San Francisco, CA
03 May 2010
Andreas Weigend
@aweigend
www.weigend.com
3 Decades of Innovation
1990’s: Search - find
2000’s: Social - share
2010’s: Mobile - create
How the
Social Data Revolution
Changes (Almost) Everything
Social Data Revolution
• How do we “utilize” the “community”?
• Who do we listen to?
• Who do we co-create with?
–
–
–
–
Physical friends
Peers (similar properties to you)
Ad hoc (e.g., for car purchase)
Experts (what bestows authority?)
• Institution? Past action?
• Reputation/ brand as shortcut to allocate attention
Social Data Revolution
In the last minute
• 4,000,000 search queries,
• 500,000 pieces of content shared on FB,
• 100,000 product searches on Amazon.com,
• 40,000 bit.ly urls created,
• 40,000 tweets sent
Data creation and
sharing
 Who
creates data?
Data is the digital air in which we breathe
 How
will this data be used?
Improve product design, service delivery, relationships
 How
will this data be shared?
Every company is a publishing company
 What
(if anything) does it mean to “own” data?
1800’s: Transport energy 
Industrial Revolution
1900’s: Transport data 
Information Revolution
2000’s: Create and share data 
Social Data Revolution
private
public
Blippy: Sharing purchase info
Case study: weigend.com/blog
Social: Distributed to FB friends
Compare
FBconnect
on blog with
traditional
contact box
(no social
element)
Connecting
Computers
Connecting
Pages
Connecting
People
Underlying?
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
1 billion connected flash players
40 billion RFID tags worldwide
Pay-as-you-drive car insurance (GPS)
99% DNA
overlap
Time Scales
Data, Technology: ~1 year
Social Norms: ~10 years
Biology: ~100k yrs
How the
Social Data Revolution
Changes (Almost) Everything
Purpose of communication:
to transmit information?
Or is information just
an excuse for communication?
Web 0
Computers
Web 1
Pages
Data
Web 2
People
Introduction
Data
I
C2B (Customer-to-Business)
II
C2C (Customer-to-Customer)
III
C2W (Customer-to-World)
IV
Insights
v
Questions
Part I:
C2B
+1 800-4-SCHWAB
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?
Decision making
Discovery
Recommendations
…but people want to discover
and help with decisions!
Google helps
people find stuff
Amazon.com helps people
make decisions…
…based on
reviews
C2B Data Strategy:
- Reviews
- Purchases, Clicks…
Customers who
bought
this item also
bought…
Customers who
viewed this item also viewed…
Customers who
viewed this item ultimately bought…
Amazon.com helps people
make decisions…
… based on
clicks and
purchases
creating and refining
product space awareness…
Process of
Shopping?
… only occasionally
punctuated by purchases
How do you know peoples’
secret desires?
Accounting
Amazon.com is
engineered for feedback

Data Sources
Attention
Transactions
Clicks

Intention
Search

Context
Geolocation
Device
The Social Graph

Connection data
New phone product: How to market?

Traditional segmentation
Demographics
Loyalty

Connection data
Who called whom?
1.35%
Adoption
rate
4.8x
0.28%
Traditional
segmentation
Connection
data
Business
Customers
Part II:
C2C
C2C
= Customer-to-Customer
Customers share
with each other
Amazon.com Share the Love
Amazing conversion rates since you chose:
Content
(the item)
Context
(you just bought that item)
Connection
(you ask Amazon to email your
Conversation
(information as
friend)
excuse for communication)
Blippy: Sharing purchases
Social network intelligence
Fraud reduction
–
Provide risk scores
Social graph targeting
Provide list of prospects
Influencer Marketing?
Real life
vs
Market to influential people…
… and then reach everyone else for free
Chain length
Real Life
38% ≥ 4 links
Facebook
86% ≥ 4 links
C2W
Part III:
Amazon.com:
Public sharing of interests
Consumers
- Engage
- Share
- Connect
3 times per week
“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?
• Search tweets
• Create tweets
• Follow users
http://www.mrtweet.com
The Illusion of an Audience
Part IV:
Insights
=
+ wheels
=
+ heels
Customer
Product
Brand
From controlled production
for the masses…
… to uncontrolled production
by the masses
=
Shift in Customer
Expectations
People trust reviews and comments by
others more than marketing messages
People use their friends’ attention to filter
information and to discover new things
Social
filter
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
Part V:
Questions
Outline: Intuit Questions

Data creation and sharing

Consumer expectations

Innovation methodology

Marketing in SDR
The 4 C's of marketing

E-business  Me-business  We-business

Monetization
Data creation and sharing
 Who
creates data?
Data is the digital air in which we breathe
 How
will this data be used?
Improve product design, service delivery, relationships
 How
will this data be shared?
Every company is a publishing company
 What
(if anything) does it mean to “own” data?
Consumer expectations

How have consumer expectations changed towards creating,
sharing, accessing, and controlling data, especially in the
financial area?
•

What benefits will customers expect in exchange to giving
Intuit permission to use their data?

Ultimately, how can Intuit help people discover products
and services, make better decisions, and subsequently
participate in the value its customers create?
Innovation methodology

How should Intuit experiment with
C2C platforms for social commerce, such as Facebook?

How can Intuit leverage
C2W data (Customer-to-World), such as Twitter?

Which new data sources and technologies should Intuit pay
attention to, e.g., for recommendations?
Marketing in SDR

What are the obstacles for Intuit to fully utilize the data of
its customers
Including consumer choice, purchase decisions, social relations,
attitudes and beliefs?

How can the limitations of traditional market research be
overcome by "instrumenting the world“?
I.e., by systems and incentives that enable customers to give
feedback to Intuit whenever they want to?

How can Intuit marketing leverage the consumer mind shift
of the social data revolution?
The 4 C’s of Marketing
 Content
 Context
 Connection
 Conversation
E-biz  Me-biz  We-biz
 Who
talks to whom?
Consumers to consumers
 Who
trusts whom?
Shift from institutions to individuals
 Who
is in control?
From e-business
(company focus, Web 1.0)
to me-business
(customer focus , Web 2.0)
to we-business
(community focus , Web 3.0)
Monetization
 Who
manages whom?
Move from CRM to CMR (Customer Managed Relationships)
 Who
pays whom?
Design incentives for participation and interaction
Charge as much as you can  Charge as little as you can?
•
Jeff Jarvis
Transaction economy  Relationship economy
•
Shoshana Zuboff
Summary
 Innovation
Internal  External
•
“Most smart people don’t work here.” Bill Joy
 Data
Collect and analyze  Create and share
 Experiments
Push and prey  Launch and learn
Q&A
Andreas Weigend
@aweigend
www.weigend.com
http://weigend.com/blog
@aweigend
 OPEN
DATA is part of the OPEN FIRST group.
Ted Shelton. Noreena Hertz. Doc Searls. Andreas Weigend.
Research focused into how mobile – global – cloud impacts the
organizations of the future.
 OPEN
DATA helps companies:
Understand the value of the data they already have, and to
Show them how to create significant additional value by
combining these data with appropriate other data
Example: Publishing the right data in order to benefit

Customers and trading partners, and

Third party developers.