Speech Analytics: A New Way to Know Your Customers

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Businesses know that one of the best ways to ensure success is to know exactly who their customers are, what drives them to make decisions, and how best to meet their needs. With this end in mind, many companies have adopted big data analytics, gathering as much data as possible and discovering detailed insights that can help them in multiple different ways. Understanding customers better is one way organizations are utilizing big data effectively, and part of the promise of using big data comes from the different sources they can collect from. We can see this from analysis of massive sets of sales data, clickstream data, and even text analytics. One new source that is getting a lot of attention is speech analytics. As can be seen from the name, this is where the actual speech of customers and clients is recorded and analyzed for information that can prove helpful to understanding them and satisfying their needs to create more business success, and companies are only getting started in this realm.

For now, speech analytics is most used in places where customer representatives interact directly with customers the most. Call centers in particular try to take advantage of speech analytics through the use of speech recognition software. Essentially, this requires analyzing what the customer says to get to know them better. Perhaps one conversation can only reveal so much, but over time, after enough conversations with many different customers, certain patterns can be established that could be applied across a wider array of customers. This helps businesses, because after all, once you know more about your customers, the better you’ll be at meeting and even exceeding their expectations.



It all comes down to figuring out what words have the most meaning in these conversations. Most companies have concentrated on picking out certain keywords they feel best pertain to what the company is trying to accomplish, but that may only be scratching the surface of the potential of speech analytics. One thing analytics experts are beginning to discover is that functional words may have just as much meaning if not more than contextual words. Functional words are typically those that help tie together the verbs, nouns, and adjectives found in statement. They’re things like pronouns and articles that are usually glossed over in favor of focusing on the perceived more important parts of a sentence. However, functional words could reveal more about customer intent and predict future behavior since customers usually don’t think too much about their choice of functional words. This would be a case of unfiltered language that indicates behaviors and intent, all incredibly valuable for companies. The next phase of speech analytics will likely look to incorporate this aspect of speech in order to draw a more complete customer profile.

Getting to the heart of what the customer needs, expects, and demands is what speech analytics is all about. And it’s important to note that this doesn’t just apply to interactions within a business’s call center. The speech analytics concepts is quickly expanding to include the rest of the organization. After all, the insights gained from speech analytics can be applied to things like marketing campaigns, sales, new product designs, and more. The trick is finding ways to analyze customer speech when it’s not over the phone. The answer to that conundrum comes in the form of wearable technology, where business representatives can record customer conversations through devices they happen to be wearing. Not only can these conversations be saved for future use, but the analysis can all be done in real time. It’s no stretch to think a sales representative could get an alert in the middle of a conversation with a customer to try a different tactic that would be more effective based on the language the customer is using. As all flash storage systems become commonplace, this level of analysis will be much easier to perform for all organizations.



Speech analytics represents the future of big data analytics. It takes what the customers say directly and distills it into information that helps a company get to know them better. With that data at their disposal, businesses can have confidence they’re helping their customers in ways they couldn’t before.

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