Intelligent Personalized Marketing_IIR USA_Shoppers Insights_fractal analytics

® Intelligent Customer Targeting to drive Engagement and ROI Shopper’s Insights in Action July 19, 2012Proprietary Information of Fractal Analytics Inc.This document contains proprietary and confidential information of Fractal Analytics and subsidiaries (Fractal) and shall not be reproduced or transferred to other documents,disclosed to others or used for any purpose other than that for which it is furnished, without the prior written consent of Fractal. It shall be returned to Fractal upon request.

® Trivia Question #1 Estimate the highest number of emails sent from one company to a person during 2011? A. Less than100 emails B. 101-200 emails C. 201-400 emails D. 401-600 emails E. More than 600 emailsConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 2

® Personalized Marketing: Good and the Bad* The Good News: Online sales through email grew from 10% to 17%. But Silver lining  Some retailers are finding that sending fewer emails can pay off.  Since cutting volume, Nicole Miller has seen the rate at which customers "unsubscribe” drop, and the percentage of recipients who open the emails has grown from 15% to 40%, “Stores Smarten up Amid Spam Flood”, Wall Street Journal 09 March,2012Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 4

® Key Premises We all can agree that:  Companies want to build lasting relationships with their customers.  Customers want to shop with Companies that respond to their needs in a relevant mannerConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 5

® Presentation Focus  Consumer & Company Perspectives  Customer-Centric Marketing: Size of the Prize  Customer-Centric Marketing: Key Challenges  Customer-Centric Marketing: Case Study in Targeted InteractionsConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 6

® Consumers are Sophisticated and Demanding Shopping Needs Shopping Channels  Personalized Marketing Store  Great Experience Catalog  Seamless Search Web/E-mail  Response to Feedback Kiosk  Trusted Relationship  Recognized & Call center Rewarded MobileConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 7

® Company Perspective: CMO Priorities  A recent CMO study* identified three issues that dominate the CMO agenda. 1. Deliver value to empowered Customers 2. Foster lasting connections with these customers and 3. Capture the value delivered and measure the results  Appear to be focusing on the right issues.  But do they “walk the talk”? * Insights from the Global Chief Marketing Officer Study, 2011Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 8

® CMO Priorities: “Walk the Talk”?  Apparently yes.  Another recent CMO survey*, reported that firms expect the marketing analytics portion of their total marketing budget to grow from 5.7% to 9.1% over the next three years. A 60% increase!  Over the last 2 years the overall marketing budgets have just increased 8.3%!  Clearly, companies have finally woken up to the fact that marketing analytics do matter and have backed this goal with the increased budgets * The CMO Survey.Org, Feb 2012Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 9

® Trivia Question #2 Your best guess about the returns from smarter marketing A. Below 0.49% of revenue B. 0.50% - 0.99% of revenue C. 1.0% - 3.5% of revenue D. Over 3.5% of revenueConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 12

® The Size of the Prize 1% - 3.5% of Revenue! Delivering a unique shopping experience enables retailers to deliver a smarter shopping experience and impressive ROIs* Integrated Customer Information 0.1% - 0.4% of revenue Prescriptive Insights 0.2% - 0.7% of revenue Precision Targeting 0.1% - 0.4% of revenue Relevant Experience 0.3% - 1.3% of revenue Continuous Dialogue 0.2% - 0.7% of revenue “Smarter Shopping Value Quantification.” IBM Center for Applied Insights and the IBM Global Retail Industry. October 2011Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 13

® The Size of the Prize Revenue Impact for Typical Soft Line Retail $236M-$873M typical $25B soft line retailer “Smarter Shopping Value Quantification.” IBM Center for Applied Insights and the IBM Global Retail Industry. October 2011Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 14

® Challenges Bridging the Customer-Company Relationships 1. Data gaps that inhibit the creation of actionable insights 2. Tools and technology challenges that impede the creation and deployment of insights 3. Gaps in the creation of actionable Insights 4. Challenges in measuring the business impact of insightsConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 16

® Data and Technology Challenges  Collect relevant data?  Process for collecting data customer friendly?  Plumbing for making the collected data available for analyses and campaigns?  Tools and technology support?Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 17

® Trivia Question #3  Your best guess about % who use analytics for marketing decision making A. Under 10% B. 11% - 20% C. 21% - 40% D. 41% - 60% E. More than 60%Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 18

® Reasons for Limited Analytics Usage  Leadership may not value the of use insights  Lack of an organizational culture around measurement and insights.  Results confirm what is already known and do not add any new valueConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 20

® Flavors of Marketing Insights*  Three types of marketing insights with varying business impact Evaluative Operational Focus Insights “what happened” Marketing Instrumental Execution Focus Insights Insights “smarter execution” Conceptual Strategic Focus Insights “mind changer”  Likely that the evaluative insights (reporting based) are the norm today  Important to understand the relationship among these * Prof. C Moorman, Duke University , Feb 2012Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 21

® Insight Flavors: Relationship Campaign 1 Campaign 2 Game changing insights = ability to connect the dots from multiple sources. These insights Influence and change managerial beliefs Similar to Strategic Intuition Evaluative Instrumental Conceptual Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 22

® Measurement Challenges  Campaign designed to facilitate learnings?  Agreed upon approach to define success?  Collect relevant response data?  Leading or lagging metrics?Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 23

® Approaches to Address these Challenges Intelligent Business Interactions Impact Next Logical Product Market Basket Analyses SophisticationConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 25

® Case Study: The Retailer Context  National retailer with over 3,000 stores  Multiple product lines - hard-lines & soft-lines  Large loyalty program  Multiple channels - POS, email, online, in-store, etc.  Challenges  Improve shopping frequency  Increase spend  Enhance shopping experienceConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 26

®Customer DNA Markers Form the Foundation forTargeted Interactions Spend Very High High Medium Low Very Low Trips Very High High Medium Low Very Low Recency Very High High Medium Low Very Low Brand Loyalty Index Very High High Medium Low Very Low Promotion Sensitive Very High High Medium Low Very Low Price Sensitive Very High High Medium Low Very Low Web Activity Very High High Medium Low Very Low Attrition Probability Very High High Medium Low Very Low Fashion Expert Very High High Medium Low Very Low Pet Owner Dog Cat Others None Sports Interest Football Basketball Soccer Baseball Golf Offer Interest Apparel Footwear Electronics Gardening Lifestage Single Married With Kids Shopping Mission Stock Up New Home Purchase YesConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 28

® Use Available Data from Multiple Sources to Create Customer DNA Markers Appended Derived Data Data • 3rd Party Appended Data • Product Propensities • Demographics • Segmentation • Consumer Interest Customer • Monetary DNA • Meta Data Markers Self Stated Observed Data Data • Shopper Surveys • In store/Online Transaction • Shopper Sweepstakes • Online BrowsingConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 29

® Customers with Similar RFM Metrics Possibly Very Different DNA Markers Shopper Profiles Recency Visited last week Visited last week Visited last weekSimilarRFM Frequency Twice a month Twice a month Twice a monthmetrics Monetary Spends more than $150 Spends more than $ 150 Spends more than $150 per month per month per month Hobby Automotive Work / Home Improvement, Wood Working Mechanics Furnishing DecoratingVerydifferent Buying Pattern Buys items on Buys expensive items Buys items he need promotion irrespective of the priceDNA Spends more on Auto and Fitness Apparel and Home Tools and Kids Appliancesmarkers Shops mostly on Saturday Sunday Weekdays Customer DNA markers offer greater opportunities for granular targeting compared to traditional targeting techniques (eg. using RFM based segmentations) Confidential | Copyright © 2011-2012 Fractal Analytics, Inc. 30

®Test and Learn Framework Identifies and TunesBest Offers Track the campaign performance for all campaigns using test and control methodology Performance Metrics: response rate, revenue earned Test and Control Method Control Set No Campaign (5%-10% Target % Response A Executed Group) Total Target Incremental Customers Response Test Set (B – A) Campaign % Response B (Rest of Target Group) Executed Why do A/B Testing? What can be tested? How to do A/B testing?  To test the  The headline  Plan what you want to test. (E.g. Headline) effectiveness of  Calling Script  A: Choose a free gift of your choice marketing efforts  Product description  B: Guaranteed FREE gift of your choice  It improves the  Graphics  Divide the sample set into two groups (A and B) campaign ROI  Location of Call to  The Test is monitored over the campaign period action  Colors  Response for each is measured  The effective one is used in futureConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 31

®Optimized Campaign Management Capability Overall Marketing Constraints Per Campaign Constraints  Overall Budget  Minimum Offers  Campaign Sequencing  Maximum Offers  # of Campaigns/Quarter  Maximum Total Offer Cost  Offer Response Rates  Concurrent Offers  Outbound Band Width  Max # of campaigns per  Geographical Presence customer  Response per Campaign  Max # of equivalent offers  Max # offers per time interval Channel Constraints Customer level ConstraintsConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 32

® Conclusion  Intelligent customer-centric personalized marketing is imperative in today’s competitive and demanding environment – the returns are worth the effort!  Implementing this vision is at the intersection of :  Harnessing the power of big data  Relevant tools and technology  Deriving deep customer insights  Intelligent deployment of insights  Data-driven test and learn culture  Well-defined and measured success metricsConfidential | Copyright © 2011-2012 Fractal Analytics, Inc. 33

®We believe analytics is critical to deeply connect with consumers, earn customer loyalty, make better decisions toreduce waste, and ultimately improve lives.Fortune 500 companies partner with Fractal to build breakthrough analytic solutions, set up analytical centers ofexcellence, and create a culture of data driven decisioning.We solve problems, operationalize solutions to drive results, and ultimately drive change in organizations towards fact-based decisioning.We help businesses: (a) Understand, predict and influence consumer behavior; (b) Improve marketing, pricing, supplychain, risk and claims management; (c) Harmonize data, visualize information, build dashboards and forecastbusiness performance. For further details contact:www.fractalanalytics.com Hari S. HariharanUnited States | United Kingdom | Singapore | India | UAE +1 608 338 4393 harih@fractalanalytics.com pcosd.1211.1

Intelligent Personalized Marketing_IIR USA_Shoppers Insights_fractal analytics

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