Contact Center Solutions Featured Article

SAS Analytics Helps CSPs Understand Evolving Customer Requirements

September 18, 2012

Communications service providers (CSP) must target the right audience for their marketing offers to overcome fierce competition and boost business performance. Through innovative solutions and using SAS, from the leader in business analytics software and services, organizations can better segment their markets, determine how and when to target influencers, and test new campaigns, products and services.

SAS helps CSPs understand evolving customer requirements and relationships.

SAS Customer Link Analytics is also used by telecommunications companies in Argentina, Australia, Greece, India, Japan, the Philippines, Turkey, Romania and the U.S.

“Early adopters who are socially engaged wield enormous influence over others’ purchasing decisions. SAS Customer Link Analytics has proven invaluable in identifying these crucial customers and understanding what they like,” said Ken King, director of SAS Telco and Media Convergence.

SAS Analytics provide an integrated environment for predictive and descriptive modeling, data mining, text analytics, forecasting, optimization, simulation, experimental design and more.

SAS provides a range of techniques and processes for the collection, classification, analysis and interpretation of data to reveal patterns, anomalies, key variables and relationships, leading ultimately to new insights and better answers faster. SAS is different as it offers an integrated suite of analytics software.

Individuals can explore data for strategic business advantage, and analyze data to solve complex problems, create new insights and conduct evidence-based decision making.

SAS analytics offers the following components:

  • Predictive Analytics and Data Mining – Build descriptive and predictive models and deploy results throughout the enterprise.
  • Data Visualization – Enhance analytic effectiveness with dynamic data visualization.
  • Forecasting, Econometrics and Time Series – Analyze and predict future outcomes based on historical patterns.
  • Model Management and Monitoring – Streamline the process of creating, managing and deploying analytical models.
  • Operations Research – Leverage optimization, project scheduling and simulation techniques to identify the actions that will produce the best results.
  • Quality Improvement – Identify, monitor and measure quality processes over time.
  • Statistics – Use statistical data analysis to drive fact-based decisions.
  • Text Analytics – Maximize the value buried in unstructured data assets.


“As a mobile operator serving a large customer base in a very competitive market, microclustering helps us direct the most suitable offers to customers through the most effective channel of contact,” said Elisabetta Ripa, director of Mobile Consumer Market for Telecom Italia.

“SAS Customer Link Analytics helps us understand the behavior of our customers and the relationships among them, so we can maximize the results of our CRM retention and up-selling efforts,” Ripa added.

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Edited by Braden Becker