator. After all, someone may sound tired or exasperated for reasons that have absolutely nothing to do with their interactions with the contact center agent. Businesses may spend X amount of time and money to solve a problem that didn’t exist in the first place.
  • Specific keywords and phrases are shown to be strong indicators of a potential sales opportunity, whether direct, cross, or up, as well as what may cost money, such as a potential cancellation. When those words are said, they provide solid evidence of these occasions, as opposed to the more abstract aspects of vocal tones and emotions.
  • Script compliance is essential to many businesses, particularly in more regulated industries. In this case, what is said is far more important than how it was said. Speech analytics ensure that all of a contact center’s agents are 100% compliant in order to avoid serious consequences, such as heavy fines and lawsuits.
  • It’s one thing to know that a customer is upset, but it’s entirely another to know how to actually fix the problem. Keyword detection predicts customer wants and needs with more accuracy than voice analytics, delivering the tools needed to build a more effective solution that will keep customers happy.

Speech analytics and voice analytics are easily confused. Even businesses that use one or the other tend to conflate the two. Now that you know what distinguishes one from the other, you are better equipped to choose the solution that will help take your contact center data to new heights!

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