Predictive analytics drives proactive, real-time decision making - Predictive analytics solutions empower your entire organization to spot trends, risks, and patterns hidden in your Big Data and gain actionable insights to make better, more confidant decisions.

SAP Analytics, June 24, 2014 -- The benefits of predictive analytics are no longer reserved for select data scientists and high-level executives. Solutions are now available that can empower the entire organization with actionable insights. With self-service capabilities, business users can quickly drill down to individual customer data and gain the information they need to:

  • Answer complex questions about customers in real time
  • Identify and home in on problem regions and customers
  • Win back business and strengthen loyalty with deeper customer insights

PROBLEM SOLVER. Leveraging predictive technology, business users can not only analyze what customers have done in the past, but they are also able to accurately anticipate what customers will do in the future. Agile visualizations enable the entire organization to spot trends, risks, and patterns such as declining revenue and customer churn propensity hidden in the company’s Big Data and use these insights to improve its response to customers.

THE SOCIAL SIDE. Predictive analytics solutions give organizations the ability to analyze continuous streams of data, including transactional data and unstructured data created by external sources like social media.This combination of customer behavior and social media and sentiment analysis provides the organization with a 360-degree view of the customer. Based on these insights, predictive models can be built that show possible proposed offers customers are most likely to accept in the future and reveal potential cross-sell and up-sell opportunities. 65% of companies are currently using or plan on using social media data over the next three years for predictive analysis. (TDWI,“Predictive Analytics for Business Advantage”).

PREDICT CHURN PROPENSITY. Leveraging predictive analytics solutions that can combine vast amounts of structured and unstructured data points, mine them for insight, and build predictive models, organizations can put a numerical value on a customer’s churn propensity. From there, they can identify where the highest potential risk is for customer churn from a regional, local, or individual level, enabling them to better allocate their resources and focus their energy on where it is needed most. Loudhouse Consultancy,“Predicting the Future of Predictive Analytics,” Companies in the United States and UK cite predicting customer needs and market trends as two primary reasons why they use predictive analytics.

PREDICTIVE SOLUTIONS. With a comprehensive view of your customers’ wants, needs, and pain points, companies are able to increase their understanding of customer behavior, improve their response to customers, and deliver tangible business value, ultimately driving their profitability.


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