New IBM Predictive Analytics Software Enables Users to Uncover and Analyze Information from Social Media Sources

Originally published 11 May 2010

IBM recently announced new software that enables users to uncover and analyze information from social media sources, such as social networks and blogs, and then merge that with vast internal data for faster, more accurate insight and predictive intelligence.

The new data mining and text analytics software allows users to monitor changes in consumer, constituent and employee attitudes, uncover deeper insights, and then predict key factors that will drive future customer acquisition and retention campaigns. For example, companies can now extract sentiment from the use of emoticons and slang terminology that people often use in describing their view toward a product or service.

As part of today's news, IBM is also announcing customers such as Navy Federal Credit Union, Rosetta Stone and Money Mailer that are making faster and more personalized decisions with predictive analytics software through insight gained by extracting information about client sentiment from a variety of data sources.

Recognizing that each industry has unique priorities and its own vernacular, the new software analyzes trends and captures insights from industry-specific terminology. Within these domains, the software includes new semantic networks with 180 vertical taxonomies (from Life Sciences to Banking and Insurance, and Consumer Electronics), and more than 400,000 terms, including 100,000 synonyms and thousands of brands. This allows customers to draw better links and understanding between sentiment and products without having to spend time building their own definitions.

For instance, in the banking industry, the semantic network knows that a "floating rate" is a "Mortgage Loan," and "Variable Rate Mortgage" and "Adjustable Rate Mortgage" are synonyms. It can also detect that "estate planning," "older people," and "retirement planning" are related to "reverse mortgage."

Analyze Textual Data Sources from Social Media to Improve Analysis

With IBM predictive analytics software, customers can directly access text, web and survey data and integrate it into predictive models for more comprehensive recommendations and better business decisions. It uses natural language processing (NLP) to allow clients to pull key concepts, opinions and categories relevant to their business from these data sources to uncover deeper customer insights.

Organizations can combine all of their structured data with textual information from documents, e-mails, call center notes, and social media sources. By incorporating text sources into modeling efforts, users can extract, discover and explore relationships between concepts and sentiments, including emoticons and slang terminology, leading to better insight to reach specific customers, constituents, employees or students at a specific time and through a specific channel.

For example, to proactively capture and analyze consumer responses, Rosetta Stone Inc., a leading provider of technology-based language-learning solutions, relies on IBM predictive analytics software to uncover hidden trends in text responses from online customer product reviews, competitor websites and open-ended survey questionnaires. This enables the company to recognize why certain customers are brand promoters or brand detractors, and improve customer satisfaction, product development and marketing effectiveness.

Nino Ninov, vice president of strategic research and analysis at Rosetta Stone, said, "Predictive analytics allows us to leverage unsolicited and unbiased customer feedback and strategically improve our business. We now can also monitor competitor and industry websites, including blogs and news feeds, and other publicly available textual information to maintain a current view and better understand how the public perceives our competition."

Navy Federal Credit Union Doubles Growth with Predictive Analytics

IBM predictive analytics can be combined with the entire portfolio of IBM technologies to improve their current business and operational environments.

Navy Federal Credit Union, the world's largest credit union with more than 3 million members, has improved member services and satisfaction levels with both IBM business intelligence software and IBM predictive analytics.

By improving customer intimacy with its membership, Navy Federal is able to better meet their changing needs and communicate on a one-to-one basis. This expanded ability to better understand its membership and predict behaviors has enabled Navy Federal to grow from $24.8 billion in assets to $40 billion.

Alan Payne, manager of member research and development at Navy Federal Credit Union, said, "We are able to identify and anticipate member needs, analyze trends and provide a variety of member profiles to our business units that develop product and service offerings to meet and surpass member expectations. IBM business intelligence and predictive analytics software allows us to uncover greater insight into our membership and identify areas of opportunity to increase our satisfaction levels. Increasing awareness of our products and services, and also creating new offerings that meet our members' changing needs and behaviors has lead to better service and member understanding, and more strategic decision making."

Achieving True Customer Intimacy with Predictive Analytics

Customer interactions through any channel are now truly evidence-based and result in more predictable and profitable outcomes. IBM predictive analytics software allows users to translate customer knowledge into action. The result is a more effective customer relationship management strategy, including advertising and marketing campaigns; upsell and cross-sell initiatives; and long-term customer loyalty, retention and rewards programs.

Money Mailer is a leader in the U.S. direct marketing industry. By optimizing direct marketing results through integrated shared mail, one-to-one, and interactive solutions such as email, SMS text messaging and online coupon circulation, Money Mailer is able to accurately target every household in the United States. The organization uses IBM predictive analytics software to optimize direct mail campaigns and predict who is most likely to respond and will be most profitable and loyal for their clients.

John Gramata, vice president of marketing at Money Mailer, said, "IBM predictive analytics software provides our organization with an advanced, powerful and user-friendly data mining platform that enables us to reach the best customer through the right channel at the right time for our clients. This solution not only saves us time and money, but more importantly, it helps us increase our clients' return on marketing investment. IBM predictive analytics is a key competitive edge for any organization; without it, we couldn't serve our customers nearly as effectively."

SOURCE: New IBM Predictive Analytics Software Enables Users to Uncover and Analyze Information from Social Media Sources