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

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Presentation transcript:

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

Building Computers 1970’s

Connecting Computers 1980’s

Connecting Pages 1990’s

Connecting People 2000’s

Connecting Sensors 2010’s

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

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

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

tude/b/0/history/dashboard Location: Google Latitude

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

Create DistributeConsume Everybody

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 Social Data Growth is EXPONENTIAL

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

The ABC AttentionAdvertising BelongingBranding CollaborationConfusion

Two Monologues don’t make a Dialogue GDI, Zurich, January 2010 Twitter -- The Illusion of an Audience World Innovation Forum, NYC, June 2010

Fundamental Shift in Communication One-way  Two-way Asynchronous  Synchronous Planning  Interaction List  Flow Private  Public

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

Case study: What data for targeting of a new phone product? Connection data Who called who? Traditional segmentation Demographics Loyalty

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

Company Customers

Audience C2B: Customer to Business C2C: Customer to Customer C2W

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 her friend ) Conversation (information as excuse for communication)

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

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

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

Fraud reduction: Provide risk scores Social network intelligence Social graph targeting: Provide prospects

Audience C2B: Customer to Business C2C: Customer to Customers C2W: Customer to World

Amazon.com: Public sharing of interests

Where does product knowledge come from? Case Study: Best Buy

Who Can You Get To Work For You? 100M Customers 100k Employees 100 Specialists

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

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

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

Product Customer Brand

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

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 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

1. Facebook Customers knowingly and willingly give data Designed for contribution and distribution 2. Google Take whatever you can get 3. Amazon Customer-centric: Help them make good decisions

Do not have  Somewhere already Cannot get  Can! User will give Must not use  Embrace it Be secretive  Be transparent Information asymmetry  Information symmetry

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

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

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