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Merkle - iStrategy Chicago
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Merkle - iStrategy Chicago

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Digital Marketing at iStrategy

Digital Marketing at iStrategy

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  • Names – Absolute IdentificationFaces – Emotive, influential and more of an ID than even the name. Milan Kundera, with the unrepeatable combination of features, “The serial number of the human specimen is the face.”Friends – Story of how value social graph is. 1) VC story, will always retain the social graph. 2) Friend’s age is extremely high predictor of your age 96% confidence level.
  • Names – Absolute IdentificationFaces – Emotive, influential and more of an ID than even the name. Milan Kundera, with the unrepeatable combination of features, “The serial number of the human specimen is the face.”Friends – Story of how value social graph is. 1) VC story, will always retain the social graph. 2) Friend’s age is extremely high predictor of your age 96% confidence level.
  • Transcript

    • 1. A Case for Social Commerce:Driving ROI through Social Graph Data
    • 2. Agenda• Open Graph Primer: Explicit Social Truths• Case Study: 1-800-Flowers.com 22
    • 3. Open Graph Primer:Explicit Social Truths
    • 4. What is possible at the convergence? • “Re-Imagination of Nearly Everything” APIs (Platforms) “Connected UX Data” (CRM) (Beauty) *Mary Meeker Internet Trends Report
    • 5. Companies re-imagining everything.
    • 6. Have a distinctly social and personalized feel.
    • 7. Personalization has been around for awhile. • So what has social brought?
    • 8. 3 explicit social truths. • Names • Faces • Friends
    • 9. Examples of Onsite Social Personalization: Travel
    • 10. Examples of Onsite Social Personalization: Rentals
    • 11. Examples of Onsite Social Personalization: Media
    • 12. Examples of Onsite Social Personalization: Media
    • 13. Examples of Onsite Social Personalization: Cause
    • 14. Examples of Onsite Social Personalization: Cause
    • 15. Examples of Onsite Social Personalization: Cause • More than $300 million dollars pledged • Over 30,000 successfully funded projects.
    • 16. Examples of Email Social Personalization Friends’ recent activity with Subject line customized commerce call to action with friends’ names 16 16
    • 17. Examples of Onsite Social Personalization: Retail
    • 18. Names, Faces and Friends are made possible by: Facebook’s Open Graph
    • 19. Big Channel• Why you Like the Open Graph.
    • 20. Big Data• Why you also Like the Open Graph.
    • 21. Actionable Move from broad conversation and sentiment analytics to more actionable customer level social data and analytics.
    • 22. First Wave of Social... • Push phenomena
    • 23. Second Wave… Existentialist…• Pull phenomena
    • 24. Social Graph Data Leveraging social graph data, product adoption can increase by up to 400%.
    • 25. FB Historical Recap 2007 2010 2012 FB Platform FB Open Graph FBX Ad Release Release Exchange Social Strategies Earned Facebook Open Graph Paid Media Media / Apps Commerce Leverage apps, In News Feed Customer’s Facebook polls, posts to Purchasing, fan Facebook network Retargeting, Spon engage audience page commerce utilized across sored Stories on Facebook Page media channels 25
    • 26. Moving Forward… 2012 and Beyond Social Strategies Earned Media Open Graph Paid Media   Leverage Customer’s Facebook apps, polls, posts Facebook network Retargeting, Spon to engage  utilized across sored Stories audience on media channels Facebook Page 26
    • 27. Case Study:1-800-Flowers.com
    • 28. Smiles design and delivered.• 1-800-Flowers.com is actually in the business of delivering smiles. = 28
    • 29. Justin Bieber Deluxe Totebag.• Social connections – between friends, couples, coworkers – drive gift giving in all its forms… 29
    • 30. Case StudyBackground: 1-800-Flowers.com was underwhelmed by Facebook Marketing results. They scaled their Facebook page to hundreds of thousands of Likes, built and deployed apps on their fan page and executed Facebook paid media. All with minimal impact on sales. They expected more.Solution:• Social Graph data capture through Social Emails• Social Graph data capture through Social Sign On• Social and CRM audience linking to power hyper-targeted Facebook Media• Integrate Customer’s Facebook Network into the Shopping Experience 30
    • 31. Process: Creating Connections1800Flowers.com 1800Flowers.com Customers Site or Email Customer Friends• Onsite Social App • Likes and Interests • Common Likes• Connection Experience • Demographics • Close friends• Value Exchange • Product Likes • Influencers • Shares and Comments• Audience • Activation • Amplification 31
    • 32. Sample Flow - Social EmailsHTML Snippet in emails • Ongoing messagingpower Social Graph Data • CRM support &Capture integration • Fair value-exchange to capture social crm profile • A/B test permissions
    • 33. 1 Authentication ≈ 250 Social CRM User Profiles • FB Permissioning Social: • Gender: Male • Age: 28 • Location: Chicago • Brand Likes: ESPN, Adidas, Canon, Nike • Likes & Interests: Football, basketball, running, Chicago Bears • Friends: Photos, Number of Friends, Names, Birthday • Open Graph Likes: Jeans, Shoes, Apparel CRM: • Email: High Email Engager • Customer Segment: High Value 33
    • 34. ResultsChallenge:Integrate connected-userinsights into email programto drive higher engagementand incremental salesSolution:Social Email integration &personalization Results: Social Email drove 10X higher consumer engagement than standard product based newsletters 34
    • 35. Social Sign On Social Sign On widget for newsletter sign up
    • 36. Facebook UIDs and Lookalike Targeting Valuable Facebook user and friend profile data collected by Social Amp UIDs All your open graph data High Value Social • UID Consumer • Lookalike • Likes H&M retargeting • 24 years old • Influencer targeting • NYC • Map to • 400-500 friends transactions/ROI • Single • High LTV Facebook Clusters Facebook Sponsored Stories and Marketplace Ads
    • 37. Analytics Use Cases (non-CRM enabled) Social Analytics (non-CRM enabled) • Social Audience Profiling • Demographics (age, gender, location etc.) • Social Audience Segmentation (e.g. Fitness Fanatics, Skiers, Traveling Socialites) • Competitive Brand Analysis • Social Funnel Analysis • Frequency / recency of product or comparable product liked by user • Type of engagement on comparable products (like, want, “OG” verb)
    • 38. Analytics Use Cases (CRM enabled) Social Analytics Tier (CRM enabled) • Influence analysis • Based on friends of users who have purchased or liked after the user • Profile analysis of influencers (demo, interests, activities) • Social CRM Analysis • Customer analysis overlaying social segments (e.g. Fitness Fanatics, Skiers, Traveling Socialites) with purchase history and loyalty • Social Profile analysis of high value or LTV audience segments (demo, interests, activities)
    • 39. Lesson 1: Don’t Treat Social in a Silo 90% of the data that exists in the world It is projected that the amount of data has been created in the past 2 years we create will grow by 40% each year Availability Voice/ video Petabytes Social Knowledge data gap Web log Terabytes data Volume Email and text data Gigabytes CRM and enhanced data Usability Megabytes Media data Transactions 39
    • 40. Lesson 2: Plan for the Future State of CRM 40
    • 41. Lesson 3: Trial Sponsored Stories1 Kristen loves or 3 Gianna loves and/or reviews a product buys… integrated with Open Paid Media amplifies Graph app on VS.com the action once more. 1 action ≈ 250 unique FB sponsored stories Paid Media to amplify action to friends and friends of friends 2 Gianna sees Kristen’s action on Facebook as sponsored media 41