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Andreas Weigend @aweigend weigend

Andreas Weigend @aweigend www.weigend.com. Customer Centricity: The Art of Social Data cleverbridge Networking Event, Boston 12 October 2011. 1970’s. Building Computers. 1980’s. Connecting Computers. 1990’s. Connecting Pages. 2000’s. Connecting People. 2010’s. Connecting Sensors.

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Andreas Weigend @aweigend weigend

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  1. Andreas Weigend @aweigend www.weigend.com Customer Centricity:The Art of Social Data cleverbridge Networking Event, Boston 12 October 2011

  2. 1970’s BuildingComputers

  3. 1980’s ConnectingComputers

  4. 1990’s ConnectingPages

  5. 2000’s ConnectingPeople

  6. 2010’s ConnectingSensors

  7. “Social Data is the New Oil” UN General Assembly, 8 November 2011

  8. Irreversible Shift in Customer Mindset

  9. Nike+ Customers- engage- connect - share 3 times per week on average

  10. Smartphones and Sensors • Context, situation • Sound • Light • Customers interact • Tag • Scan

  11. Location: Google Latitude

  12. Location • Absolute: Place, time • Individual: Identity, History • Aggregate: Insights • Relative: Distance • To places: Advertising • Between people: Dating • Between devices: Risk

  13. Create • Distribute • Consume • Everybody

  14. Social Data Growth is EXPONENTIAL • The amount of data a person creates • doubles every 1.5 years • after five years  x 10 • after ten years  x 100

  15. Social Data Growth is EXPONENTIAL • This year people will generate • more data than mankind has from its beginning through last year

  16. Economics of Social Data • * With social data being abundant, attention has become the scarcest resource. • * To get attention, people will do anything, including socialize their data

  17. The ABC

  18. Twitter -- The Illusion of an AudienceWorld Innovation Forum, NYC, June 2010 Two Monologues don’t make aDialogue GDI, Zurich, January 2010

  19. Fundamental Shift in Communication

  20. Data Strategy • Attention • Clicks, Transactions • Situation • Geo-location • Device • Intention • Search • Connection • Social graph • User generated • Reviews

  21. Case study: What data fortargeting of a new phone product? • Traditional segmentation • Demographics • Loyalty • Connection data • Who called who?

  22. 1.35% Adoptionrate 4.8x 0.28% • Traditionalsegmentation • Connection data

  23. Company Customers

  24. Amazon.com Share the Love

  25. Result:Amazingconversion 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)

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

  27. 1993 “On the Internet, nobody knows you’re a dog”

  28. 2011 “On the Internet, everybody knows you’re a dog”

  29. Social networkintelligence Fraud reduction: Provide risk scores Social graph targeting: Provide prospects

  30. Audience

  31. Amazon.com: Public sharing ofinterests

  32. Who Can You Get To Work For You?

  33. aware consider buy use share opinion Marketer-generated Consumer-generated Megaphone Funnel

  34. Get Your Customers To Work For You! • Reduce barriers for contribution • Design incentives that work

  35. Corner / Oversized Rooms: Rooms Ending in: 04 Oversized, Corner Room, Quiet Room 24 Oversized, Corner Room with North 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

  36. Customer Product Brand

  37. From controlled production forthe masses… … to uncontrolled production bythe masses

  38. E  Me  We-commerce Who talks to whom? • Consumers to consumers Who trusts whom? • Shift from institutions to individuals Who is in control? • From e-commerce (company focus, Web 1.0) • to me-commerce (customer focus, Web 2.0) • to we-commerce (relationship focus, Web 3.0)

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

  40. Data Culture

  41. Product Culture • Help people make better decisions • Make it trivially easy for people to contribute • Give people an excuse to connectNote: Products and services that use social data improve over time

  42. Company Culture • Write the equations of your business in terms of customer centric metricse.g., View-weighted availability • Capture the space created by the disappearing constraints of the paste.g., Communication costs

  43. Andreas Weigend @aweigend www.weigend.com Thank you! Customer Centricity: The Art of Social Data cleverbridge Networking Event, Boston 12 October 2011

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