1. Bruce Kolodziej Analytics Sales Manager May 15, 2012 Predictive Analytics and WebFOCUS RStat Overview Montreal User Group Meeting

2. What is Predictive Analytics? Predictive Analytics (PA) helps one to…  Discover/understand what’s going on  Predict what’s going to happen  Improve overall decision making  Improve business processes  Create a competitive edge! Predictive Analytics IS a key business process…  “Learning from experience”  Not new  User-centric, interactive  Leverages analysis technologies and computing power  Keeps the focus on the business issue  An information-based approach to decision making  Results are mainly used in a forward-looking style  “Next Generation BI”

3. Extending Business Intelligence with Predictive Analytics Degree of Intelligence Standard Reports Ad Hoc Reports Query/Drill Down KPIs/Alerts What happened? How many, how often, where? Where exactly is the problem? What actions are needed? Rear View Statistical Analysis Forecasting/Extrapolation Predictive Modeling Optimization Why is this happening? What if these trends continue? What will happen next? What is the best that can happen? Forward View Note: Adapted from “Competing on Analytics”

4. Business Intelligence with Predictive Analytics Copyright 2007, Information Builders. Slide 4 Business Intelligence + Predictive Modeling = 145% ROI Business Intelligence = 89% ROI Business Intelligence + Predictive Modeling = 145% ROI Business Intelligence = 89% ROI Median ROI Source: “Predictive Analytics and ROI: Lessons from IDC’s Financial Impact Study”

5. Companies That Use Predictive Analytics Compete Better in the Marketplace * IBM Survey was conducted on 3,000 executives, managers and analysts working across more than 30 industries and 100 countries where respondents were asked to assess their organization’s competitive position ^ IDC white paper “The Financial Impact of Business Analytics” Study 1 * : Predictive Analytics = better performance 45% 20% 53% 27% Top Performers Use analytics to guide future strategies Use analytics for day to day operations Bottom Performers

6. Copyright 2007, Information Builders. Slide 6 InformationWeek BI Survey Results Predictive Analytics is the top response

7. Copyright 2007, Information Builders. Slide 7 6 Major Tech Innovations for 2012 Predictive Technology is the top response 1.Predictive Technology a.Several companies have started talking about their research into predictive tech. The idea is that, as computers become smarter, they can analyze historical data to make predictions. 2.HTML5 3.High resolution displays 4.Social analytics 5.Speech for business 6.Business-ready storage http://www.inc.com/john-brandon/6-major-tech-innovations-for-2012.html

8. Copyright 2007, Information Builders. Slide 8 Predictive Analytics 101  I have a variety of data (transactions, demographics, offers, responses, accounts, purchases, geography, from a variety of sources)  I’d like to predict the likely future behavior of a customer  I use historic data that has examples of that behavior Age Education Marital Gender Occupation Historic Response to Offer 21 College Single Male Engineer Yes 23 HSgrad Single Male Administrator No 29 HSgrad Married Female Bus. Owner Yes  Build a model (find the patterns) then use the model to predict that behavior for new records Age Education Marital Gender Occupation Predicted Response to Offer 24 HSGrad Married Male Engineer No 27 College Single Female Bus. Owner Yes 31 PhD Married Male Bus. Owner Yes

9.  Sales, Marketing and CRM  It’s very expensive to acquire new customers, there must be a better way  If I understood who my best customers are, I could target more like that  I wish I knew which of my customers were interested in offers, instead of offering all products to all customers  Response rates to our campaigns are low and declining, how can we better target our customers?  I wish I knew which customers were most likely to churn so I could retain them  How can I provide better service to my customers by understanding their needs and guide my interactions? Business Initiatives That Predictive Analytics Can Address

10.  Fraud  How can I predict fraudulent activity and at the same time avoid investigating 100% of my data?  Risk  I want to approve and price my prospects for insurance coverage appropriately  I want to approve my prospects for loans or credit to maximize profit and minimize my risk  Process Improvement  How can I use my process data to uncover the root cause of defects?  How can I better predict the time until some event (failure, attrition, churn) occurs? Business Initiatives That Predictive Analytics Can Address

11. WebFOCUS RStat Solutions and Applications Consumer Packaged Goods

12. WebFOCUS RStat Solutions and Applications Financial Services

13. WebFOCUS RStat Solutions and Applications Insurance

14. Copyright 2007, Information Builders. Slide 14  Leverages widely available statistical models to improve decision making  Decisions based on high probability – NOT “gut- feel”  Makes building “scoring” systems easy  Enables predictive applications at a fraction of the cost of other solutions  Based on “R” open source system Business Value: By binding predictive analytics with WebFOCUS you can embed high probability directions, scores and expected outcomes into frontline operational processes, improving returns. WebFOCUS RStat Predictive Analytics

15. WebFOCUS RStat 1.3.1 New Features Overview  Improved performance on large data set scoring  Traditional predictive model deployment is to deploy the model to the WF server, but now we have the option of scoring in-database  Can export the scoring model C files that are Teradata UDF (user defined function) compliant for in-database processing  When scoring large amounts of data, executing the predictive model using in- database processing results in significant performance gains and reduces data movement  Integration of R scripts into the RStat GUI  R code can now be brought into RStat  Can re-use the code, no need to re-build in RStat  R code can be executed in RStat and files or plots are outputted for results analysis  Also, for models that are currently deployable via RStat, these R script models are deployable

16. WebFOCUS RStat Success Story Grand Sierra Resort & Casino Reno, Nevada GSR’s Goals  Link hotel, gaming, entertainment and food/beverage data for a complete customer view  Wanted the ability to do better target marketing and customer retention programs  Marketing was based on “gut-feel” and much $$ was not well spent  Wanted to take a data-driven approach and improve ROI Information Builder’s Solution  Predictive analytics will allow them to do things not available today  Targeted promotions and campaigns to maximize response  Predict which customers will churn and when, in order to prevent churn  Data Integration, Predictive Analytics and BI Reporting together positioned IBI as a full service technology provider

17. WebFOCUS RStat Demonstration  Walk through the RStat interface  Demo scenario of targeting customers with an offer  Using attributes of age, gender, marital status, occupation, income and education  We’ll build a model to uncover the patterns related to responders and non- responders historically  Then apply the model to a new data set to predict future responders and non-responders  Assists an organization with targeting their offers efficiently and cost- effectively  Focus on ease of use, broad range of capabilities and easy deployment of predictive results to end-users  This approach is the same for offer targeting, churn or fraud or risk predictions, part failure predictions, etc  The data differs, but not the approach

18. Active PDFs Displaying Predictive Output

19. WebFOCUS RStat Predictive Churn Dashboard

21. Copyright 2007, Information Builders. Slide 21 Predictive Analytics Summary Organizations use predictive analytics to:  Reduce marketing/operational costs  Increase sales  Reduce defects  Improve site location  Increase web site profitability  Improve cross-sell/up-sell campaigns  Increase retention/loyalty  Detect and prevent fraud  Identify credit risks  Acquire new customers  Improve assortment planning ROI is realized when:  Decision-making is improved with forward-looking views of likely behavior  Results are widely-distributed to end users where decisions are made

22. Copyright 2007, Information Builders. Slide 22 Why WebFOCUS RStat? Summary of Differentiators  Integrated Solution  Data access and preparation, business intelligence, predictive model building and deployment of results all in one integrated platform  Historical, present and future views  Cost Effective  Based on open-source R, RStat is the best value on the market  Contains the most commonly used techniques  Why pay for techniques that will rarely, if ever, be used?  If another technique is needed, the R language is equipped  Predictive Analytics and Statistical Analysis Together  Covers a wide variety of business objectives and data sources  RStat is a General Purpose Analytic Solution  Not a niche product for risk or fraud or churn or quality or cross-selling analysis. RStat is all of these = maximum value and ROI

23. Wrap-up  Thank you for your time today!  For additional information or if you have any questions, please contact  Bruce Kolodziej, Analytics Manager  Bruce_Kolodziej@ibi.com Bruce_Kolodziej@ibi.com  917.968.6035  Or contact your local Information Builders Account Executive