Have you ever been frustrated trying to call into a company’s customer service line or contact center?

Dealing with customer service can be an emotional experience, too often leaving consumers exasperated. But help is on the way with new and innovative predictive analytics solutions. For example, new emotion analytics technology—combined with best practices on when human intervention can help—is reducing customer frustration in the contact center and beyond.

Simply put, emotion analytics collects data on how a person communicates, verbally and nonverbally, to understand a person’s mood or attitude. Companies, and front-line employees, in particular, can take action based on this valuable insight to engage customers at precisely the right time to improve their overall experience. With an improved understanding of how a customer may be “feeling” during a given interaction, frustrated, impatient, concerned, to name a few, customer-facing employees are better positioned and prepared to step in and help.

A recent article in CMO offered up some exciting examples of how emotion analytics is already in use at some of the world’s leading brands. This includes facial recognition, social listening, audio analytics, and biometrics scanning. Below we take a quick at some of the highlights:

  1. Facial Recognition: Air carrier British Airways is using facial recognition technology, which scans faces by camera, to help speed up the boarding process and even eliminate the need to check passports for passengers boarding planes from the U.S. In another case, the British Broadcasting Corporation (BBC) is using facial recognition technology during test screenings to determine a show’s potential popularity. Specifically, the predictive analytics technology analyzes “social sentiment and activity to predict global demand for [BBC] content in a certain geographic market around the world.” Disney is also using facial recognition technology to test its content before release.
  2. Voice Analysis: According to the CMO article, U.S.-based health insurance company Humana is using voice and sentiment analysis in its call centers to improve the customer experience. The solution not only helps identify the current emotional state of the customer, but it also offers up suggested responses and next best actions for call center agents to help “fix” the situation using predictive analytics.   
  3. Biometrics: In Japan, insurer Sompo has teamed with Accenture, Intel and local taxi company Daiichi Kotsu Sangyo to improve automobile safety. The companies are collecting intelligence at the edge from Internet-of-Things (IoT) devices, such as smart watches, using biometrics to detect factors like heart rate. The information collected, in addition to traffic images and “journey” data, is then used to provide drivers with personalized driving instructions in real time, helping to improve driver safety and bringing down the number of traffic accidents. In addition, National Bank Australia (NAB) is using biometric technology for customer identification and authentication.

To learn more on emotion and predictive analytics, including other examples from companies like USA Today and Tesco, you can read the complete CMO article here.