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Transera taps into Big Data Analytics to optimise customer interactions

11/06/2014 by


Transera, the Customer Engagement Analytics in the cloud company, today announced the first Statistical Performance Analytics for contact centers that provides reliable predictions on agents’ future performance and customers’ needs and propensities based on historical agent and customer activity data. Using months of data, Transera can match the customer with the best available agent for the desired business outcome.

This approach is being used to prioritise customers based upon their needs. Agents are assigned to the customer based upon the agent’s ability to achieve the desired results, including conversions, retentions and customer satisfaction. The agent is selected based upon an algorithmic scoring model that combines individual agent and overall agent population past performance data to predict an agent’s future performance with high fidelity. The algorithmic score takes into account agent churn, new agent ramp time and the unique abilities of each agent.

“Transera has created a practical, scalable solution for unlocking business value from the enormous amounts of contact center agent and customer data in enterprises today,” said Prem Uppaluru, Transera’s president and chief executive officer. “With Transera’s Customer Engagement Analytics SaaS offering, performance analytics is now within reach of any contact center, providing rich insights into customer interactions at a realistic price point.”

The Process

Transera’s approach to achieving true analytics-driven customer engagement consists of four stages: Information; Insights; Intelligence; Improvement.

Information – Data from the various contact center systems are collected and connected in a cloud-based Customer Engagement Repository, which contains a contact center system-aware universal data dictionary and uses Big Data techniques and technologies such as Hadoop and NoSQL.

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