IBM Business Analytics Helps Improve Customer Retention by Nearly 50 Percent at XO Communications

IBM business analytics software allows XO to analyze big data for faster, more proactive customer service

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LAS VEGAS, N.V. - 25 Oct 2011: IBM (NYSE: IBM) today announced that XO Communications, a leading nationwide provider of advanced broadband communications services and solutions, has reduced its customer churn rates by nearly 50 percent, largely through the use of IBM predictive analytics software. The software has helped save XO millions of dollars by uncovering deeper insights into customer behaviors, spotting trends, identifying those likely to defect, allowing proactive actions to keep their most valuable customers.

In the competitive communication service provider industry, a fundamental tenet is that it costs much less to retain an existing customer than it is to acquire a new one. The challenge is to identify customers who are at the highest risk of churn before they switch to another service provider.

By leveraging the power of IBM predictive analytics software, XO Communications, based in Herndon, Virginia, has achieved significant improvement in customer retention and revenue protection with better quality customer interactions in contact centers and through more effective marketing campaigns.  

XO has vast amounts of customer data, including demographics, transaction history, calling patterns, and conversations with call center agents. They compiled more than 500 data variables on its customers, and used the software to identify specific trends and correlations in those variables that were the most predictive to voluntary churn. By applying those results to its current customer base, XO could then accurately predict and proactively engage with the most valuable and profitable customers who carried the highest churn scores.

“IBM business analytics software has been the difference maker to our organization, allowing us to exceed our initial goals by improving retention rates, and creating millions of dollars in annualized revenue protection,” said Cris Payne, senior manager of customer intelligence at XO Communications. “With a better overall customer experience, XO is now able to stay competitive against other carriers and improve our overall satisfaction. Our IBM business analytics portfolio allows us to quickly produce edible customer information leading to more strategic decisions affecting our top and bottom lines.”

Traditionally, retention programs focus on keeping customers in contract, and focus on when contracts should be renewed. IBM predictive analytics allows XO to go beyond just looking at contract end dates by developing a better understanding of the entire customer experience. This allows the organization to prioritize their proactive outbound calls to “high risk” customers and better organize their resources. Now, each client services manager can monitor churn risk on up to 400 accounts.

“IBM’s business analytics software allows communications service providers to leverage all available customer data to quickly and accurately increase customer retention, acquire more profitable customers and create better interactions at every touch point,” said Deepak Advani, vice president of predictive analytics at IBM. “XO is a terrific example of an organization who has unleashed the power of predictive analytics to positively impact their business processes and significantly drive ROI."

Using numerous IBM business analytics solutions, XO has been able to quickly build and analyze customer data and share the information across the organization. IBM SPSS predictive analytics analyzes and scores customer data, while an IBM Netezza analytic appliance speeds data delivery and facilitates the creation of faster predictive models. Finally, IBM Cognos business intelligence software allows everyone across XO to better share, consume and collaborate with the data more effectively.

According to independent analyst firm Nucleus Research, XO recorded an 376 percent ROI in just 5 months, an average annual benefit of $3,819,200 million. Download the full case study here.

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