Customer Service Call Centers Improved with Big Data

The customer service call is often a less than satisfying experience. First there’s navigating through the inflexible voice mail tree. This is followed by impatient waiting on hold until a call service representative answers. The customer, who is stressed by the problem that has prompted his call as well as the voice mail routing and waiting, finds that the service rep doesn’t fully understand either his problem or his reason for calling. As a result, the frustrated customer avoids future use of the company’s services and products. After several months, the customer service representative finds the job too exhausting and leaves, which contributes to the call center’s high turnover problem.

For some companies, this all too common scenario plays out better for both the customer and the service representative. Thanks to the marriage of psychology, behavioral science, and big data, customers are being matched with service representatives on the basis of their personality types and communication styles.

This streamlines the amount of back and forth interaction needed to resolve customer issues because the representative understands both the customer’s words as well as “where he is coming from” at an intuitive level. Likewise, the customer finds that the service rep quickly understands and responds in a way that’s both useful and easy to understand. After hanging up, the customer feels better off because of the experience.

Companies such as CVS Health, Progressive, Esurance, Hilton Hotels, and Wells Fargo perform this technological wizardry by using the SaaS-based behavioral analytics software of Mattersight. The software analyzes the tone, tempo, and word usage of customers’ speech patterns and then assesses their communication style. This style is a kind of personality fingerprint that allows the matching of compatible customer and service rep personalities within seconds.

The software also notes which personality types each rep has had the best success with and makes adjustments. The software also fine tunes its assessments of customers over time and across the different companies the customers patronize.

Mattersight’s software has analyzed one billion phone calls and uses 10 million behavioral algorithms and language libraries to make its assessments. It not only assesses personality type but can assess the emotions displayed by both the customer and the service rep on all the calls that it monitors. It identifies emotions in all of its various shades such as anger, sarcasm, anxiety, impatience, and the empathy level of the service rep. It can also determine whether the exchange was strained or went smoothly.

Big data it seems, has mastered a key component of empathy, which is the recognition of emotions of human beings.

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