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Customer Centricity:
The Art of Social Data
cleverbridge Networking Event, Boston
12 October 2011




              Andreas Weigend
                              @aweigend
                         www.weigend.com
Customer Centricity: The Art of Social Data
Building    1970’s
Computers
Connecting   1980’s
Computers
Connecting   1990’s
Pages
Connecting   2000’s
People
Connecting   2010’s
Sensors
Social vs Transactional
     Data vs Social Media
Revolution vs Evolution
“Social Data is the New Oil”
UN General Assembly, 8 November 2011
Irreversible Shift
in Customer Mindset
Nike+


Customers
- engage
- connect
- share 3 times per week on average
Customer Centricity: The Art of Social Data
Smartphones and Sensors
              Context, situation
              •   Sound
              •   Light

              Customers interact
              •   Tag
              •   Scan
Location: Google Latitude
Customer Centricity: The Art of Social Data
Location
           Absolute: Place, time
           •   Individual: Identity, History
           •   Aggregate: Insights


           Relative: Distance
           •   To places: Advertising
           •   Between people: Dating
           •   Between devices: Risk
Create   Distribute Consume




         Everybody
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
Social Data Growth is EXPONENTIAL


  This year people will generate
 more data than mankind
  has from its beginning

         through last year
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
The ABC


Attention       Advertising

Belonging       Branding

Collaboration   Confusion
Twitter -- The Illusion of an
                      Audience
       World Innovation Forum, NYC, June 2010




Two Monologues don’t make a
                  Dialogue
                      GDI, Zurich, January 2010
Fundamental Shift in Communication

   One-way           Two-way
Asynchronous       Synchronous
   Planning         Interaction
     List              Flow
   Private             Public
Data Strategy

 Attention                       Situation
  • Clicks, Transactions          • Geo-location
                                  • Device
                    Intention
                      • Search

 User generated                  Connection
  • Reviews                       • Social graph
Case study: What data for
  targeting of a new phone product?



Traditional segmentation   Connection data
• Demographics             •   Who called who?
• Loyalty
1.35%

          Adoption
          rate
                4.8x
  0.28%




Traditional            Connection
segmentation             data
Company




Customers
Amazon.com   Share the Love
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)
Purpose of communication:
to transmit information?




               Or is information just
      an excuse for communication?
1993




“On the Internet, nobody knows you’re a dog”
2011




“On the Internet, everybody knows you’re a dog”
Social network intelligence




Social graph targeting: Provide prospects
Fraud reduction: Provide risk scores
Audience


     C2B: Customer to Business
     C2C: Customer to Customers
     C2W: Customer to World
Amazon.com: Public sharing of interests
Who Can You Get To Work For You?


             100M
           Customers
             100k
           Employees
              100
           Specialists
Marketer-generated     Consumer-generated

aware                                 share
         consider         opinion
                    buy use




        Funnel                Megaphone
Get Your Customers To Work For You!


   •   Reduce barriers
       for contribution


   •   Design incentives
       that work
Customer Centricity: The Art of Social Data
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
Customer


           Product


                     Brand
From controlled production for the masses…




       … to uncontrolled production by the masses
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)
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
Data Culture
  Do not have  Somewhere already

  Cannot get  Can! User will give
 Must not use  Embrace it
  Be secretive  Be transparent
  Information  Information symmetry
   asymmetry
Product Culture
   Help people make better decisions
   Make it trivially easy for people to
    contribute
   Give people an excuse to connect

    Note: Products and services that use social data
    improve over time
Company Culture
   Write the equations of your business in
    terms of customer centric metrics
      e.g., View-weighted availability


   Capture the space created by the
    disappearing constraints of the past
      e.g., Communication costs
Thank you!
Customer Centricity: The Art of Social Data
cleverbridge Networking Event, Boston
12 October 2011




               Andreas Weigend
                               @aweigend
                          www.weigend.com

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Customer Centricity: The Art of Social Data

  • 1. Customer Centricity: The Art of Social Data cleverbridge Networking Event, Boston 12 October 2011 Andreas Weigend @aweigend www.weigend.com
  • 3. Building 1970’s Computers
  • 4. Connecting 1980’s Computers
  • 5. Connecting 1990’s Pages
  • 6. Connecting 2000’s People
  • 7. Connecting 2010’s Sensors
  • 8. Social vs Transactional Data vs Social Media Revolution vs Evolution
  • 9. “Social Data is the New Oil” UN General Assembly, 8 November 2011
  • 11. Nike+ Customers - engage - connect - share 3 times per week on average
  • 13. Smartphones and Sensors Context, situation • Sound • Light Customers interact • Tag • Scan
  • 16. Location Absolute: Place, time • Individual: Identity, History • Aggregate: Insights Relative: Distance • To places: Advertising • Between people: Dating • Between devices: Risk
  • 17. Create Distribute Consume Everybody
  • 18. 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
  • 19. Social Data Growth is EXPONENTIAL This year people will generate more data than mankind has from its beginning through last year
  • 20. 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
  • 21. The ABC Attention Advertising Belonging Branding Collaboration Confusion
  • 22. Twitter -- The Illusion of an Audience World Innovation Forum, NYC, June 2010 Two Monologues don’t make a Dialogue GDI, Zurich, January 2010
  • 23. Fundamental Shift in Communication One-way  Two-way Asynchronous  Synchronous Planning  Interaction List  Flow Private  Public
  • 24. Data Strategy Attention Situation • Clicks, Transactions • Geo-location • Device Intention • Search User generated Connection • Reviews • Social graph
  • 25. Case study: What data for targeting of a new phone product? Traditional segmentation Connection data • Demographics • Who called who? • Loyalty
  • 26. 1.35% Adoption rate 4.8x 0.28% Traditional Connection segmentation data
  • 28. Amazon.com Share the Love
  • 29. 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)
  • 30. Purpose of communication: to transmit information? Or is information just an excuse for communication?
  • 31. 1993 “On the Internet, nobody knows you’re a dog”
  • 32. 2011 “On the Internet, everybody knows you’re a dog”
  • 33. Social network intelligence Social graph targeting: Provide prospects Fraud reduction: Provide risk scores
  • 34. Audience C2B: Customer to Business C2C: Customer to Customers C2W: Customer to World
  • 36. Who Can You Get To Work For You? 100M Customers 100k Employees 100 Specialists
  • 37. Marketer-generated Consumer-generated aware share consider opinion buy use Funnel Megaphone
  • 38. Get Your Customers To Work For You! • Reduce barriers for contribution • Design incentives that work
  • 40. 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
  • 41. Customer Product Brand
  • 42. From controlled production for the masses… … to uncontrolled production by the masses
  • 43. 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)
  • 44. 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
  • 45. Data Culture Do not have  Somewhere already Cannot get  Can! User will give Must not use  Embrace it Be secretive  Be transparent Information  Information symmetry asymmetry
  • 46. Product Culture  Help people make better decisions  Make it trivially easy for people to contribute  Give people an excuse to connect Note: Products and services that use social data improve over time
  • 47. Company Culture  Write the equations of your business in terms of customer centric metrics e.g., View-weighted availability  Capture the space created by the disappearing constraints of the past e.g., Communication costs
  • 48. Thank you! Customer Centricity: The Art of Social Data cleverbridge Networking Event, Boston 12 October 2011 Andreas Weigend @aweigend www.weigend.com

Editor's Notes

  1. My background:80’s: Traces of elementary particles (CERN)90’s: Traces of traders (30MM t-bond futures trades)00’s: Traces of people on the web (Amazon.com)Now: Bridging physical and digital, social and mobile data
  2. Digitizing back office: 100 people
  3. 100k poke
  4. Connecting Content / Content is king100M
  5. CommunitySocial filters
  6. Measure, detectorsContext is king
  7. Has been talked to death: Social media etc. My perspective: People choose to shareWhat really is this revolution? - again, talk about social data as being qualitatively different. 
  8. Means of production
  9. Means of production
  10. on averageChange behavior: of individualOf citiesWhy do people do this? They get attention? They get belongingTHIS IS VERY DIFFERENT FROM A SOCIAL MEDIA / TWITTER CAMPAIGN
  11. What is this? This is a scale. This is my scaleIt is connected to the internet.
  12. twitter.com/aweigendmetricsSurprised, influences my behavior. I used to step on a scale once a yearChanges behaviorFor myself / trackingFor others (peer groups)Harvard TED talkBook: LinkedOther examples:
  13. Lightweight E.g., QR code -- classhttp://www.youtube.com/watch?v=EHlN21ebeakPhone = Proxy for the personCf partner?How do you feel when you leave home without mobile?Playground
  14. Ok, all kinds of stuff. Now who does it?Statistics: no more need for sampling.Amazon observes every customer. People can’t hide!“CDC”Consequences.Study of consumer has changedConsumer has changed
  15. BrainwashingPeople share.ConfusionCollaborationCommunity
  16. Application to business:
  17. Data source
  18. based on experience, intuition, and data Picture of graph from FosterLeveraging the social graph
  19. based on experience, intuition, and data Picture of graph from FosterLeveraging the social graph“Birds of a feather shop together”Hill, Provost, & Volinsky, Network-based Marketing. Statistical Science 21 256–276 (2006)
  20. DC: Redo, as discussed in ER
  21. forCY: makes this table or individual arrowsAlso of plz adjust title to what we had in the outline
  22. MerchandisingDefine viral marketing10 years agoAmazon vs FacebookAmazon is about products, interactions with store, not with friends. No NewsFeed.Facebook is about interactions between friends.
  23. Information the purpose for communication
  24. based on experience, intuition, and data Transient: (anonymous) Computes scores across social networks in the US
  25. forCY: makes this table or individual arrowsAlso of plz adjust title to what we had in the outline
  26. Reduce barriers for contribution (e.g., light-weight annotation)Design incentives that work (clear value to contributor)
  27. Point is to show specifics
  28. companies thought they own their customer  switching costs largely gonecompanies thought they own product -> who knows more about my phone: manufacturer? Carrier? … or the web?companies thought they own brand  co-creationcustomers talk about whatever they want to talk about CONVERSATION Ultimately, all about data. Social data.
  29. Mass Production / Industrial Age
  30. Successful social systems are engineered for individuals to express themselves and interact effortlessly.Community or connection
  31. Accenture: Get it right the first time
  32. emphasize how different this is from the past
  33. emphasize how different this is from the past
  34. emphasize how different this is from the past This is the new “mission, vision, values”
  35. My background:80’s: Traces of elementary particles (CERN)90’s: Traces of traders (30MM t-bond futures trades)00’s: Traces of people on the web (Amazon.com)Now: Bridging physical and digital, social and mobile data