Nedbank Ltd.

Faster and deeper social media data insights gained by deploying a near-real-time text-analytics solution

Published on 11-Sep-2013

"By improving our social media analytics capabilities, we’re engaging with our customers more deeply, finding and solving problems more quickly and taking better advantage of opportunities." - Liebenberg, head of retail BISS decision science support (DSS)

Customer:
Nedbank Ltd.

Industry:
Banking

Deployment country:
South Africa

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

IBM Business Partner:
Olrac spSolutions

Overview

Founded in 1888 and headquartered in Johannesburg, Nedbank Ltd. is a financial services provider that offers banking, investment, loan, credit card and asset-management services and products to customers throughout southern Africa.

Business need:
Nedbank needed to make a comparable leap in its ability to extract actionable insights from social media feedback.

Solution:
A predictive modeling solution—enhanced through automation tools—provides decision makers across the bank’s operations with deep, near-real-time analysis of social media data through flexible dashboards, giving marketers potent insights regarding preferences, sentiment and satisfaction that help them craft and deliver more effective promotions and messages.

Benefits:
With the SPSS Modeler software, Nedbank can more sharply focus its marketing campaigns, promote high profit margins and increase cross-selling opportunities.

Case Study

Founded in 1888 and headquartered in Johannesburg, Nedbank Ltd. is a financial services provider that offers banking, investment, loan, credit card and asset-management services and products to customers throughout southern Africa. The company is the principal banking subsidiary of holding company Nedbank Group Ltd. It reported market capital of USD8 billion in 2011.

The Opportunity
With social media jumping to the core of its strategic marketing arsenal, Nedbank needed to make a comparable leap in its ability to extract actionable insights from social media feedback. It sought to gain faster and deeper results for decision makers to act on.

What Makes It Smarter
A predictive modeling solution—enhanced through automation tools—provides decision makers across the bank’s operations with deep, near-real-time analysis of social media data through flexible dashboards, giving marketers potent insights regarding preferences, sentiment and satisfaction that help them craft and deliver more effective promotions and messages.

Real Business Results
With the SPSS Modeler software, Nedbank can more sharply focus its marketing campaigns, promote high profit margins and increase cross-selling opportunities. The solution also facilitates more operational efficiency as well as cost savings. By integrating social media analytics into existing systems and processes, the bank streamlines the means by which customer service representatives identify and address problems, resulting in a 20 percent increase in their productivity, while a greater degree of autonomy in performing social media analysis and reporting cuts agency costs by USD105,000.

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

To learn more about Nedbank Ltd., visit http://www.nedbank.co.za.

Products and services used

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

Software:
SPSS Collaboration and Deployment Services, SPSS Modeler

Legal Information

© Copyright IBM Corporation 2013 IBM Corporation Software Group Route 100 Somers, NY 10589 Produced in the United States of America September 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.


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