1. Andreas Weigend @aweigend www.weigend.com San Francisco, CA 03 May 2010

3. 1990’s: Search - find 2000’s: Social - share 2010’s: Mobile - create 3 Decades of Innovation

4. Social Data Revolution How the Changes (Almost) Everything

5. How do we “utilize” the “community”? Who do we listen to? Who do we co-create with? –Physical friends –Peers (similar properties to you) –Ad hoc (e.g., for car purchase) –Experts (what bestows authority?) Institution? Past action? Reputation/ brand as shortcut to allocate attention Social Data Revolution

6. In the last minute 4,000,000 search queries, 500,000 pieces of content shared on FB, 100,000 product searches on Amazon.com, 40,000 bit.ly urls created, 40,000 tweets sent

7. Who creates data? Data is the digital air in which we breathe How will this data be used? Improve product design, service delivery, relationships How will this data be shared? Every company is a publishing company What (if anything) does it mean to “own” data?

8. 1800’s: Transport energy  Industrial Revolution 1900’s: Transport data  Information Revolution 2000’s: Create and share data  Social Data Revolution

9. privatepublic

10. Blippy: Sharing purchase info

11. Social: Distributed to FB friends Case study: weigend.com/blog

12. Compare FBconnect on blog with traditional contact box (no social element)

13. Connecting Computers

14. Connecting Pages

15. Connecting People

16. Underlying?

17. 2x doubles every 1.5 – 2 years Data

18. The amount of data each person creates doubles every 1.5 … 2 years □ after five years  x 10 □ after ten years  x 100 □ after twenty years  x 10000

20. 1 billion connected flash players

21. 40 billion RFID tags worldwide

22. Pay-as-you-drive car insurance (GPS)

23. 99% DNA overlap

24. Biology: ~100k yrs Time Scales Social Norms: ~10 years Data, Technology: ~1 year

25. Social Data Revolution How the Changes (Almost) Everything

26. Or is information just an excuse for communication? Purpose of communication: to transmit information?

27. 1 billion videos watched yesterday Social Data = Shared Data 7 billion pieces of content shared last month

28. Web 0 Computers Web 1 Pages Web 2 People Data

29. Introduction Data I C2B (Customer-to-Business) II C2C (Customer-to-Customer) III C2W (Customer-to-World) IV Insights v Questions

30. C2B Part I:

31. +1 800-4-SCHWAB

32. Imagine... You knew all the things people here have bought... what would you do? You knew all of their friends You knew their secret desires

33. Discovery Recommendations Decision making

34. Google helps people find stuff …but people want to discover and help with decisions!

35. …based on reviews Amazon.com helps people make decisions…

36. C2B Data Strategy: - Reviews - Purchases, Clicks…

37. Customers who bought this item also bought …

38. Customers who viewed this item also viewed …

39. Customers who viewed this item ultimately bought …

40. … based on clicks and purchases Amazon.com helps people make decisions …

41. … only occasionally punctuated by purchases Process of creating and refining product space awareness… Shopping?

42. How do you know peoples’ secret desires ? Accounting

43. Amazon.com is engineered for feedback

44. Context Geolocation Device Attention Transactions Clicks Intention Search Data Sources

45. Connection data The Social Graph

46. New phone product: How to market? Connection data Who called whom? Traditional segmentation Demographics Loyalty

47. Connection data Traditional segmentation 0.28% Adoption rate 1.35% 4.8x

48. Business Customers

49. C2C Part II:

50. Social Data = Shared Data Knowingly Willingly

51. C2C = Customer-to-Customer Customers share with each other

52. Amazon.com Share the Love

53. Amazing conversion rates since you chose: Content (the item ) Context ( you just bought that item) Connection (you ask Amazon to email your friend ) Conversation (information as excuse for communication)

54. Las 4 C’s del Marketing Contenido Contexto Conexiόn Conversaciόn

58. Blippy: Sharing purchases

59. Social network intelligence

60. Fraud reduction – Provide risk scores

61. Social graph targeting Provide list of prospects

62. Influencer Marketing? Real life vs

63. Market to influential people… … and then reach everyone else for free

64. Real Life Facebook 38% ≥ 4 links 86% ≥ 4 links 1 2 3 4 Chain length

65. C2C = Customer-to-Customer Customers share with each other

66. C2W = Customer-to-World Customers share with the world

67. C2W Part III:

69. Amazon.com: Public sharing of interests

71. Consumers - Engage - Share - Connect 3 times per week

72. “We are not in the business of keeping the media companies alive.” “We are in the business of connecting with consumers.” Trevor Edwards Nike Corporate Vice President for Brand and Category Management Q: Or rather in the business of facilitating consumers to connect with each other?

74. Search tweets Create tweets Follow users

75. http://www.mrtweet.com

76. The Illusion of an Audience

80. Insights Part IV:

81. + wheels + heels = =

82. Product Customer Brand

83. From controlled production for the masses… … to uncontrolled production by the masses

84. Web 0 Computers Web 1 Pages Web 2 People Data

89. Shift in Customer Expectations People trust reviews and comments by others more than marketing messages People use their friends’ attention to filter information and to discover new things =

90. Social filter

91. Travel

97. Rooms to Avoid: 01, 21 08, 17 Rooms Ending in: Possible Ice Machine / Elevator Noise Limited View Rooms Corner / Oversized Rooms: 04 24 Oversized, Corner Room, Quiet Room Oversized, Corner Room with North Times Square Views (Higher Floors are Preferred Rooms Ending in:

100. Travelers share their intentions to highlight where you’ve been, to show where you’ve lived, to share where you want to go. Export your travel map to any Web page. Edit your map once Including your Facebook and MySpace profiles and blogs to automatically update your exported maps everywhere Sign in to export your map if you’re already a VirtualTourist member. Click

107. Questions Part V:

108. Data creation and sharing Consumer expectations Innovation methodology Marketing in SDR The 4 C's of marketing E-business  Me-business  We-business Monetization

109. Who creates data? Data is the digital air in which we breathe How will this data be used? Improve product design, service delivery, relationships How will this data be shared? Every company is a publishing company What (if anything) does it mean to “own” data?

110. How have consumer expectations changed towards creating, sharing, accessing, and controlling data, especially in the financial area? What benefits will customers expect in exchange to giving Intuit permission to use their data? Ultimately, how can Intuit help people discover products and services, make better decisions, and subsequently participate in the value its customers create?

111. How should Intuit experiment with C2C platforms for social commerce, such as Facebook? How can Intuit leverage C2W data (Customer-to-World), such as Twitter? Which new data sources and technologies should Intuit pay attention to, e.g., for recommendations?

112. What are the obstacles for Intuit to fully utilize the data of its customers Including consumer choice, purchase decisions, social relations, attitudes and beliefs? How can the limitations of traditional market research be overcome by "instrumenting the world“? I.e., by systems and incentives that enable customers to give feedback to Intuit whenever they want to? How can Intuit marketing leverage the consumer mind shift of the social data revolution?

113. Content Context Connection Conversation

114. Who talks to whom? Consumers to consumers Who trusts whom? Shift from institutions to individuals Who is in control? From e- business (company focus, Web 1.0) to me- business (customer focus, Web 2.0) to we- business (community focus, Web 3.0)

115. Who manages whom? Move from CRM to CMR (Customer Managed Relationships) Who pays whom? Design incentives for participation and interaction Charge as much as you can  Charge as little as you can? Jeff Jarvis Transaction economy  Relationship economy Shoshana Zuboff

116. Innovation Internal  External “Most smart people don’t work here.” Bill Joy Data Collect and analyze  Create and share Experiments Push and prey  Launch and learn

118. Andreas Weigend @aweigend www.weigend.com Q & A

120. http://weigend.com/blog @aweigend

121. How do marketers need to respond to the consumer mind shift? Why do most firms neither capture nor fully utilize data on consumer choice, purchase decisions, social relations, attitudes and beliefs? How can the limitations of traditional market research be overcome by "instrumenting the world", i.e., by systems and incentives that enable customers to give feedback whenever they want to?

122. How should firms use C2C platforms for social commerce, such as Facebook? How can they leverage C2W data (Customer-to-World), such as Twitter? Which of these new data sources and technologies are the most important ones for successful recommender systems?

123. How have consumer expectations changed towards creating, sharing, accessing, and controlling data? In a world where every employee and every customer has become a marketer, what are the platforms, tools, and best practices? And, ultimately, how can companies help people discover products and services, make better decisions, and participate in the value their customers create?

124. OPEN DATA is part of the OPEN FIRST group. Ted Shelton. Noreena Hertz. Doc Searls. Andreas Weigend. Research focused into how mobile – global – cloud impacts the organizations of the future. OPEN DATA helps companies: Understand the value of the data they already have, and to Show them how to create significant additional value by combining these data with appropriate other data Example: Publishing the right data in order to benefit Customers and trading partners, and Third party developers.