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“I want you to shut down the channel. We can
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Why We Automate: Observations from billions of customer interactions
The presentation discusses the importance of automation and machine learning in enhancing customer experiences at Amazon, emphasizing that email communication is a privilege that should be used thoughtfully. It highlights that effective use of machine learning can serve customers efficiently by providing personalized recommendations based on their preferences. Ultimately, the focus remains on understanding customer needs and working backwards to create impactful solutions.
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Why We Automate: Observations from billions of customer interactions
- 1. AI, automation, andobservations from billions of customer interactions WHY WE AUTOMATE 1 Vicky Ge, Sr. Product Manager Global Email Automation Amazon.com linkedin.com/in/vickyge vickymakesstuff
- 2.
- 3. 3 Product manager Illustrator andcalligrapher An Amazon customer Complex decision maker Has some organic intelligence Also once met Grumpy Cat IRL
- 4. DISCLAIMER The views expressedin 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
- 5. WHY WE AUTOMATE 5AMAZON.COMCONFIDENTIAL 5
- 6. 6 Customers should feelthe 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 startwith 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 STUDYIN CUSTOMER OBSESSION 8
- 9. 9 “I want youto 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 aprivilege, not a right We don’t have to send email.
- 11. HOW TO MAKEAN 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 socustomers can be served efficiently and at scale.
- 13.
- 14. DEFINITIONS Artificial Intelligence (AI) MachineLearning (ML) Automation 14
- 15. APPLICATIONS OF ML Healthcare Datasecurity 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 ML1,000,000,000,000,000,000 ,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 Datasecurity 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.
- 19. APPLICATIONS OF ML Healthcare Datasecurity 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 machinelearning so customers can receive recommendations they like, not recommendations we like.
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- 24. 24 Rob Haitani Amazon Outbound MarketingSummit, 2017
- 25. 25 Rudolf Arnheim, VisualThinking 1969 Rob Haitani Amazon Outbound Marketing Summit, 2017
- 26. MACHINE LEARNING ISNOT SO DIFFERENT FROM HUMAN LEARNING 26 Input data Find patterns Output results Rob Haitani Amazon Outbound Marketing Summit, 2017
- 27. HERE’S WHAT ANEURAL NET THINKS OF YOUR #SELFIE 27 http://karpathy.github.io/2015/10/25/selfie/ Rob Haitani Amazon Outbound Marketing Summit, 2017
- 28. 28 Rob Haitani Amazon Outbound MarketingSummit, 2017
- 29. TRAINING FOR PATTERNRECOGNITION 29 Visualizing and Understanding Convolutional Networks (Matthew Zeiler 2013) Rob Haitani Amazon Outbound Marketing Summit, 2017
- 30. WHAT ML THINKSOF YOUR SELFIE Amazon.com 30 53.1 67.3 Rob Haitani Amazon Outbound Marketing Summit, 2017
- 31. WHAT ML THINKSOF YOUR SELFIE 31 52.0 56.3 Rob Haitani Amazon Outbound Marketing Summit, 2017
- 32. FOR BETTER ORWORSE, ML REFLECTS HUMANS 32 Rob Haitani Amazon Outbound Marketing Summit, 2017
- 33. 33 Machine learning ispowerful … but only as powerful as your data set
- 34. SIMPLE AUTOMATION ALSOWORKS 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 ALSOWORKS 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 socaught up in the AI of tomorrow that you forget the BI of today … also known as “common sense”
- 37. 37 Reflections Email isa 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 focuson 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