Speech or Text – That Is the Question
Posted in Customer Engagement
Speech analytics and text analytics are extremely valuable tools in the battle for that precious data contained in recorded conversations with customers and in the text-based channels where they regularly communicate.
Text and speech analytics enable you to understand the drivers of issues critical to your business, surface issues you didn’t even know existed, and examine customer comments and feedback across a broad range of channels, including phone, social media, surveys, email, chat and more.
While there are a lot of similarities between speech analytics and text analytics, they were built specifically for different tasks. You wouldn’t use a hammer to tighten a screw, or a screwdriver to hammer a nail, right? The same is true for speech and text analytics tools. You don’t want to use speech analytics when you really need text analytics—or vice versa. You’ll get far superior results if you use the right tool for the job.
Speech analytics is used specifically for analyzing recorded customer conversations. The sheer volume of phone calls to your organization can quickly exceed your ability to review and analyze them. Speech analytics helps you glean valuable intelligence from thousands, or even millions of customer calls, so you can take action quickly.
Text analytics was built specifically for analyzing text-based data—in emails, contact center notes, verbatim survey responses, live chat sessions, tweets, blogs and forums, just to name a few. Text analytics is the process of analyzing the unstructured text in these text-based channels, extracting relevant information, and transforming it into structured actionable information that can be leveraged to help improve business outcomes.
Since text data is very different from phone-based interaction, speech analytics shouldn’t be used on text-based data or vice versa. The analysis and extraction processes used in text analytics take advantage of techniques that come from computational linguistics, statistics and other computer science disciplines. The information uncovered through text analytics can be combined with structured data and analyzed using various business intelligence or predictive and automated discovery techniques. In addition, the information can be analyzed to determine relationships and trends, to look for clusters, and to uncover other pertinent information.
By leveraging this essential information, your organization can help improve its processes and products—while responding more effectively to customer and market demands.
Trying to use one tool to do the job of the other is like using a screwdriver to hammer a nail—it’s not going to get the job done! Choose the right tool for your business needs, and you’ll begin to achieve the superior results you need to succeed.
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