4
• 1970’s: Building Computers
• 1980’s: Connecting Computers
• 1990’s: Connecting Pages
• 2000’s: Connecting People
• 2010’s: Connecting Data
7
Questions
1. What is abundant?
2. What is scarce?
3. What are the constraints?
4. What is the bottleneck?
Which data would you pay most for?
1. Geolocation: Where did he go?
2. Search history: What did he search for?
3. Purchase history: What did he buy?
4. Social graph: Who are his “friends"?
5. Demographics
15
Data Rules
1. Start with a question, not with the data
2. Focus on decisions and actions, design for feedback
19
O2O: Mobile• Identity: Proxy for person
• Context: Many sensors
Easy for user to contribute Easy to reach user, but
high cost if inappropriate
22
What changed, what didn’t?Changed
• Ask for forgiveness,not for permission
• Customer-centricity• Helping people
make better decisions
• Recommendations
Unchanged• Algorithms Data
• AI• BI• CI• DI
23
Data Scientist• Data literate
• Able to handle large data sets
• Understands domain and modeling
• Wants to communicate and collaborate
• Curious with “can-do” attitude
24
Goal: Help people make better decisions
Data Strategy: Make it trivially easy to Contribute Connect Collaborate
Amazon = Data Refinery
27
Amazon: Recommendations
1. Manual (Experts)
2. Implicit (Clicks, Searches)
3. Explicit (Reviews, Lists)
4. Situation (Local, Mobile)
5. Connections (Social graph)
Data sources for marketinga new phone product
Social Graph(Who called
whom?)
Segmentation (Demographics,
Loyalty)
Fitness Function
• Also called the equation of business
• Expresses your beliefs, mission, values
• Needed for the of evaluation of experiments
36
Focus• Audience• Associate• Basket• Country• Customer• Household• Lawyer
• Manufacturer• Product• Register• Shelf• Store• Supplier• Truck
37
Focus• Audience• Associate• Basket• Country• Customer• Household• Lawyer
• Manufacturer• Product• Register• Shelf• Store• Supplier• Truck
39
Data Rule #3
1. Start with a question, not with the data
2. Focus on decisions and actions
3. Base your fitness function on metrics that matter to your customers
41
Data Ecosystem
data.taobao.com
Users: 420 kPrice per day: 10 元 = USD 2 Revenues per
year:1.5 B 元 = USD 250 M
42
New Business Models
Share Economy “Access trumps possession” Airbnb,… Uber, Sidecar, Lyft,… Relayrides, Getaround,…
Innovation enabled by data
43
Getaround requires Facebook to login. We use Facebook to ensure trust and safety to our community.
44
What is the Essence of Facebook?
1. Content creation
2. Content distribution and
consumption
3. Identity management
48
• Trust is distributed (across the network)
• History is traceable (via blockchain)
Digital title for your house
Digital contracts, signatures…
Innovation enabled by data
49
Summary: Data Rules
1. Start with a question, not with the data
2. Focus on decisions and actions
3. Base your fitness function on metrics that matter to your customers
4. Embrace transparency
Summary: Commerce
1. E-commerce: Digitize Focus on company and products
2. Me-commerce: Share Focus on customer and attributes
3. We-c0mmerce: Connect Focus on connections between
individuals
Questions?
1. Do your customers understand the value they get when they give you data?
2. Does your product or service get better over time and with data (or worse)?
53
… 1984 – 1994 – 2004 – 2014 …
• How has data (connectivity, cloud, refineries) changed you in the past years?
• How will data change you, your community, your business, society in the next few years?
Thank you
@aweigend
+1 650 [email protected]
weigend.com/files/speaking
youtube.com/socialdatarevolution
56
A Brief History of Privacy
1. No Privacy
Some inventions (Chimneys, Cities)
2. Privacy
More inventions (Facebook, Glass)
3. Illusion of Privacy
Top Related