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What’s New in Uplift Optimizer 5.3 Patrick Surry Product Manager USA: 1 866 793 4279 Austria 0800 28 1673 Belgium: 0800 505 60 Canada: 1 866 270 8076 India.

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Presentation on theme: "What’s New in Uplift Optimizer 5.3 Patrick Surry Product Manager USA: 1 866 793 4279 Austria 0800 28 1673 Belgium: 0800 505 60 Canada: 1 866 270 8076 India."— Presentation transcript:

1 What’s New in Uplift Optimizer 5.3 Patrick Surry Product Manager USA: Austria Belgium: Canada: India Republic of Ireland: Netherlands Norway: Spain Sweden: UK: International: Access code # Starting in 15 minutesStarting in 10 minutesStarting in 5 minutesStarting in 2 minutesStarting Now

2 © 2008 Portrait SoftwareStrictly Confidentialpage 2 How to ask a Question

3 © 2008 Portrait SoftwareStrictly Confidentialpage 3 What’s New in Uplift Optimizer 5.3

4 © 2008 Portrait SoftwareStrictly Confidentialpage 4 What’s New in Uplift Optimizer 5.3 Presenter: Patrick Surry Audience: Current users of Uplift Optimizer Goal: Highlight the key new features and functionality provided in version 5.3 Format: A live demo with some slides

5 © 2008 Portrait SoftwareStrictly Confidentialpage 5 Interaction Optimizer ™ Campaign Manager ™ Portrait Solutions Sales Service Customer Analytic Insight Analytic Insight Your CRM Siebel Microsoft Your CRM Siebel Microsoft Marketing Marketing Channels Campaign Management Campaign Management Interaction Management Uplift Interaction Management

6 © 2008 Portrait SoftwareStrictly Confidentialpage 6 Expert Opinion on Portrait’s Uplift Solution “Telenor will realize an 11-fold increase in uplift campaign ROI when compared with existing programs” – Gartner, “Magic Quadrant for Customer Data-Mining Applications 2008”, Gareth Herschel “Innovative” “Marketers can now add uplift modeling to the arsenal of tools” - Forrester Research “Optimizing Customer Retention Programs”, Suresh Vittal

7 © 2008 Portrait SoftwareStrictly Confidentialpage 7 Typical Analytical Tasks Predict response, attrition, credit risk, value Diagnosis of emerging issues Responding to market changes Incremental value vs. apparent response Savability Select group of customers Ad-hoc query Test hypothesis Create marketing segmentation Profile a set of customers “selection” “fast counts” “segmentation and profiling” “predictive modeling” “uplift modeling” Calculate historic customer value “calculation”

8 © 2008 Portrait SoftwareStrictly Confidentialpage 8 Uplift Modeling: Core Idea Traditional targeting is based on modeling outcomes, not uplift in outcomes Uplift Optimizer directly models the difference in behavior between a treated group and a control group to find the people most affected by an intervention This allows us to: –target people who are more likely to buy given an incentive, rather than simply those likely to buy –target people who can be saved from attrition by an intervention, rather than simply those likely to attrite –target people whose risk of default (or expected loss) can be reduced by intervention, rather than simply those with high risk

9 © 2008 Portrait SoftwareStrictly Confidentialpage 9 Uplift Targeting vs. Attrition Probability 0%20%40%60%80%100% Proportion targeted Attrition Rate 0% 4% 6% 8% 10% 2% -6% -2% 0% 2% 4% -4% Targeted Control Reduction in Attrition (Lift) (Most likely to Attrite first) (Most likely to be saved first) Uplift rate (change in Attrition probability)

10 © 2008 Portrait SoftwareStrictly Confidentialpage 10 StayLeave Stay Fundamental Segmentation for Retention PERSUADABLES SLEEPING DOGS  SURE THINGS  LOST CAUSES  When targeted When not targeted

11 © 2008 Portrait SoftwareStrictly Confidentialpage 11 MORE SAVABLE Attrition probability if not targeted 0 SLEEPING DOGSLOST CAUSES SURE THINGSPERSUADABLES Attrition probability if targeted Predicting Savability

12 © 2008 Portrait SoftwareStrictly Confidentialpage 12 Sure Things Act whether you treat or not © copyright Portrait Software A 2B 3 Persuadables Only act if treated Sleeping Dogs Act only if not treated 2 No impactPositive impact Negative impact 123 Incremental Impact for Retention Lost Causes Will not act, even if treated Put this money back into your marketing budget

13 © 2008 Portrait SoftwareStrictly Confidentialpage 13 Uplift Optimizer 5.3 Themes Increased Efficiency –Removed multiply-up stage –Performance enhancements for wide foci –Support implied case-weighting Improved Usability –Better diagnostic reports (navigation, heat-maps, summaries) –Integrated with Analytics 5.3, updated documentation –Added progress reporting, better system-wide defaults SAS Integration –Drive uplift modeling & reporting from SAS scripts –Deliver uplift models as SAS code, reports as SAS data –Read and write SAS datasets as always General Availability: 3 November 2008 ( Rollout to all customers coordinated by Portrait Support)

14 © 2008 Portrait SoftwareStrictly Confidentialpage 14 Demonstration

15 © 2008 Portrait SoftwareStrictly Confidentialpage 15 Uplift Optimizer Futures Themes: –Business-user focus: vs. SAS user (Excel reporting, financial forecasting, what-if analysis) –Enhanced automation: fire & forget (uplift assessment, better parameter search, recommend best model) –Intelligent targeting for outbound Self-arbitrating response vs. uplift analysis Web-based Simple wizard-style interface Integrated with PCM Estimated availability: early 2009

16 © 2008 Portrait SoftwareStrictly Confidentialpage 16 Customer Case Studies Cross-sell HELOC to existing customer base via direct mail Campaign ROI increased over 5 times previous campaigns (75% to 400%) Incremental revenue increased 327% Business Goals ROI Churn Reduced Net $$ Increased Best 60% of targets generate >$500K of incremental revenue Reduced baseline cost from lower volume More incremental response by avoiding negative effects (downlift)

17 © 2008 Portrait SoftwareStrictly Confidentialpage 17 Customer Case Studies Deliver next generation targeting for customer retention (churn) campaigns Removing negative effects thus decreasing both churn and campaign costs Campaign ROI increased over 11 times previous campaigns Churn rate decreases by an additional 36% over traditional approach Traditional targeting reduced churn by 5% (from 23% to 18%) But significant negative effects observed Uplift model reduced these significantly Saving 40% of treatment costs Further reducing churn to 6.8% Business Goals ROI Introduction of first prediction model Introduction of refined prediction model months annual defection rate Churn Reduced

18 © 2008 Portrait SoftwareStrictly Confidentialpage 18 A Next Generation Marketing Solution Slash marketing costs while boosting revenue and retention Reduce customer ad fatigue Eliminate the negative impact of marketing Perfect for both inbound and outbound marketing Proven - power to extend any analytics environment The only packaged solution of its kind Your Organization’s New Competitive Advantage

19 © 2008 Portrait SoftwareStrictly Confidentialpage 19 Where to find out more … Uplift Optimizer Support website: Documentation –What’s new in the Uplift Optimizer release notes –Updated Uplift Optimizer help Uplift Optimizer Support –Web Site: –Tel: US ; All

20 © 2008 Portrait SoftwareStrictly Confidentialpage 20 Europe (Headquarters) The Smith Centre, The Fairmile Henley-on-Thames, Oxfordshire, RG9 6AB, United Kingdom T: +44 (0) F: +44 (0) Americas 125 Summer Street 16 th Floor Boston MA 02110, USA T: F: Edinburgh 39 Melville Street Edinburgh EH3 7JF, United Kingdom T: +44 (0) F: +44 (0) Asia Pacific Level Young Street Sydney NSW 2000 Australia F: Oslo Maridalsveien 87, Bygg Oslo Norway T: F: Questions?

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