Avaya: Applying Big Data to Customer Engagement
Avaya: Applying Big Data to Customer Engagement
Dr. Brent Kelly is a Vice President and Principal Analyst at Constellation Research and President of KelCor, Inc. He focuses on the unique intersection of unified communications, social business, cloud services, video and mobility. Dr. Kelly provides strategy and counsel to key clients including Chief Information Officers, Chief Technology Officers, investment analysts, venture capitalists, technology policy executives, sell-side firms and technology buyers. Prior to joining Constellation, Dr. Kelly served for 10 years as a partner at Wainhouse Research where he was the primary author of most of the firm’s unified communications reports and forecasts. Dr. Kelly is a regular presenter at Enterprise Connect (formerly VoiceCon), the communications industry trade show where his well…...
Read moreAt the Avaya Evolutions event in Dallas (February 5/6, 2013) I had the opportunity to speak with Brett Shockley, Senior Vice President and General Manager, Avaya Applications and Emerging Technologies. The discussion focused around new technology Avaya is working on that will significantly impact and enhance contact center customer engagement: speech analytics and big data analytics. Both of these capabilities overlay two Avaya’s contact center products, Elite and the newer Avaya Aura Contact Center.
The big data offering is based on grid computing in which hundreds or thousands of customer characteristics are kept resident in memory during a customer engagement session. In milliseconds, decisions about how to route a call are made based on the customer’s data. This data can include income level, product preferences, whether purchases are more likely to be made on a specific day of the week, where the customer lives, family size, etc. Decisions are made and then fed into the ACD which will route calls to contact center agents who are more successful at meeting the organization’s objectives with respect to that customer. In addition, the system can keep track of millions or billions of “events” that occur in the process of a customer engagement session, thus enabling additional analytics on huge amounts of data that otherwise would be discarded.
A second capability is speech analytics. Avaya has developed a speech analytics engine that can understand context as well as sentiment. Two examples were cited. In the first, contact center agents were given a new script to use with customers. For a variety of reasons, some of the agents resisted this new way to work with customers. The speech analytics engine was applied to the conversations. Whereas only 20% of the agents were diligently using the new script before analytics were applied, over 90% used it after the analytics engine was used because contact center management had an easy to tell not just that agents were using the right script, but they were also able to detect the sentiment with which the agent approached the customer.
In another example, a major broadcasting organization fed years of archived video footage into the speech analytics engine with the intent to make these video clips easily searchable using text phrases and tags. The accuracy of the tagging was surprisingly high, making it much easier to find a particular video clip.
As I listened to this explanation of big data and analytics, I recall one of my Constellation Research colleagues, Alan Lepofsky, suggesting that before organizations roll out social software or big data, they need to understand the “why”, meaning “why are they doing this”. Brett’s explanation of how big data will be used in the contact center and how it can impact outcomes was one of the most compelling approaches I've heard; it centered around this need for understanding the “why”. The way Avaya will sell big data and analytics to its customers will be to focus on the outcomes the CEO the chief customer experience officer want to have. Then, it will tune the analytics engine and the underlying contact center routing, operations, and rewards toward achieve those desired outcomes.
Data to Decisions Next-Generation Customer Experience Tech Optimization
For example, Rhodin asked that we image a central “employee center” for global organizations – one which becomes a trusted career advisor from pre-hire through advanced roles in the organization through the continuous analysis of formal, informal, social and other inputs (structured and unstructured) to present a highly personalized, dynamic and guided path for each individual. Not the static, pre-defined career paths of the past, but truly intelligent, contextual and adaptive guidance to the individual all throughout their career with a company.