SlideShare a Scribd company logo
1 of 39
AI, automation, and observations
from billions of customer interactions
WHY WE AUTOMATE
1
Vicky Ge, Sr. Product Manager
Global Email Automation
Amazon.com
linkedin.com/in/vickyge
vickymakesstuff
Hello, Email Insiders!
3
Product manager
Illustrator and calligrapher
An Amazon customer
Complex decision maker
Has some organic intelligence
Also once met Grumpy Cat IRL
DISCLAIMER
The views expressed in this presentation are mine alone and do not
necessarily reflect those of my employer, Amazon.com, LLC. I am not an
official spokesperson of Amazon.com, LLC. Information in this
presentation is not confidential or proprietary to Amazon.com, LLC or
any third party that has disclosed information to us.
4
WHY WE AUTOMATE
5AMAZON.COM CONFIDENTIAL 5
6
Customers should feel the same anticipation, curiosity, and delight to
see a notification from Amazon as they feel to see an Amazon box
on their doorstep.
We are proudest when customers feel that Amazon gets them.
7
Customer Obsession
Leaders start with the customer and work backwards. They work
vigorously to earn and keep customer trust. Although leaders
pay attention to competitors, they obsess over customers.
A CASE STUDY IN CUSTOMER OBSESSION
8
9
“I want you to shut down the channel. We can
build a $100B company without sending out a
single email […] Who in this room needs to get up
and shut down the channel?”
10
Email is a privilege, not a right
We don’t have to send email.
HOW TO MAKE AN EMAIL MARKETER
1 part market researcher
1 part content designer
1 part quality assurance
2 parts <table> wrangler
1 tsp “no we can’t remove the unsubscribe button”
5 parts courage to press the send button
For low calorie option, substitute man hours with marketing automation
Season with cutting edge technology to taste
11
12
We automate so customers can be served
efficiently and at scale.
13
DEFINITIONS
Artificial Intelligence (AI)
Machine Learning (ML)
Automation
14
APPLICATIONS OF ML
Healthcare
Data security
Driverless cars
Image recognition
Fraud
Categorization
Anomaly detection
Predictive analytics
Financial trading
Search
Marketing
personalization
Content recommendations
Reducing wait times
Pricing algorithms
Pattern recognition
Defense
Law
Chat bots
Customer service
Natural language
processing
…
15
APPLICATIONS OF ML 1,000,000,000,000,000,000
,000,000,000,000,000,000,
000,000,000,000,000,000,0
00,000,000,000,000,000,00
0,000,000,000,000,000,000
,000,000,000,000,000,000,
000,000,000,000,000,000,0
00,000,000,000,000,000,00
0,000,000,000,000,000,000
,000
Healthcare
Data security
Driverless cars
Image recognition
Fraud
Categorization
Anomaly detection
Predictive analytics
Financial trading
Search
Marketing
personalization
Content recommendations
Reducing wait times
Pricing algorithms
Pattern recognition
Defense
Law
Chat bots
Customer service
Natural language
processing
…
16
APPLICATIONS OF ML
Healthcare
Data security
Driverless cars
Image recognition
Fraud
Categorization
Anomaly detection
Predictive analytics
Financial trading
Search
Marketing
personalization
Content recommendations
Reducing wait times
Pricing algorithms
Pattern recognition
Defense
Law
Chat bots
Customer service
Natural language
processing
…
17
18
APPLICATIONS OF ML
Healthcare
Data security
Driverless cars
Image recognition
Fraud
Categorization
Anomaly detection
Predictive analytics
Financial trading
Search
Marketing
personalization
Content recommendations
Reducing wait times
Pricing algorithms
Pattern recognition
Defense
Law
Chat bots
Customer service
Natural language
processing
…
19
20
We use machine learning so customers can
receive recommendations they like, not
recommendations we like.
21
22
23
“Literally”“Obviously”
010100101101010100110110100110
101010011010101001010010100101
101010100110110100110101010011
010101001010101101001101010100
110101010010100101001011010101
001101101001101000101011001110
Wow
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
24
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
25
Rudolf Arnheim, Visual Thinking 1969
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
MACHINE LEARNING IS NOT SO DIFFERENT FROM
HUMAN LEARNING
26
Input
data
Find
patterns
Output
results
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
HERE’S WHAT A NEURAL NET THINKS OF YOUR #SELFIE
27
http://karpathy.github.io/2015/10/25/selfie/
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
28
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
TRAINING FOR PATTERN RECOGNITION
29
Visualizing and Understanding Convolutional Networks (Matthew Zeiler 2013)
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
WHAT ML THINKS OF YOUR SELFIE
Amazon.com 30
53.1 67.3 Rob Haitani
Amazon Outbound
Marketing Summit, 2017
WHAT ML THINKS OF YOUR SELFIE
31
52.0 56.3 Rob Haitani
Amazon Outbound
Marketing Summit, 2017
FOR BETTER OR WORSE, ML REFLECTS HUMANS
32
Rob Haitani
Amazon Outbound
Marketing Summit, 2017
33
Machine learning is powerful
… but only as powerful as your data set
SIMPLE AUTOMATION ALSO WORKS
How do customers signal to you?
Viewing
Searching
Purchasing
Calling a sales rep
Referring a friend
Being referred from a friend
Visiting a brick and mortar store
...
34
How do you react to that signal?
Related to what you viewed
How can we help you find…
Share your purchase with a friend
Did s/he meet your expectations
Thanks for referring
Welcome to the family
Buy online, get it delivered
...
SIMPLE AUTOMATION ALSO WORKS
35
How do you connect the dots?
When do you send your messages?
Where do you send your messages?
How do you display your content?
How do you mix your content?
How often do you contact customers?
What channels do your customers use?
How do you set and analyze success?
…
36
Don’t get so caught up in the AI of
tomorrow that you forget the BI of today
… also known as “common sense”
37
Reflections Email is a privilege, not a right.
Machine learning is as powerful as your data set.
Plan for the AI of tomorrow; deliver the BI of today.
38
Keep your focus on the customer
… and work backwards into the technologies you need.
Why We Automate: AI, Automation, and Observations from Billions of
Customer Interactions
Vicky Ge, Sr. Product ManagerAmazon.com
Global Email Automation
Amazon.com
THANKS!
linkedin.com/in/vickyge
vickymakesstuff
vge@amazon.com

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Eis 2 fri_ vickyge

  • 1. AI, automation, and observations from billions of customer interactions WHY WE AUTOMATE 1 Vicky Ge, Sr. Product Manager Global Email Automation Amazon.com linkedin.com/in/vickyge vickymakesstuff
  • 3. 3 Product manager Illustrator and calligrapher An Amazon customer Complex decision maker Has some organic intelligence Also once met Grumpy Cat IRL
  • 4. DISCLAIMER The views expressed in this presentation are mine alone and do not necessarily reflect those of my employer, Amazon.com, LLC. I am not an official spokesperson of Amazon.com, LLC. Information in this presentation is not confidential or proprietary to Amazon.com, LLC or any third party that has disclosed information to us. 4
  • 6. 6 Customers should feel the same anticipation, curiosity, and delight to see a notification from Amazon as they feel to see an Amazon box on their doorstep. We are proudest when customers feel that Amazon gets them.
  • 7. 7 Customer Obsession Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers.
  • 8. A CASE STUDY IN CUSTOMER OBSESSION 8
  • 9. 9 “I want you to shut down the channel. We can build a $100B company without sending out a single email […] Who in this room needs to get up and shut down the channel?”
  • 10. 10 Email is a privilege, not a right We don’t have to send email.
  • 11. HOW TO MAKE AN EMAIL MARKETER 1 part market researcher 1 part content designer 1 part quality assurance 2 parts <table> wrangler 1 tsp “no we can’t remove the unsubscribe button” 5 parts courage to press the send button For low calorie option, substitute man hours with marketing automation Season with cutting edge technology to taste 11
  • 12. 12 We automate so customers can be served efficiently and at scale.
  • 13. 13
  • 15. APPLICATIONS OF ML Healthcare Data security Driverless cars Image recognition Fraud Categorization Anomaly detection Predictive analytics Financial trading Search Marketing personalization Content recommendations Reducing wait times Pricing algorithms Pattern recognition Defense Law Chat bots Customer service Natural language processing … 15
  • 16. APPLICATIONS OF ML 1,000,000,000,000,000,000 ,000,000,000,000,000,000, 000,000,000,000,000,000,0 00,000,000,000,000,000,00 0,000,000,000,000,000,000 ,000,000,000,000,000,000, 000,000,000,000,000,000,0 00,000,000,000,000,000,00 0,000,000,000,000,000,000 ,000 Healthcare Data security Driverless cars Image recognition Fraud Categorization Anomaly detection Predictive analytics Financial trading Search Marketing personalization Content recommendations Reducing wait times Pricing algorithms Pattern recognition Defense Law Chat bots Customer service Natural language processing … 16
  • 17. APPLICATIONS OF ML Healthcare Data security Driverless cars Image recognition Fraud Categorization Anomaly detection Predictive analytics Financial trading Search Marketing personalization Content recommendations Reducing wait times Pricing algorithms Pattern recognition Defense Law Chat bots Customer service Natural language processing … 17
  • 18. 18
  • 19. APPLICATIONS OF ML Healthcare Data security Driverless cars Image recognition Fraud Categorization Anomaly detection Predictive analytics Financial trading Search Marketing personalization Content recommendations Reducing wait times Pricing algorithms Pattern recognition Defense Law Chat bots Customer service Natural language processing … 19
  • 20. 20 We use machine learning so customers can receive recommendations they like, not recommendations we like.
  • 21. 21
  • 22. 22
  • 25. 25 Rudolf Arnheim, Visual Thinking 1969 Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 26. MACHINE LEARNING IS NOT SO DIFFERENT FROM HUMAN LEARNING 26 Input data Find patterns Output results Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 27. HERE’S WHAT A NEURAL NET THINKS OF YOUR #SELFIE 27 http://karpathy.github.io/2015/10/25/selfie/ Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 29. TRAINING FOR PATTERN RECOGNITION 29 Visualizing and Understanding Convolutional Networks (Matthew Zeiler 2013) Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 30. WHAT ML THINKS OF YOUR SELFIE Amazon.com 30 53.1 67.3 Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 31. WHAT ML THINKS OF YOUR SELFIE 31 52.0 56.3 Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 32. FOR BETTER OR WORSE, ML REFLECTS HUMANS 32 Rob Haitani Amazon Outbound Marketing Summit, 2017
  • 33. 33 Machine learning is powerful … but only as powerful as your data set
  • 34. SIMPLE AUTOMATION ALSO WORKS How do customers signal to you? Viewing Searching Purchasing Calling a sales rep Referring a friend Being referred from a friend Visiting a brick and mortar store ... 34 How do you react to that signal? Related to what you viewed How can we help you find… Share your purchase with a friend Did s/he meet your expectations Thanks for referring Welcome to the family Buy online, get it delivered ...
  • 35. SIMPLE AUTOMATION ALSO WORKS 35 How do you connect the dots? When do you send your messages? Where do you send your messages? How do you display your content? How do you mix your content? How often do you contact customers? What channels do your customers use? How do you set and analyze success? …
  • 36. 36 Don’t get so caught up in the AI of tomorrow that you forget the BI of today … also known as “common sense”
  • 37. 37 Reflections Email is a privilege, not a right. Machine learning is as powerful as your data set. Plan for the AI of tomorrow; deliver the BI of today.
  • 38. 38 Keep your focus on the customer … and work backwards into the technologies you need.
  • 39. Why We Automate: AI, Automation, and Observations from Billions of Customer Interactions Vicky Ge, Sr. Product ManagerAmazon.com Global Email Automation Amazon.com THANKS! linkedin.com/in/vickyge vickymakesstuff vge@amazon.com