Published on 03-Apr-2012
"By enabling our client service managers to prioritize their proactive outbound calls, we can cover more risk with our existing client services team. It’s been a very successful business model for us and has helped us organize our resources better." - Trent Taylor, Director of Customer Intelligence, XO Communications
Customer:
XO Communications
Industry:
Telecommunications
Deployment country:
United States
Solution:
Big Data, Business Analytics, Business Intelligence, Smarter Analytics, Smarter Analytics - Grow & retain customers
Overview
XO Communications is a communications service provider that focuses exclusively on US business and government customers and the global telecommunications sector. Founded in 1996, it has grown to employ more than 4,000 people and generate annual revenues of more than $1.5 billion.
Business need:
Business objectives included: protect existing revenues by reducing customer churn. Increase profitability: retaining existing customers is more cost-effective than winning new ones. Improve client service without substantially increasing headcount. Implement a predictive analytics framework to produce the insight required for the Customer Intelligence organization.
Solution:
After a thorough industry evaluation, XO Communications deployed IBM Predictive Analytics solutions. The XO Communications team worked with IBM Education Services to build up a high level of competence in-house and transitioned away from the early models built by third-party consultants. This enabled the team to identify the factors that indicate whether a given customer is likely to change providers, and build a sophisticated statistical model that provides a monthly risk assessment for each customer.
Results:
Improved customer retention by 26 percent over two years through targeted interventions with customers. XO Communications’ new ability to pinpoint and preempt customer churn delivers a 376 percent annual return on investment. The project paid for itself within five months, and provides an annual net benefit of over $3.8 million.
Benefits:
Uses predictive analytics to provide new insight into the behavior of thousands of small and medium business customers. Enables the company to identify the customers who are at greatest risk of changing provider and intervene to promote retention. Prioritizes client service workload, enabling each manager to monitor up to 400 individual customer accounts. Brings analytics skills and knowledge in-house, eliminating third-party costs and enabling the development of additional predictive models for other areas of the business.
Case Study
Strategy
In the communications sector, customer loyalty is the key to profitability – it costs much less to retain an existing customer than it does to win a new one. As part of an organizational business transformation project, XO Communications identified an opportunity to improve its performance in the small- and medium-sized business sector by increasing customer retention, and needed a strategy that would help it achieve this in a cost-effective way.
The majority of the customers in this segment spend less than $1,000 per month with XO Communications, so it was not economically prudent to allocate dedicated client service managers to each account. At the same time, it was vital to offer these clients a high level of service and ensure that any issues they had were dealt with quickly and effectively. Instead of a ‘brute force’ approach – simply hiring more client service managers – the company decided to use predictive analytics to identify the customers who were most at risk of changing providers, and prompt the client service team to intervene appropriately.
Focus on Business Impact
After a thorough industry evaluation, XO Communications deployed IBM Predictive Analytics solutions. The XO Communications team worked with IBM Education Services to build up a high level of competence in-house and transitioned away from the early models built by third-party consultants. This enabled the team to identify the factors that indicate whether a given customer is likely to change providers, and build a sophisticated statistical model that provides a monthly risk assessment for each customer.
Customers are prioritized based on the score the model calculates for them, and the client service team deals with the highest-risk customers first: making contact with them, finding out if they have any problems or are dissatisfied with the service they are receiving, and then taking appropriate steps to improve the situation.
Business Value Outcomes
A Nucleus Research ROI study has shown that XO Communications’ new ability to pinpoint and preempt customer churn delivers a 376 percent annual return on investment. The project paid for itself within five months, and provides an annual net benefit of over $3.8 million.
Deeper Insight
By bringing predictive analytics in-house and giving client managers the ability to identify the customer relationships that need most attention, XO Communications has been able to reduce customer churn without substantially increasing headcount.
Indirect Benefits
- Improved customer retention by 26 percent over two years through targeted interventions with customers.
- Reduces the need to invest heavily in winning new clients. Maintaining existing relationships is a much more cost-effective strategy.
Direct Benefits
- Enables each client service manager to monitor churn on up to 400 customer accounts. Without the predictive analytics solution, the company would require twice as many managers to handle the same workload.
XO Communications has applied the skills and experience from this project to generate additional returns in subsequent projects. With additional tuning and analysis, the next phase of the customer churn project has produced another $7 million in revenue and the model is 50 percent more accurate than the original. Not only has this prevented churn, but it has also increased the revenue stream. Other areas of focus include profitability analysis, bad debt write-offs, and some further levels of granularity with predictive modeling on a per-product basis.
Solution Review
The predictive analytics project originated as part of a full-scale transformation initiative to increase business efficiency at XO Communications. During the consultation phase of this initiative, the company decided to look into predictive analytics, and began a small project with a third-party consulting partner. The results of this project convinced XO Communications that predictive analytics could be a vital tool, and also highlighted the benefits of building up a capability in-house.
The company formed a Customer Intelligence team, tasked with purchasing and building a solution. The team performed a very thorough vendor evaluation before selecting IBM SPSS Modeler and IBM SPSS Statistics. This decision was based on the perceived superiority of the SPSS products in terms of functionality, scalability, licensing terms and ease of use.
The team utilized the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology to manage the project through six main phases: business understanding, data understanding, data preparation, modeling, evaluation and deployment. During the process, the team evaluated more than 500 variables to see which had the most influence on customer retention. Ultimately, a model was built based on the 25 most relevant variables. The model assigns risk scores to each customer. The top 20 percent reflects 66 percent of the churn, so the top 10 percent are passed on to the centralizaed retention team, and the next 10 percent are passed to the field retention team for remedial action.
As part of the project, the Customer Intelligence team received comprehensive training from IBM, which helped not only to gain technical knowledge, but also to build up a set of best practices for future predictive analytics deployments. As a result of the expertise gained, the team’s churn prediction model has been able to outperform the early third-party model by 50 percent. With the success of this initial project, the team is now embarking on a number of new initiatives using predictive analytics, as well as expanding information delivery with dashboards and business intelligence.
About Nucleus Research
Nucleus Research provides investigative, case-based technology research and advisory services. Nucleus analysts investigate hundreds of deployments every year to deliver unique insight into the measurable value of technology. Founded in 2000, Nucleus Research is headquartered in Boston MA and provides services worldwide.
About IBM Business Analytics
IBM Business Analytics software delivers actionable insights decision-makers need to achieve better business performance. IBM offers a comprehensive, unified portfolio of business intelligence, predictive and advanced analytics, financial performance and strategy management, governance, risk and compliance and analytic applications. With IBM software, companies can spot trends, patterns and anomalies, compare “what if” scenarios, predict potential threats and opportunities, identify and manage key business risks and plan, budget and forecast resources. With these deep analytic capabilities our customers around the world can better understand, anticipate and shape business outcomes.
Products and services used
IBM products and services that were used in this case study.
Software:
SPSS Modeler, SPSS Statistics Base, IBM Netezza 100, SPSS Collaboration and Deployment Services
Service:
IBM Learning Services, Software Services for Business Analytics
Legal Information
© Copyright IBM Corporation 2012. IBM Corporation, Software Group, Route 100, Somers, NY 10589. Produced in the United States of America. March 2012. IBM, the IBM logo, ibm.com, and Cognos are trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml. This document is current as of the initial date of publication and may be changed by IBM at any time. Not all offerings are available in every country in which IBM operates. The client examples cited are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions. It is the user’s responsibility to evaluate and verify the operation of any other products or programs with IBM products and programs. THE INFORMATION IN THIS DOCUMENT IS PROVIDED “AS IS” WITHOUT ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING WITHOUT ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND ANY WARRANTY OR CONDITION OF NON-INFRINGEMENT. IBM products are warranted according to the terms and conditions of the agreements under which they are provided.