IBM’s Predictive Analytics Software Understands You

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IBM announced new software that will enable users to discover and analyze information from social media sources, merging that information with internal data to gain insights and predictive intelligence. You might be thinking that this isn’t really any different from any other analytics solution (predictive or otherwise) but you would be wrong – very, very wrong.

What makes the data mining and text analytics software unique is that it allows for the monitoring of changes in attitudes, uncovering insights and predicting key factors that will influence 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. Did that just blow your mind? Because it just blew mine!

Customers of IBM’s predictive analytics software can directly access text, web and survey data and integrate it into predictive models for recommendations, ultimately making 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, extracting, discovering and exploring relationships between concepts and sentiments, including emoticons and slang terminology at a specific time and through a specific channel.

A good example of this in action comes from Rosetta Stone, a provider of technology-based language-learning solutions. Seeking to proactively capture and analyze consumer responses, the company relies on IBM’s predictive analytics software to reveal trends in text responses from online customer product reviews, competitor websites and open-ended survey questionnaires and 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."

 

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