Big data from various sources provides insights into consumer spending trends from the macro to micro level. Understanding these trends is key to making effective marketing decisions in today's competitive environment. A full wallet, 360 degree view of customers that includes transaction data provides a more complete picture of consumer behavior compared to traditional models relying on demographics and in-store spend alone. This comprehensive view of customers, markets, competition and opportunities can help merchants optimize acquisition, retention and marketing strategies.

2. Information Services for Merchants Enabling decisions at the speed of consumer behavior

3. Looking Inside the Consumer Wallet Key Success Factors for Driving Loyalty in a Competitive Environment Top Themes for Today: Big Data delivers key macro and micro business insights New world realities require new models Full-wallet, 360o view is the key to marketing success Bring it All Together – A Roadmap for Success

4. Big Data Delivers Business Insights

6. Clear understanding of consumer behavior

7. Competitive view at a location level

11. Online Apparel sales are approaching 20% share of Apparel marketSource: MasterCard SpendingPulse September 2011

12. Big Data in Action: Understanding Economic Drivers Example – US Sector Performance Source: MasterCard SpendingPulse September 2011

13. Big Data in Action: Understanding Key Channel Trends Example – Online Sales Online Apparel sales had year-over-year growth of almost 20% in August 2011. Online sales accounted for over 22% of Apparel sales on Tuesdays in August! Online sales only represent 7% of Apparel sales on Saturdays in August. Electronics was marginally above zero growth to halt a two month string of negative growth rates. Source: MasterCard SpendingPulse September 2011

14. Big Data in Action: Monitoring Key Channel TrendsExample: US ecommerce sales shift online Source: MasterCard SpendingPulse September 2011 Online retail sales growth has accelerated in August to almost 17% compared to August 2010.

15. Big Data in Action: Monitoring Key Channel TrendsExample: US Apparel had 16.4% of sales online in 2010 16.7% of Jewelry sales are now occurring online this is up from 12.8% in 2007. Source: MasterCard SpendingPulse September 2011

18. Big Data in Action: Using Trends to Plan Ahead Example - US Daily Total Retail sales during holiday season Source: MasterCard SpendingPulse September 2011

19. Big Data in Action: Using Trends to Plan Ahead Example - US Online daily total retail sales during holiday season Source: MasterCard SpendingPulse September 2011

22. Forecasting reports predict key shopping days for total Apparel by channel.The Opportunity Insight into channel sales and trends pertaining to key shopping days used to inform future marketing initiatives and promotional calendars.

23. New World Requires New Models

25. Proliferation of noise at consumer level

26. More choices and channels than ever

27. More devices (research and buying)

28. New global options

29. More retail options

30. More ways to access (social, etc.)Managed Services Information Services

32. Demographics only takes segmentation so far

33. Survey data is inferred behavior but does not equate with real behaviorSpend with you: $35.44 Spend with you: 3 times per year

35. Near real-time channel trends

36. 360 degree behavioral spend view

37. Competitive performance at a local levelLikely to spend in category in the next 3 months: 4x your average customer Spend with you: $42.17 Total Wallet: $16,273.81 Spend with you: 3 times per year Spend in industry: 19 times per year

39. Purchase Cluster scoring included to enhance insights at the channel level. The Opportunity Merchant’s marketing team can leverage full wallet view to better tailor their marketing messages against retention and acquisition strategies by channel.

40. Whole Wallet, 360o View is the Future

41. Looking Inside the Consumer Wallet Do You Know? US: 6 sectors drive 45% of card spending with Restaurant, Apparel, & Home Improvement ranking as top 3. New York, Chicago, Los Angeles and Philadelphia drove 20% of total retail spending in Q2 2011 (these top 4 drive 26% of Apparel spend). 68% of restaurants guests visited 5 or more restaurant merchants in Q2 2011. Canada is the top cross border country for US based cardholders when purchasing Home Furnishings, Italy is #2. Source: MasterCard anonymized data warehouse 2011

42. Looking Inside the Consumer Wallet Do You Know? Philly is the #4 DMA driving retail sales, ranking ahead of Dallas andSan Francisco Due to the proliferation of restaurants and frequency of visits, 84% of industry customers visited at least 5 different restaurant merchants from July ’10 – June ‘11 International Competition and Opportunity - OutboundUS merchants are competing with the UK for Men’s and Women’s Apparel purchases, but with Canada and Italy for Children’s Apparel and Home Furnishing International Business Coming to the US – InboundSpend has declined marginally year-over-year, but Brazil, being less impacted by global economy, is growing +34% on average across industries Source: MasterCard anonymized data warehouse 2011

43. Track Key Performance Indicators vs. CompetitionIdentify opportunities to focus on customer acquisition or basket size efforts Total Spend Customer Accounts Average Spend Average Transaction Size Average Purchase Frequency Increase Customer Acquisition and/or Average Spend to Drive Total Spend UP Increase Average Transaction Value and/or Average Purchase Frequency to Drive Average Spend UP

44. Discretionary Income and Purchase Behavior Revisiting the thought around the correlation between income and spend Customer “A” % Total Spend Allocated to Discretionary Spend Traditional View Total Income = Traditional Behavioral view= New Approach Customer “B” % Total Spend Allocated to Discretionary Spend Discretionary Spend Traditionally: Discretionary Spend = F (Total Income) But: Higher income does not imply different spending preferences Now: Discretionary Spend = F (Actual Consumer Spending Behavior) Because: Discretionary spend in relation to total spend can reveal general spending preferences irrespective of other allocation of income (i.e. savings)

45. Enhanced Targeting & SegmentationMapping the customer journey for more relevant offers, engagement and response Increased Engagement & Sales Purchase Sequence Recency & Frequency Spend Value Recent purchasing behavior and how often customer segment purchases Improve segmentation and lift overall customer engagement by adding another dimension to the equation Optimal time to reach customer segment with offer Customer segment average transaction size Purchase Sequence Purchase with You Where else are they engaged and how can this be leveraged? What up-sell/cross-sell opportunities exists?

47. Use transaction data insight to identify strong shopping days for targeted offers

48. Leverage transaction data insight to identify shopping behavior outside your store for high-value customers Lift from addition of near real-time transaction data CUSTOMER VALUE In-store, demographic and survey data CUSTOMER LIFE CYCLE ACQUISITION GROWTH & RETENTION

53. Impact on spending across merchant locations over time

54. Correlation between new location cannibalization and proximity measuresThe Opportunity Creation of more stringent site selection guidelines around the proximity of new stores vs. existing ones.

56. Spending outside the merchant franchise that could fuel customer development strategies company-wide The Opportunity Provide a clearer understanding of purchasing dynamics across high value customer segments

62. Information Services Product SuiteTools, that range from macro to micro insights, to address your business challenges Insights My Industry: Understand sector trends and outlook My Markets: Measure competition and identify specific market challenges/opportunities My Segments: Reveal customer loyalty trends and spending behaviors My Customers: Improve customer acquisition and retention marketing Spending Pulse Benchmark Analytics Merchant Need Product Customer Analytics Customer File Enhancement; Acquisition Targeting Actions

63. Andrew_Mantis@MasterCard.com