Unlocking Customer Sentiment Through Speech Analytics

by   |   November 22, 2016 5:30 am   |   0 Comments

Matt Matsui, Senior Vice President of Products, Markets, & Organizational Strategy at Calabrio

Matt Matsui, Senior Vice President of Products, Markets, & Organizational Strategy at Calabrio

Brands have conversations with customers every single day, but many are missing out on critical information that is hidden within these conversations. A customer may say, “I’m looking forward to us coming to a resolution.” A short time later, that same customer might add, “I would like you to do something about this.” Today, various organizations are using speech analytics to understand customer sentiment in conversations just like these. However, what many brands don’t realize is that there are critical elements within a customer conversation that can help companies predict how a customer will behave. Every single word in a conversation with a customer holds meaning, but some words mean more than others and those are the words that companies must analyze to better understand sentiment and predict customer behavior. Speech analytics can help brands do both, but to uncover a customer’s true sentiment, a company must understand contextual versus functional words.

Contextual Versus Functional Words

Contextual, or content, words are defined by conscious intention. They are the nouns, verbs, adjectives, and (sometimes) adverbs that people use when formulating a sentence. Contextual words usually refer to things like the products customers want, or they are descriptions of moods, customer sentiment, or tendencies. Functional words serve to establish relationships with the words around them and are used to make a sentence grammatically correct, but they are typically regarded as having little to no meaning of their own. Even if the functional words are removed, a listener or reader can generally understand the basic meaning behind the now-fragmented sentence, which is why they are often referred to as “throwaway words.” Allegedly, the only purpose of a functional word is to make a sentence flow. However, that is absolutely not the case. According to The Secret Life of Pronouns: What Our Words Say About Us by James W. Pennebaker, pronouns and prepositions often reveal the most about underlying sentiment. If brands want to know what their customers are really thinking, functional words will give them more insight into actual customer sentiment than contextual words.

The Importance of Functional Words

When customers are speaking with a brand, they are actively choosing which nouns, verbs, and adjectives to use in a sentence, but the same isn’t true for the functional words. The functional words are a byproduct of subconscious thoughts — ones that customers don’t even realize they’re having — and it’s the subconscious that provides brands with a clear view of what customers are actually thinking. For example, a customer may start the conversation using the word “we,” which signals inclusion. As the dialogue progresses, “we” may change to “you,” which indicates that the customer is distancing him/herself from the brand. That is a huge red flag, and may indicate that a customer is thinking about taking his/her business elsewhere. Understanding the use of these functional words will allow brands to course correct, which can potentially mend the relationship before it becomes a customer churn statistic. If organizations want to use speech analytics effectively, they’ll need to continue capturing customer conversations, but adjust and analyze them with the contextual versus functional lens.

What’s Next for Speech Analytics

Brands are already using speech analytics in a number of ways, including identifying keywords that correspond with campaigns to gauge customer sentiment around particular advertisements or events. However, as technology advances and more emphasis is placed on the customer experience, the importance of speech analytics will grow. With that, companies will need to deepen their knowledge of both written and verbal language in order to accommodate spoken language and speech-to-text conversations. In addition, understanding a customer’s actual feelings may involve leveraging the expertise of linguists. Contextual and functional words are just the beginning, and there is so much more customer sentiment buried deep within word usage and sentence structure. In addition, as more data is collected, brands will be able to apply that language expertise to larger data sets, and subsequently develop increasingly accurate predictive models. The sooner brands can predict customer behavior accurately, the sooner they can take action to cultivate loyal, long-term customer relationships. Eventually, companies may even be able to predict long-term customer behavior by gleaning insights from conversations during the sales process.

The possibilities with speech analytics are endless, and companies are currently only scratching the surface of how this technology can be used to enhance the customer experience and reduce churn. As more brands turn to speech analytics to understand and analyze what their customers are saying, it’s important to remember that every piece of a conversation is critical. By placing emphasis on the functional words, companies will better understand customer sentiment so they can, in turn, more accurately predict customer behavior. This will allow them to adjust strategies and reengage unsatisfied customers — all of which rolls up to a better customer experience. All of this is possible by simply understanding the fact that the so-called “throwaway words” are rich in meaning and by implementing the right strategies to unlock customer sentiment that lies in the functional words.


Matt Matsui, Senior Vice President of Products, Markets, & Organizational Strategy at Calabrio, oversees company-wide go-to-market efforts. Matt joined Calabrio with more than 25 years of experience leading product and marketing organizations for a broad range of companies, including ACNielsen, Cognos, Fair Isaac and numerous early stage analytics firms.

Through this experience, Matt has developed a keen sense for growing markets with a heavy emphasis on big data and business analytics. Prior to joining the Calabrio team, Matt was a managing partner for Veralytics, a predictive sales and marketing analytics and product insights company. Matt’s proficiency is bringing to market scalable and flexible analytics solutions that integrate communication streams, giving business the ability to launch powerful intelligence strategies in a simple way.

He holds undergraduate degrees from the University of Maryland and a master’s degree from Northwestern University.


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