NICE Systems Launches Customer Engagement Analytics Platform

2 minute read
Barry Levine avatar

Understanding what online customers are doing, and predicting what they will do, has become a major part of contemporary e-Commerce. But, with so many online channels and so many types of customer actions, how best to capture, display and interpret? Toward this end, customer analytics provider NICE Systems is now offering it Customer Engagement Analytics (CEA) platform, which it described as the “industry’s first to combine interaction and transaction analysis.” 

The CEA platform is designed to capture and analyze customer data across channels and to track a customer through all the touchpoints in a journey, such as receiving a bill, logging into a web account to resolve an issue, emailing the company and, as a final step, contacting customer service.

The customer’s path is presented at the individual level by groups or segments and as part of the entire customer base, in order to improve a customer’s experience while also improving business procedures and efficiency. Specific applications will be offered on the platform, with the first one being Call Volume Reduction. Others, including sales optimization and “voice of the customer,” are expected soon.

Structured or Unstructured Data

Yochai Rozenblat, President of the NICE Customer Interactions Group, said in a statement that his company’s new Big Data analytics platform delivers “insights from the vast amount of data collected across interactions and transactions” to improve business performance.

The platform collects data from customer interactions and transactions in such sources as Web actions, phone, social media or chats, and from CRM, billing and other systems. Raw data is pre-processed to increase analytical efficiency, and the analytics engine can handle large amounts of either structured or unstructured data.

Learning Opportunities

Call Volume Reduction

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Insights can be obtained from mapping and other visualization of customer journeys, and trends can be detected. The company said it expected the analytics-derived insights will be used for evolving business policies and processes, or for such specific operational uses as agent coaching.

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The company offers an example use case for Call Volume Reduction, in which a phone company finds that many new owners of a smartphone, purchased from a particular retail branch, call into customer service within 72 hours in order to activate an accompanying email account. The platform informs the telco in real time that this customer behavior is occurring, so policy and targeted coaching for agents can be directed toward efficiently managing this surge in call volume.