Voice Data

Voice data is a form of unstructured data. It is often captured by call centers for both training and personnel supervision reasons.   One interesting characteristic of Big Data is that it often realizes high value on previously captured data.  Call center voice recordings is an example of this pattern.

Mattersight is a developer of personality-based call center applications (Bertolucci, 2015).  They developed a Big Data solution that utilizes the vast amount of voice data that is captured during customer calls to call centers.  The data is analyzed to determine personality characteristics of both the caller and the representative.  The idea is to match the caller to an appropriate representative to minimize the chances that the customer will become irate or the call will lead to an escalation.  Mattersight’s product is used by CVS Pharmacy and Esurance.  Wesbecher, Mattersight’s chief marketing officer, says there are a quarter of a billion calls every day between consumers and American brands.  

This is similar to an approach that Southwest Airlines is taking with their call center data (Erevelles, Fukawa, & Swayne, 2016).  Southwest utilizes a speech analytics tool to examine conversations between customers and representatives to gain insights into customer behavior and to improve customer service.  Southwest utilizes this data to identify unrecognized consumer needs.  They utilize Aspect, a competitor of Mattersight, to calculate real-time key performance index (KPI) dashboards (van Rijmenam, 2017).  These metrics guide representatives towards better customer service.

Most large organizations support their customers with a call center.  It is an opportunity to apply Big Data techniques to gain new insights.  Once the recordings are converted to text, additional forms of analytics can be performed.  We are seeing an emerging trend towards considering the psychological makeup of both the caller and the customer service representative.  It is not so difficult to imagine a display guiding future customer service representatives through a call in real time, warning when they are saying something that might upset the customer or lead to an undesirable outcome.  Eventually, we may remove the humans from this conversation and have one autonomous intelligent agent communicating with another, until then, “please hold for the next available agent.”

References

Bertolucci, J. (2015). Big Data: Matching Personalities In The Call Center. InformationWeek.

Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897-904.

van Rijmenam, M. (2017). Southwest Airlines uses Big Data to deliver excellent customer service.   Retrieved from https://datafloq.com/read/southwest-airlines-uses-big-data-deliver-excellent/371