1. Young-Bean Song AnalyticsDNA September 18, 1015

8. “Every two days now we create as much information as we did from the dawn of civilization up until 2003 ” – Eric Schmidt

12. From chaos to something useful… Display AdVideo AdSearchSocialEmail Brand web site Physical StorePurchase $88 $134 $48 $32 $0 $64 Real-time Analytics ROI Value Ecommerce store Target Customers Devices Cookies

13. What we are covering today? Framework for a analytics roadmap Simplify what all this muck means Demystify lots of buzz words and hype Case studies & research

14. Connecting the dots… Define Success Metrics or proxies By customer segments How do I want to see the results Benchmarks What decisions will I make from the outcomes? Methodology Experimental Design Buy-in across organization Prototype Start fast, simple Data Alignment What data do I need? Where can I get it? User level or macro level? How can I use my own data? Start fast, simple Framework for an Analytics Strategy and Roadmap

15. “Hello Mr, Wood…”

16. Pagliacci’s Definition of Success Sales & Profitability Segment by Volume x (Revenue & Profit) Household or business Toppings to infer kids, Day of Week What to do about it? Speed Retention Cross-sell product recommendations

17. How am I going to convince myself and others that Big Data works? Methodology

21. o +10 o in temp 300% more barbeque meat 45% more lettuce 50% more coleslaw 25% fewer sprouts 300% more barbeque meat 45% more lettuce 50% more coleslaw 25% fewer sprouts

22. Where do I get the data and how do I make it all work? Data Alignment

24. How did IKEA do it? 1. Link online surfing to in-store sales 2. Inputs: Onsite Behavior 3. Methodology: Multi-linear regression to predict: In- store sales user level (95% accuracy) 4. Proxy metric that combine: 1. Products added to shopping list 2. Stock availability 3. Local store look ups 4. Ikea product searches 5. Number of products viewed Conversion Metrics How to scale…?? Predictive >> Prescriptive

25. Look-a-like Targeting

26. IKEA Case Study Results Average basket size of exposed was 45% higher than non-exposed Campaign drove 4.6 to 1 ROI YOY performance increase 91% Cost per conversion down by 51%

28. Myth #1 “We need a dashboard” Sorry… rarely helpful

29. Myth #2 “We’ll just outsource it”

30. Myth #4 “This is easy…” External APIs Custom Insight Dashboards Da Media TV Mobile Online Radio Analytics Engine Print Data Collection Demographic Data -Demos -Extended demos Demographic Data -Demos -Extended demos OOH Social Behavioral Data -In-market classification -Online behavior -Offline purchase data Behavioral Data -In-market classification -Online behavior -Offline purchase data Brand-level data Category level data Brand-level data Category level data Economic data - By vertical Economic data - By vertical Hygiene Weight & Balance ETLETL Data Warehouse Measurement and Optimization Sales Proxies Market Factors Advertisi ng Impact Web Services Web Services Report Generator Report Generator Report Distribution Data Mart Data Collection AnalyticsReporting “Over half of the business leaders today, realize they don’t have access to the insights they need to do their job.” - IBM

31. Case Study: How to TED Talk @ 4:10

34. The Biggest Myth in Marketing: “Advertising makes people do what I want time to do…” REALLY GOOD MARKETING Make us feel good, make us laugh, or at least, help us do what we already want to do, easier…

35. Thank You! Young-Bean Song ybsong@analyticsdna.com