With the advent of multi-channel contact centers, businesses are able to engage in consistent and contextual interactions with their customers. However, analyzing these interactions to garner insights that will enhance profitability still presents a challenge for most businesses.

While first generation analytics focused on structured data analysis, newer solutions help in analyzing unstructured data, such as speech. More than 95% of call center transactions are unstructured and difficult to analyze. But speech analytics applications structure these interactions and aim to identify customer insights hidden within phone conversations. This supports a customer-centric approach, delivering products and services that are most suited for the customer at the right time and through the right channel. Customer-centric sales eventually lead to enhanced customer loyalty and improved business profitability.

Speech analytics works by searching unstructured audio data to identify patterns in meta-data. These patterns may be word choices, word tempo, callers’ emotions, or preference for competitors’ products, and are assessed on a near real-time basis to help agents improve performance metrics. Understanding callers’ emotions allows businesses to segment customers into different profiles based on their response to upsell and cross-sell efforts. This way, the business can sell more effectively, without upsetting the customers or sounding too ‘pushy’.

With more and more businesses recognizing the power of this technology, its use is skyrocketing. In fact, DMG Consulting reports that adoption of speech analytics in call centers grew by 26% from 2013 to 2014. For successful implementation, it is essential to have a planned approach, and a dedicated team of experts who are trained to interpret the software output into actionable steps for the enterprise and the call center. After all, what’s the point of analytics if you don’t act on them?

Speech analytics serves to improve sales and support by providing opportunities for emotion-driven contextual sales efforts. The insights obtained from speech analytics also aide in improving contact center operations in terms of instituting best practices and refining sales scripts. While speech analytics is a promising technological advancement, it is still in its infancy as far as commercial call center usage is concerned. That being said, commercial success stories do exist. Just ask Bluegreen VacationsTM and Green Mountain Coffee Roasters what it did for their profit margins and agent productivity.

Have you implemented speech analytics in your contact center?