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As Consumers Evolve, Retail Analytics Advance

As Consumers Evolve, Retail Analytics Advance. Today’s Panel. Jon Quinn Vice President, Marketing Strategy, Safeway. Adam Holyk Group Vice President, Insights and Analytics, Walgreens.

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As Consumers Evolve, Retail Analytics Advance

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  1. As Consumers Evolve,Retail Analytics Advance

  2. Today’s Panel Jon QuinnVice President, Marketing Strategy, Safeway Adam HolykGroup Vice President, Insights and Analytics, Walgreens Ravi DharGeorge Rogers Clark Professor of Management and Marketing, Yale School of Management & Director, Center for Customer Insights

  3. Complex Dynamics impact Retail Analytics CHANGING SHOPPERS • INTENSIFYING COMPETITION TECHNOLOGY • RETAILER • ECONOMICS

  4. Retailers Are providing Shoppers more Access

  5. Technology is creating price transparency

  6. Technological cherry picking

  7. shoppers might know more than you do

  8. Pricing

  9. Which items to carry? Simple outcomes, complex analytics • In which stores? • How much Promo Support? • At What Price?

  10. the winning analytic strategy • GET THE RIGHT INSIGHTS • ORGANIZE TO WIN • EXECUTE WITH GREATER PRECISION

  11. The right shopper insights Buyers will not pay for value that they do not perceive, no matter how real it may be. • REQUIRED INSIGHTS: • What they do, inside & outside the box • What they perceive & believe Prof. Michael Porter – Competitive Advantage PERCEPTION OF VALUE DRIVESRESPONSE TO PRICING

  12. Insights to both behavior and beliefs 59% 36% 25% Fresh produce Everyday low prices 1 your share of their All Outlet spend ….they drive most of your dollars Fresh produce Grocery selection of your shoppers are “core”… 2 Well stocked Fresh meat & seafood 3 Prices well labeled Prepared foods 4 Store brand Grocery selection 5 …but they aren’t very loyal One-stop shopping Clean store 6 WHAT SHOPPERS SAID: WHAT SHOPPERS DID: Well stocked Fresh meat & seafood 7 Nearby location 8

  13. The right competitive insights Yoplait 6 ounce Client 3: $0.75 STRATEGY ACTUAL VS. ASSUMED COMPETITORS PRICE POSITIONING

  14. Eyes on the prize, size of the prize OPPORTUNITY $900M 25% • 8MM Elasticity Estimates 10% Also Highly Elastic “Overpriced” 80MM Competitive Price Points

  15. Discussion

  16. Assortment

  17. Why Assortment isn’t easy 328 16,897 4,932 • Items selling in Grocery weekly average • Items selling in Drug weekly average Average # of unique UPCs per household purchased in Grocery Channel in a year Can’t profitably be all things to all people Hyper-local assortment impacts supply chain efficiency Assortment is “slower” than pricing, just as important

  18. All demand is local Water Infant Nutrition Frozen Pizza Growing MTA’s: 3,519 Growing MTA’s: 2,414 Growing MTA’s: 659 CHANGE IN DOLLARS DECLINING GROWING STABLE Growing: > 2% $ growth; Stable >-2% and < +2%, Declining > -2% Source: Nielsen Scan and Panel Data, Nielsen Analysis

  19. SIMPLE FRAMEWORKS ENCOURAGE ACTION • RATIONALIZE • Make sure you have the best items in distribution • DEVELOP • Increase Items FAST AVG SALES RATE DISTRIBUTION (# ITEMS) • SQUEEZE • De-list worst performers • NURTURE • Review Slow movers for de-listment SLOW NEGATIVE • CONSUMER RESPONSE TO ASSORTMENT (INCREMENTALITY) • POSITIVE

  20. Locally relevant decisions, at enterprise scale Super- Premium Segment Value Segment Assortment Response:Total Category Assortment Response:Total Category

  21. Right products, right places 4.9% Laundry 4.5% 0.3% Laundry Sales ($MM) Source: Nielsen AssortMan, TUS Mass, 52 weeks ending 10/13/12

  22. Discussion

  23. Table talk Questions • With the evolution of smart phones and information access, how do you see your analytical needs changing? • As a Manufacturer or a retailer, what would you change about collaboration to address these analytical needs? • What are the industry challenges for analytic strategy and capacity keeping up with the rate of change in the industry, e.g. personalization and dynamic pricing?

  24. THANK YOU

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