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Customer Centricity: The Art of Social Data

  1. 1. Customer Centricity: The Art of Social Data cleverbridge Networking Event, Boston 12 October 2011 Andreas Weigend @aweigend www.weigend.com
  2. 2. Building 1970’s Computers
  3. 3. Connecting 1980’s Computers
  4. 4. Connecting 1990’s Pages
  5. 5. Connecting 2000’s People
  6. 6. Connecting 2010’s Sensors
  7. 7. Social vs Transactional Data vs Social Media Revolution vs Evolution
  8. 8. “Social Data is the New Oil” UN General Assembly, 8 November 2011
  9. 9. Irreversible Shift in Customer Mindset
  10. 10. Nike+ Customers - engage - connect - share 3 times per week on average
  11. 11. Smartphones and Sensors Context, situation • Sound • Light Customers interact • Tag • Scan
  12. 12. Location: Google Latitude
  13. 13. Location Absolute: Place, time • Individual: Identity, History • Aggregate: Insights Relative: Distance • To places: Advertising • Between people: Dating • Between devices: Risk
  14. 14. Create Distribute Consume Everybody
  15. 15. 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
  16. 16. Social Data Growth is EXPONENTIAL This year people will generate more data than mankind has from its beginning through last year
  17. 17. 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
  18. 18. The ABC Attention Advertising Belonging Branding Collaboration Confusion
  19. 19. Twitter -- The Illusion of an Audience World Innovation Forum, NYC, June 2010 Two Monologues don’t make a Dialogue GDI, Zurich, January 2010
  20. 20. Fundamental Shift in Communication One-way  Two-way Asynchronous  Synchronous Planning  Interaction List  Flow Private  Public
  21. 21. Data Strategy Attention Situation • Clicks, Transactions • Geo-location • Device Intention • Search User generated Connection • Reviews • Social graph
  22. 22. Case study: What data for targeting of a new phone product? Traditional segmentation Connection data • Demographics • Who called who? • Loyalty
  23. 23. 1.35% Adoption rate 4.8x 0.28% Traditional Connection segmentation data
  24. 24. Company Customers
  25. 25. Amazon.com Share the Love
  26. 26. 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)
  27. 27. Purpose of communication: to transmit information? Or is information just an excuse for communication?
  28. 28. 1993 “On the Internet, nobody knows you’re a dog”
  29. 29. 2011 “On the Internet, everybody knows you’re a dog”
  30. 30. Social network intelligence Social graph targeting: Provide prospects Fraud reduction: Provide risk scores
  31. 31. Audience C2B: Customer to Business C2C: Customer to Customers C2W: Customer to World
  32. 32. Amazon.com: Public sharing of interests
  33. 33. Who Can You Get To Work For You? 100M Customers 100k Employees 100 Specialists
  34. 34. Marketer-generated Consumer-generated aware share consider opinion buy use Funnel Megaphone
  35. 35. Get Your Customers To Work For You! • Reduce barriers for contribution • Design incentives that work
  36. 36. 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
  37. 37. Customer Product Brand
  38. 38. From controlled production for the masses… … to uncontrolled production by the masses
  39. 39. 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)
  40. 40. 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
  41. 41. 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
  42. 42. 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
  43. 43. 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
  44. 44. 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

  • 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
  • Digitizing back office: 100 people
  • 100k poke
  • Connecting Content / Content is king100M
  • CommunitySocial filters
  • Measure, detectorsContext is king
  • 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. 
  • Means of production
  • Means of production
  • 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
  • What is this? This is a scale. This is my scaleIt is connected to the internet.
  • 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:
  • 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
  • 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
  • BrainwashingPeople share.ConfusionCollaborationCommunity
  • Application to business:
  • Data source
  • based on experience, intuition, and data Picture of graph from FosterLeveraging the social graph
  • 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)
  • DC: Redo, as discussed in ER
  • forCY: makes this table or individual arrowsAlso of plz adjust title to what we had in the outline
  • MerchandisingDefine viral marketing10 years agoAmazon vs FacebookAmazon is about products, interactions with store, not with friends. No NewsFeed.Facebook is about interactions between friends.
  • Information the purpose for communication
  • based on experience, intuition, and data Transient: (anonymous) Computes scores across social networks in the US
  • forCY: makes this table or individual arrowsAlso of plz adjust title to what we had in the outline
  • Reduce barriers for contribution (e.g., light-weight annotation)Design incentives that work (clear value to contributor)
  • Point is to show specifics
  • 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.
  • Mass Production / Industrial Age
  • Successful social systems are engineered for individuals to express themselves and interact effortlessly.Community or connection
  • Accenture: Get it right the first time
  • emphasize how different this is from the past
  • emphasize how different this is from the past
  • emphasize how different this is from the past This is the new “mission, vision, values”
  • 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
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