Personalization Using AI/ML for Lodging
Publication date: August 25, 2022 (Diagram history)
With this architecture, you can personalize and improve the customer experience for lodging companies. Proactively recognize service changes and failures, recover from them, and interact with guests on their preferred channel. The solution uses Amazon Personalize for targeted offers, Amazon Pinpoint for multi-channel delivery, and Amazon SageMaker AI for custom artificial intelligence and machine learning (AI/ML) models.
Personalization AI/ML diagram
The following steps describe the architecture:
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Build on top of the operational data platform. Use Amazon Simple Storage Service as the data lake foundation. Ingest data from systems of record through AWS Transfer Family and AWS Data Exchange. Process data by using AWS Glue and Amazon EMR.
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Use Amazon Pinpoint to deliver operational communications over channels such as email, SMS, push, voice, or in-app messaging. Amazon Pinpoint stores all interactions with delivery status for tracking. Take into account customer channel preferences.
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Use Amazon Personalize to create segmentations, target lists, and personalized offers from data lake content. Use Amazon Pinpoint to deliver these offers based on customer preferences. Record all offers and customer interactions to refine future recommendations.
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Improve personalization effectiveness by using Master Data Management (MDM) integration. Unify guest profiles across systems of record.
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Create new AI/ML models for customer lifetime value, segmentation, and specialized offers. Use SageMaker AI and the raw and curated data in the data lakes. (Optional) Extend the capability by adding domains such as point of sale (POS) and survey systems.
Further reading
For additional information, see the following resources:
Diagram history
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| Change | Description | Date |
|---|---|---|
Initial publication | Reference architecture diagram first published. | August 25, 2022 |
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