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"Big Data Marketing: Who's Doing it Right" by Stephan Sorger at the 2014 imarketingSF Conference


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Stephan Sorger

Professor, Hult; Author; On Demand Advisors

What exactly is big data? How can I use it in my marketing efforts? What kind of results can I expect from it? Can you point me to examples of companies who are doing it right? Join us for this informative session, where we cover best practices for big data marketing by showcasing companies who are doing it right—companies such as Amazon, Birchbox, eBay, Netflix and Rent the Runway. For example, Rent the Runway’s marketing department launched a new upsell program on its website when customer analytics data showed that 25% of its customers added accessories to their orders for designer dresses. The company also found that women who viewed photos of dresses on real women were 200% more likely to rent than those who viewed dresses on models. You will take away key learnings that you can immediately apply at work and become a hero through big data.

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"Big Data Marketing: Who's Doing it Right" by Stephan Sorger at the 2014 imarketingSF Conference

  1. 1. Big Data Marketing: Who’s Doing It Right? imarketingSF Conference 2014 November 5, 2014 Stephan Sorger © Stephan Sorger 2014
  2. 2. About Our Speaker The “Analytics Ambassador” Author “Marketing Analytics: Strategic Models and Metrics” Professional Expertise Oracle, SAP, Aspect, On Demand Advisors Academic Expertise Hult; UC Berkeley SF Ext; USF MBA Board Member UC Berkeley Ext. Marketing Metrics; Demand Metric Books; Sample course content © Stephan Sorger 2014
  3. 3. New Book: Marketing Analytics: Strategic Models and Metrics Authoritative Guide • Over 10 years of professional experience • Over 5 years of academic research Comprehensive • Nearly 500 pages of text • Nearly 400 figures, tables, and graphs Practical • Structured around marketing, not math • Packed with examples Available on • Search on “Marketing Analytics” © Stephan Sorger 2014
  5. 5. On Demand Advisors: Clients Learn more at: © Stephan Sorger 2014
  6. 6. UC Berkeley Extension: Corporate Training UC Berkeley Extension Corporate & Professional Programs Accelerated, In-Depth Intensives: • Principles of Effective Leadership • Coaching & Mentoring for Leaders • Change Management • Forecasting & Budgeting • Accelerating Innovation Learn More at: Or contact Robert David at: © Stephan Sorger 2014
  7. 7. The Problem Promises Results © Stephan Sorger 2014
  8. 8. Example: Tracking the Wrong Metrics McDonald’s Campaign 2010 Track Foursquare Check-Ins! Social Media Camp No, Track Foot Traffic! You’re Both Wrong! Track Incremental Revenue! Traditional Media Camp CEO © Stephan Sorger 2014
  9. 9. We Need a Hero! © Stephan Sorger 2014
  10. 10. Who’s Doing it Right? Birchbox eBay Rent the Runway Walmart “Data Exhaust” © Stephan Sorger 2014
  11. 11. Creating Relationships Using Data Neil Lindsay, VP Marketing • CMO Council; North America Advisory Board Internal Analytics: Leveraging data to drive cross-sell • Real-time; Market-driven; User-specific • Enhanced customer experience; Reduced marketing expenses © Stephan Sorger 2014
  12. 12. Cross-Platform Analytics Service A/B Testing Built-In • Test Different Features Cross-Platform • Apple iOS • Android • Amazon Fire External Analytics: Developers selling on Amazon Appstore Continued Use “Sticky” Average Revenue Per Device (ARPD) Average Revenue Per Paying Device (ARPD) © Stephan Sorger 2014
  13. 13. Amazon Analytics Product External Analytics: Sales of Amazon Page Data Relevant Metrics • Reach • Views • Considerations • Sales Features • Video Hero • Product Hero • Merchandising Widget Featured products.. Featured links… © Stephan Sorger 2014
  14. 14. Birchbox: Dedicated to Data Deena Bahri, VP of Marketing • Dedicated to Data for company decisions • Tailor to various complexions and hair types “From the beginning, data has been an essential part of Birchbox’s growth and strategy…we use it to make important company decisions, and use it to guide us towards creating the best possible new products for our customers.” - Deena Bahri, VP of Birchbox © Stephan Sorger 2014
  15. 15. Birchbox: Birchbox Man Based on Survey Data Birchbox Man • Survey data + behavioral data indicated demand for products for males • Nov. 2011: Limited Edition Birchbox Man • April 2012: Dedicated subscription delivery © Stephan Sorger 2014
  16. 16. eBay: Data-Driven Revamp Richelle Parham, CMO • Formerly with Visa and Digitas; 2013 Marketing News Hall of Femme Big Data • 110+ Million users; 350+ Million items © Stephan Sorger 2014
  17. 17. eBay: The Feed The Feed • Highlights items based on customer behavior • Tracks data on browsing and purchasing history • Consumers can “follow” categories of items © Stephan Sorger 2014
  18. 18. eBay: Mapping The Customer Journey “In designing the Feed, we mapped out the customer journey toward a purchase, from the moment he’s aware of a product to how he researches it and then decides to buy it.” - Richelle Parham, CMO of eBay © Stephan Sorger 2014
  19. 19. eBay: Curation “We found the number one thing customers care about is curation. We also learned that big, rich photos really matter. That’s why the Feed is all about creating a visual environment of the things you love.” - Richelle Parham, CMO of eBay © Stephan Sorger 2014
  20. 20. Rent the Runway: Data-Driven Decisions Jenn Hyman, CEO • Dedicated to Data for major decisions • Data: Marketing; Operations; Inventory © Stephan Sorger 2014
  21. 21. Rent the Runway: Impact of Social Media © Stephan Sorger 2014
  22. 22. Rent the Runway: Upsell Accessories • 25% adding accessories to dress orders • RTR launched upsell program on site © Stephan Sorger 2014
  23. 23. Rent the Runway “Find Women Like Me” 200% more likely to rent when dresses worn by “real women” (vs. model) © Stephan Sorger 2014
  24. 24. Walmart: Embracing the Digital World Stephen Quinn, CMO • Dedicated to embracing the digital world • Goal to become more entrepreneurial © Stephan Sorger 2014
  25. 25. Walmart: Walmart Labs SoLoMo Initiative • Social, Local, and Mobile • 2,500 Walmart Facebook pages Acquisitions • Grabble: eReceipt • Inkiru: Predictive intelligence platform • Kosmix: Social media technology platform • OneRiot: Social media analysis • Stylr: Clothes shopping mobile app • Vudu: Streaming video service • Yumprint: Meal planning service provider • Others © Stephan Sorger 2014
  26. 26. Walmart: Polaris Search Engine Polaris Search Engine • Type in “Patio Furniture” • Returns page with multiple patio set options © Stephan Sorger 2014
  27. 27. Walmart: Polaris Search Engine Polaris Search Engine • Uses semantic search algorithms to understand what users search for • 10-15% increase in shoppers completing purchase after searching for a product • Sri Subramaniam, head of Polaris initiative • Built from scratch; Completed in 10 months • Based on Social Genome project • Connects people to places, events, and products • Applies synonym mining to glean intent © Stephan Sorger 2014
  28. 28. Data Exhaust: Combine Leasing Combine Harvester • Combine Harvester: Reaps, threshes, and winnows grain crops • Farmer’s most expensive piece of equipment • Sits idle most of the year © Stephan Sorger 2014
  29. 29. Data Exhaust: Combine Leasing Combine Leasing • Lease combines to farmers • As harvest moves across North America, so does the equipment • Companies: AgcoCorp, Olsen Custom Farms, MachineryLink, … © Stephan Sorger 2014
  30. 30. Combine Leasing: Data Collection Sophisticated Data Collection • Dashboard collects reams of data about the equipment and the harvest • Examples: Fuel consumed; Soil moisture; Elevation of field; Bushels per acre © Stephan Sorger 2014
  31. 31. Combine Leasing: Data Monetization • Use data samples to predict harvest metrics • Timeliness of data: Get sample data in mid-harvest • Customers for data: Goldman Sachs commodity brokers; Wheat futures, etc. © Stephan Sorger 2014
  32. 32. 3 Actions You Can Take 1. Look Around 2. Understand What’s Important 3. BE A HERO! © Stephan Sorger 2014
  33. 33. Questions
  34. 34. Thank You!