Cegid Group

Predictive analytics relied on to spot untapped revenue opportunities, enabling reps to take action

Published on 12-Nov-2013

"By making it easier for account teams to coordinate with each other, and by providing them with predictive insights that they can act on when it matters most, the solution is helping the company capitalize on revenue opportunities and keep customers satisfied." - Cegid Group

Customer:
Cegid Group

Industry:
Computer Services

Deployment country:
France

Solution:
BA - Business Analytics, BA - Predictive Analytics, Smarter Planet

Overview

A leading developer of management software in France with annual sales of EUR263.8 million in 2011, Cegid Group counts more than 2,000 employees and 350,000 users in France and abroad. Based in Lyon, the company operates branch offices in Paris, New York, Barcelona, Madrid, Milan, London, Casablanca, Shenzhen, Tokyo and Singapore.

Business need:
As a decentralized company with product-centric business units, it was a challenge for Cegid account teams to coordinate in identifying new revenues opportunities, as well as migration risks, within its existing accounts.

Solution:
This business software provider built a predictive modeling tool that analyzes the parameters of its existing account relationships to segment its customers based on untapped up-selling and cross-selling revenue opportunities.

Benefits:
The IBM solution helped increase the productivity of support teams, expand opportunities for cross-selling and up-selling and increase customer retention.

Case Study

A leading developer of management software in France with annual sales of EUR263.8 million in 2011, Cegid Group counts more than

2,000 employees and 350,000 users in France and abroad. Based in Lyon, the company operates branch offices in Paris, New York, Barcelona, Madrid, Milan, London, Casablanca, Shenzhen, Tokyo and Singapore.

The Opportunity
As a decentralized company with product-centric business units, it was a challenge for Cegid account teams to coordinate in identifying new revenues opportunities, as well as migration risks, within its existing accounts. The company envisioned a more coordinated approach to account management that would improve its ability to understand its needs as well as unmet concerns. Its missing link was the ability to look into its customer data and extract the insights needed to guide its actions.

What Makes It Smarter
Business customers seldom put up signs telling their vendors and service providers where to find new revenue opportunities within their existing relationships. Indeed, it’s up to providers to discover and exploit cross- selling and up-selling opportunities that aren’t always apparent. By the same token, the key to keeping customers on board is addressing issues before they reach the tipping point of customer migration. This business software provider built a predictive modeling tool that analyzes the parameters of its existing account relationships to segment its customers based on untapped up-selling and cross-selling revenue opportunities. Moreover, by analyzing the content of its customer correspondence logs with advanced textual algorithms, the provider not only identifies accounts at risk of migrating, but also prioritizes these at-risk customers so that account teams can channel their resources to where they’re
needed most.

Real Business Results
• Increased the productivity of support teams by 10 percent
• Expanded opportunities for cross-selling and up-selling through a more coordinated customer coverage model
• Increased customer retention through early detection and proactive response to at-risk account situations

For More Information
Please contact your IBM representative or IBM Business Partner. Visit us at ibm.com/spss.

To learn more about Cegid Group, visit www.cegid.com.

Products and services used

IBM products and services that were used in this case study.

Software:
SPSS Modeler

Legal Information

© Copyright IBM Corporation 2013 IBM Corporation Software Group Route 100 Somers, NY 10589 Produced in the United States of America November 2013 IBM, the IBM logo, ibm.com and SPSS 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 performance data discussed herein is presented as derived under specific operating conditions. Actual results may vary. 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.