Retail Marketing with Machine Learning & Amazon Rekognition (RET205) - AWS re:Invent 2018

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Retailers need to create individually tailored experiences to delight customers while more and more companies are leveraging technology to do so. In this chalk talk, we whiteboard the architecture and demonstrate Amazon Rekognition to understand how to automate the process of building personalized marketing solutions using ML-based machine vision and gather consumer insights using visualization tools. Audience participation is encouraged through a Q&A for retail marketing use cases like customer mood analysis, celebrity product placement marketing with social media, and store traffic analysis to drive merchandising decisions, planogram decisions, and overall product placement.

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Retail Marketing with Machine
Learning and Amazon Rekognition
Simon Treacy
Solution Architect
AWS
R E T 2 0 5
Jignesh Desai
Partner Solution Architect
AWS
Krithika Ganesamoorthi
Partner Solution Architect
AWS

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
500,000,000
More than
tweets per day

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
500,000,000
More than
tweets per day
>1,000,000,000,000 since July 2013

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Retail marketing trends
AWS Digital Transformation Building Blocks
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Video analytics will bring us closer to the consumer
Amazon Rekognition

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Deep learning-based image and video analysis
• Object, scene, and activity detection
• Facial recognition
• Facial analysis
• Person tracking
• Unsafe content detection
• Text in images

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Frictionless experiences

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
ID by license plate
(Pickup at Amazon Fresh store)

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Architecture—Amazon Rekognition Video
Live Feed
Notification
AWS Cloud
Processing and Notification
Capture and Classification

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Architecture—Amazon Rekognition
Notification
Live Feed
AWS Cloud
Web UI
Capture and Notification
Storage and Display
Classification

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Architecture—Amazon SageMaker
AWS Cloud
Web UI
Storage and Modeling
End point with Recommendation
Notification

Thank you!
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Simon Treacy
streacy@amazon.com
Jignesh Desai
jigned@amazon.com
Krithika Ganesamoorthi
kganesam@amazon.com

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
https://github.com/aws-samples/amazon-rekognition-
video-analyzer

© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
https://aws.amazon.com/blogs/machine-learning/shopper-
sentiment-analyzing-in-store-customer-experience/
https://amzn.to/2QHlH6Q

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