Webinar Slides

© 2020, Amazon Web Services, Inc. or its Affiliates. Summary • Centralized data lake allows for easier discovery and transformation of data for ML and Engagement • Work with IT team to discover key datasets • Contact AWS with your use case for potential PoC Support

• Slide Number 1
• Agenda
• Recap from Episode 1: Know Your Customers
• Responsibilities of a modern customer experience pipeline
• Ingesting data into AWS
• Challenges to making a secure data lake
• Robust data lake infrastructure with AWS
• Data ingestion options
• AWS Glue automates the undifferentiated heavy lifting of ETL
• Slide Number 10
• AWS Glue Crawlers and the AWS Glue Data Catalog
• Streaming with Amazon KinesisEasily collect, process, and analyze video and data streams in real time
• Amazon Kinesis Data Streams overview
• Amazon Kinesis Data Firehose overview
• AWS DataSync
• Data lake reference architecture
• Engage your audience
• User Engagement Challenges
• Users' expectations are continually evolving
• Stages of AWS User Engagement
• Customer touch points
• Slide Number 22
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• Slide Number 24
• Slide Number 25
• Overview: Amazon Personalize
• Successfully engage your customers using Amazon Pinpoint
• Solution Architecture: Predictive User Engagement
• Getting started with Amazon Personalize
• Setting up Amazon PersonalizeEasy three step process
• Add your datasets
• Create your solution (train your model)
• Create your solution (train your model) (1)
• Create your campaign (host your model)
• Getting started with Amazon Pinpoint
• Create your first segment
• Building a campaign
• Step 1 – Select Segment
• Select segment
• Step 2 – Select Channel
• Step 3 – Select Content
• Slide Number 42
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• Step 4 - Schedule
• Slide Number 46
• Automate multi-step campaigns with journeys
• Journeys UI
• Summary
• Resource
• LEARN MORE
• Thank you!