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Big Data in the Contact Center

Speech analytics is just the beginning.
By Nancy Jamison - Posted Apr 30, 2014
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Everyone is talking about big data in the contact center, which is ostensibly used to glean customer intelligence and improve the customer experience.

Frost & Sullivan defines big data as a volume of data so large and moving at such high velocity that it is difficult or impossible to work with using traditional database management tools. Big data represents the collective and exponential growth of structured and unstructured data, from every imaginable digital source, including data logs, pictures, audio, and video. The size and scope of the data generated each day has surpassed the capabilities of traditional enterprise systems to capture and process it.

Sources include social networks; corporate documents; sensors such as Radio Frequency Identification tags on physical assets, motion detectors for use on toll bridges or turnstiles, GPS on smartphones, or location-based technologies; instrumented machinery; population census data; Web interactions; video, such as surveillance footage or in-store cameras; and psychographic or demographic data.

Speech and Text Analytics

Ironically, the contact center itself was the source of one of the earliest and richest of these data sets, recorded contact center calls. More recently, chat and social media interactions have added sources to the mix. Using speech analytics, solution providers such as CallMiner, Genesys, Nexidia, NICE Systems, Uptivity, and Verint have been mining this data to gain critical business insights. Avaya's Ava and [24/7]'s Assist chat products are two tools that handle chat interactions and produce additional levels of customer interaction data. And social media interactions, while not of the same depth as agent conversations, are also being analyzed, using text analytics to uncover trends, opportunities, and competitive threats, so that real-time interactions can be viewed with new criteria.

Customer Interaction Analytics and the Inclusion of Big Data

But this is just one piece of a very large puzzle. Contextually relevant information along the entire customer journey, which might just as easily have started at a brick-and-mortar branch as on the Web, is often siloed, and this information is left out of chat or agent calls. However, solution providers are now combining customer interaction tools with speech, text, and big data analytics, including CRM and billing systems, Web logs, chat logs, and IVR transactions, to uncover greater patterns, trends, and issues, and then take action on them.

While speech and text interactions are rich sources of big data, layering on other sources can add tremendous business intelligence. NICE Systems and [24/7] are two companies combining data in a centralized place to analyze and act upon. For example, NICE Customer Engagement Analytics performs real-time cross-channel analytics, cross-channel interaction management, and real-time decisioning and guidance to improve employee performance, affect the customer journey, and optimize processes across the enterprise. By blending in a multitude of data sources, it allows companies to do several things:

  • determine the potential value a customer might have, given demographic factors;
  • identify customers with a low probability of purchasing goods or services, using predictive analytics;
  • identify likely brand ambassadors;
  • identify churn factors, based on social media mining or call recordings;
  • estimate the lifetime value of a customer, based on similar customer profiles; and
  • change offers in real time and help agents pick the next best actions for customers.

Final Word

The contact center industry ushered in an era of multichannel interaction more than a decade ago, and it's only gotten more complex. New channels of interaction have given consumers more power, control, and knowledge. Research has shown that customers turn first to the Web and their peers to get information and self-serve before they call into the contact center, changing the balance of power between the agent and customer. As such, the ability to pull in, combine, and use customer interaction analytics along with big data resources is the future in providing the elevated level of customer experience new generations of consumers demand.


Nancy Jamison is a principal analyst for contact centers at Frost & Sullivan. She can be reached at nancy.jamison@frost.com, or follow her on Twitter @NancyJami.


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