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eBay Uses Voice Analytics to Increase Client Sales

Sep 26, 2013

By William Atkinson

An eBay company, EBay Enterprise provides omnichannel commerce solutions for a variety of brands and retailers, including phone, e-mail, chat and social support for these clients’ customers, who often need help placing orders, checking order status and making returns. As such, eBay Enterprise considers its key product to be “the customer experience.” Each client’s brand has a distinct experience and emotion that must be cultivated and reinforced through interaction with eBay Enterprise customer care agents.

In the past, eBay Enterprise measured quality via random evaluations of its customer service representatives, monitoring calls to ensure their adherence to an array of standards.

One of the most important metrics in the quality-control process involves first contact resolution (FCR). If customer service representatives can resolve consumer issues during the first contact, it eliminates the need for follow-up contacts. In addition, eBay Enterprise realized that if it could gain additional information about customer insights during FCR customer interactions, this could help its clients increase sales loyalty.

As a result, eBay Enterprise began searching for ways to gain more insight into customer experiences via voice analytics technology. “We looked at several vendors,” says Robin Gomez, director of operational excellence, omnichannel operations, eBay Enterprise. The company selected Interaction Analytics from NICE Systems, which provides a way to unlock these valuable customer insights. “We already had NICE call recording in place, so they were the incumbent, but more than that was the feature set and functionality that we saw with their tool versus the other vendors,” says Gomez. Stereo recording with clear speaker separation and the volume of calls it could analyze every day were other key factors in eBay Enterprise’s decision.

Interaction Analytics uses speech recognition and content analysis software to convert 20 million calls a year into mineable business intelligence. In addition to the content of voice, chat, e-mail, Web and social interactions, Interaction Analytics looks at call patterns, as well as desktop activity, to understand the drivers of efficiency, customer satisfaction and revenue generation.

With this new information, eBay Enterprise has developed a consumer insight department, which focuses on identifying the issues that can best promote increased sales for the company’s clients.

In addition, Interaction Analytics enables eBay Enterprise to measure customer sentiment through automatic categorization and trending of dissatisfied callers and escalations. The analysis of these types of calls provides insights into customer perspectives, which is combined with post-call surveys and directly incorporated into improvement plans.

The most significant benefit of Interaction Analytics is being able to quickly and effectively identify specific call types in volume, length, relationship to other call types and more, says Gomez. “The sheer volume of interactions that can be analyzed with the proper configuration is truly a key enabler of process improvement and business intelligence,” he says.

As a result of Interaction Analytics, eBay Enterprise has experienced some significant business benefits, including a nine percent improvement in customer satisfaction, an 18 percent improvement in first contact resolution, and a 19 percent increase in average order value during the past 24 months.

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