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Guidance for Retail Personalization on AWS

Overview

This Guidance helps you offer personalized experiences and interactions to shoppers through machine learning (ML) services, so you can increase revenue and sales. The Guidance provides a fully automated, end-to-end architecture that ingests data and trains ML models. Additionally, this architecture provides APIs for adding near real time personalized product recommendations to digital commerce mobile applications and portals.

How it works

This architecture augments different e-commerce backends by integrating Amazon Personalize as a product recommendation engine.

Download the architecture diagram

Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

This Guidance is designed to be fully scalable and automated. The serverless architecture does not require human intervention to run MLOps and an ML lifecycle. You can enable CloudWatch logging and metrics on supported services to monitor usage and failures.

Read the Operational Excellence whitepaper 

This architecture uses IAM policy best practices, such as least privilege access to resources. For example, when using the DynamoDB resolver, this architecture employs IAM roles that provide the most restrictive view to resources, such as your DynamoDB tables. 

Read the Security whitepaper 

This architecture uses serverless and managed services such as Amazon S3, Step Functions, and DynamoDB. These services automatically recover from failures, scale to increase workload availability, and provision resources based on demand.

Read the Reliability whitepaper 

This architecture scales to meet performance requirements for high capacity events, such as Prime Day or Black Friday. When Amazon Personalize returns recommended SKUs during these events, the e-commerce application needs to obtain the right metadata. DynamoDB and Amazon DynamoDB Accelerator (DAX) retrieve metadata from recommended SKUs and returns responses within microseconds.

Read the Performance Efficiency whitepaper 

With serverless and managed services in this architecture, you pay only for the computing resources required to run your workloads. Additionally, Lambda, AWS AppSync, and Step Functions remove the operational burden of managing both operating systems and instances to run code. 

Read the Cost Optimization whitepaper 

This architecture reduces the amount of resources consumed by using serverless services that automatically scale based on demand.

Read the Sustainability whitepaper 

Related Content

AWS Guidance for Retail Use Cases

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

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