World Innovation Forum 2010. Would like to download the Presentation? Please pay with a Tweet by following the link: http://www.paywithatweet.com/pay/?id=844e8b6643e07f0c2a8f06a03a5bb1b9

1. Andreas Weigend
@aweigend
www.weigend.com

3. Who creates data?
Production: Data is digital air
How will this data be shared?
Distribution: Everyone is a publisher
What will this data be used for?
Consumption: Behavior changes

4. A Shift in Language
• Collect • Share
• Solicit • Distribute
• Mine • Interpret
• Segment • Empower

5. Technologies Enabling Innovation
1800’s: Transport energy 
Industrial Revolution
1900’s: Transport data 
Information Revolution
2000’s: Create data 
Social Data Revolution

6. In the last sixty seconds…
4,000,000 Web searches
500,000 Content shares
100,000 Product searches
40,000 Tweets created
40,000 Links shortened

7. us.hsmglobal.com/contenidos/… bit.ly/WIF2010

8. Waves of Innovation
1990’s: Search  find
2000’s: Social  share
2010’s: Mobile  create
 Social Data Revolution

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

10. Agenda
Introduction Data and Behavior
I C2B (Customer-to-Business)
II C2C (Customer-to-Customer)
III C2W (Customer-to-World)
IV Insights
4:55–5:00pm Q&A

11. Connecting
Computers

12. Connecting
Pages

13. Connecting
People

14. Underlying?

15. Data
The amount of data each person creates
doubles every 1.5 … 2 years
2x
time?

16. Data
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

18. Since then…
+ Computation
+ Communication
+ Sensing

19. 1 billion connected sensors

20. 40 billion RFID tags

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

24. Monitors your excercise and sleep

25. 99% DNA
overlap

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

27. Agenda
Introduction Data and Behavior
I C2B (Customer-to-Business)
II C2C (Customer-to-Customer)
III C2W (Customer-to-World)
IV Insights
4:55–5:00pm Q&A

28. Part I: C2B

29. +1 800-4-SCHWAB

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

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

32. Customers who bought this item also bought…

33. Customers who viewed this item also viewed…

34. Customers who viewed this item ultimately bought…

35. Social proof:
Put your money
where your
mouth is

36. How do you know peoples’
secret desires?
World Innovation Forum

37.  Attention Data Sources
Clicks, Transactions
 Intention
Search
 Connection  Situation
Social graph Geo-location
Device

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

39. 1.35%
Adoption
rate
4.8x
0.28%
Traditional Connection
segmentation data

40. Business
Customers

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

42. Part II: C2C

43. Amazon.com Share the Love

44. Result: Amazing conversion rates
since customer chooses
Content (the item)
Context (she just bought that item)
Connection (she asked Amazon to email her friend)
Conversation (information as excuse for
communication)

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

46. What do my friends think of this product?

47. Social graph targeting
Provide list of prospects

48. Fraud reduction
–
Provide risk scores

49. Social network intelligence

50. C2W
Part III:

51. Amazon.com: Public sharing of interests

52. Add on-line features to off-line products…

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

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

55. • Search tweets
• Create tweets
• Follow users

56. The Illusion of an Audience

58. Part IV: Insights

59. Customer
Product
Brand

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

63. Consumers
discussing
ideas

64. Consumers
helping
consumers

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

68. Group buying… “get a better deal”

69. E  Me  We-business
 From e-business… (company focus, Web 1.0)
 …to me-business (customer focus , Web 2.0)
 …to we-business (community focus , Web 3.0)

70. Innovation
 Dead data  Live data
Collect and analyze  Create, share, experiment
 Internal  External
“Most smart people don’t work here.” Bill Joy

71. Part V: Questions

72. Audience Question 1
 Do you have any advice on how we can
be authentic in the era of Social Data?
 For companies with limited
resources, what are the costs of some
of the suggestions you mentioned in the
talk?

73. Audience Question 2
 What is the most important ingredient
for a successful innovation strategy?
 Do you have any specific suggestion for
traditional companies: how can we
learn more about the culture change of
the Social Data Revolution?

74. Thank you!
@aweigend
Andreas Weigend | www.weigend.com