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Transera Taps Into Big Data Analytics to Optimize Customer Interactions
|By Business Wire
|June 11, 2014 06:33 AM EDT
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 prioritize 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.”
Transera’s approach to achieving true analytics-driven customer
engagement consists of four stages: Information; Insights; Intelligence;
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.
Insights – A Customer Engagement Analyzer is used to segment,
profile and visualize the data in the Customer Engagement Repository to
identify correlations, trends and patterns that may impact performance.
Intelligence – Using predictive models, simulation engines,
machine learning, the R analytics language and analytics techniques, the
Transera Data Science Team validates insights that may predict customer
propensities and agent performance.
Improvements – At the end of the process, the Transera Data
Science Team recommends how to optimize contact center system and agent
behaviors for the desired business outcomes.
“Our analytics-driven approach to agent scoring and determining customer
propensity offers a better and more accurate alternative to the many
subjective approaches currently in use,” said Kumaran Ponnambalam,
Director of Data Science and Analytics at Transera. “It is because our
approach is based on Data Science and Big Data Analytics best practices
that we have been able to increase sales conversion rates by upwards of
20 percent for our customers.”
For each of its clients, the Transera Data Science Team conducts a
descriptive and predictive analytics-as-a-service process to perform:
Clustering – to find the true commonality among the data, such as
clusters of ideal customers or agent performance levels.
Stability and variance analysis – to determine the data set size
or time frame required to build reliable predictive models; too little
will not show reliable results and too much can mask significant
What-if analysis and modeling – to develop different hypotheses
that could impact business outcomes such as call routing strategies,
scripting modifications, customer prioritization, offers or proposed
Simulation modeling - to test the different hypotheses and
determine potential return on investment.
“In an age where customers are engaging with your company across
numerous devices and platforms, it is essential to use the right
analytics tools to effectively access and analyze customer data,” said
Richard Snow, VP and Research Director at research firm Ventana
Research. “Transera gives contact centers a clear picture of what
factors drive performance and applies predictive analytics to help
companies not only improve customer service, but the business outcomes
of each customer engagement.”
Transera will be hosting a live webinar on June 18th at 11am
PT. Kumaran Ponnambalam, Director of Data Science and Analytics, will
provide an overview of the Transera Statistical Analytics approach and
detail a case study of how his team applied the approach to score and
identify the best available agents for an online provider of personal
computer technical services and the resulting financial improvements. To
register for the webinar, go to http://bit.ly/1kNmTCw
For additional information about Transera’s customer engagement
offerings, go to: http://www.transerainc.com/products/
About Transera Inc.
Transera makes sense out of diverse customer interaction data so that
sales, marketing and customer service and support organizations can
increase sales, retain customers and improve customer satisfaction
through improved customer experiences. A pioneer in cloud-based
analytics-driven systems for contact centers, Transera brings data
together in the cloud from automated call distributor (ACD)
applications, interactive voice response (IVR) systems, customer
relationship management (CRM) applications and other customer data
sources such as demographic services so that contact centers can
analyze, understand, manage and automate customer interactions in new
and innovative ways. The Transera Customer Engagement Analyzer is an
interactive analytics application to perform analysis on customer
interactions and agent activity to determine what produces the best
business outcomes. These insights can then be used to change the
behavior of agents and on-premise and cloud-based contact center systems
to drive better performance and customer experiences. Today,
industry-leading companies such as Wirefly, AON, Office Depot, TiVo and
Guthy-Renker are leveraging the market-leading contact center solutions
from Transera. www.transerainc.com
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