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Amazon Personalize Developer Guide Amazon Personalize Developer Guide Amazon Personalize: Developer Guide Copyright © 2023 Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Amazon Personalize Developer Guide Table of Contents What is Amazon Personalize? .............................................................................................................. 1 Pricing for Amazon Personalize .................................................................................................... 1 Guidance for first-time users ....................................................................................................... 2 Discovering Amazon Personalize with the Magic Movie Machine ............................................... 2 Navigating this guide.......................................................................................................... 2 Related AWS services and solutions .............................................................................................. 3 Third-party services.................................................................................................................... 3 Learn more............................................................................................................................... 4 How it works..................................................................................................................................... 5 Amazon Personalize workflows .................................................................................................... 5 Workflow for Domain dataset groups................................................................................... 5 Workflow for Custom dataset groups ................................................................................... 6 Amazon Personalize terms .......................................................................................................... 7 Data import and management ............................................................................................. 7 Training ............................................................................................................................ 9 Model deployment and recommendations ........................................................................... 10 Amazon Personalize data.......................................................................................................... 11 Interactions data.............................................................................................................. 11 User data........................................................................................................................ 14 Item data........................................................................................................................ 15 Setting up Amazon Personalize .......................................................................................................... 18 Sign up for AWS ...................................................................................................................... 18 Regions and endpoints.............................................................................................................. 18 Setting up permissions .............................................................................................................. 19 Creating a new IAM policy ................................................................................................. 19 Creating an IAM role for Amazon Personalize ....................................................................... 20 Giving Amazon Personalize access to Amazon S3 resources .................................................... 21 Giving Amazon Personalize permission to use your AWS KMS key ........................................... 25 Setting up the AWS CLI ............................................................................................................ 27 Setting up the AWS SDKs .......................................................................................................... 28 Getting started ................................................................................................................................ 29 Getting started prerequisites ..................................................................................................... 29 Creating the training data (Domain dataset group) ............................................................... 30 Creating the training data (Custom dataset group) ............................................................... 30 Getting started with a Domain dataset group .............................................................................. 31 Getting started with a Domain dataset group (console) ......................................................... 31 Getting started with a Domain dataset group (SDK for Java 2.x) ............................................. 36 Getting started with a Domain dataset group (SDK for Python (Boto3)) ................................... 42 Getting started with a Custom dataset group .............................................................................. 46 Getting started (console) ................................................................................................... 46 Getting started (AWS CLI) ................................................................................................. 54 Getting started (SDK for Python (Boto3)) ............................................................................ 61 Getting started (SDK for Java 2.x) ...................................................................................... 65 Cleaning up resources ............................................................................................................... 73 Cleaning up domain-based resources .................................................................................. 73 Cleaning up custom resources ............................................................................................ 74 Datasets and schemas....................................................................................................................... 75 Schema formatting requirements............................................................................................... 75 Schema data types ........................................................................................................... 76 Domain datasets and schemas................................................................................................... 76 VIDEO_ON_DEMAND datasets and schemas ......................................................................... 77 ECOMMERCE datasets and schemas .................................................................................... 82 Custom datasets and schemas................................................................................................... 87 Custom dataset and schema requirements ........................................................................... 87 iii Amazon Personalize Developer Guide Interactions dataset requirements ...................................................................................... 89 Users dataset requirements ............................................................................................... 90 Items dataset requirements ............................................................................................... 91 Creating a schema using Python ........................................................................................ 93 Domain dataset groups..................................................................................................................... 94 Creating a Domain dataset group ............................................................................................... 95 Creating a Domain dataset group and importing interaction data (console) .............................. 95 Creating a Domain dataset group and importing interaction data (AWS CLI) ............................. 97 Creating a Domain dataset group and importing interaction data (AWS SDKs) ......................... 100 Creating recommenders........................................................................................................... 108 Choosing recommender use cases ..................................................................................... 108 Minimum recommendation requests per second and auto-scaling ......................................... 112 Creating recommenders (console) ..................................................................................... 113 Creating recommenders (AWS CLI) .................................................................................... 114 Creating recommenders (AWS SDKs) ................................................................................. 114 Evaluating a recommender ...................................................................................................... 116 Retrieving metrics........................................................................................................... 116 Metric definitions........................................................................................................... 118 Example........................................................................................................................ 119 Additional resources........................................................................................................ 120 Getting recommendations from a recommender ......................................................................... 120 Getting recommendations with a recommender (console) .................................................... 120 Getting recommendations with a recommender (AWS CLI) ................................................... 121 Getting recommendations with a recommender (AWS SDKs) ................................................ 121 Promoting items............................................................................................................. 123 Managing Domain dataset group resources ................................................................................ 128 Creating datasets............................................................................................................ 129 Managing data............................................................................................................... 129 Managing recommenders................................................................................................. 131 Maintaining recommendation relevance ..................................................................................... 135 Custom dataset groups ................................................................................................................... 137 Determining your use case ....................................................................................................... 137 Amazon Personalize use cases .......................................................................................... 137 What data to import ....................................................................................................... 138 Preparing and importing data .................................................................................................. 138 Step 1: Creating a Custom dataset group .......................................................................... 139 Step 2: Creating a dataset and a schema ........................................................................... 142 Step 3: Importing your historical data .............................................................................. 147 Creating a solution ................................................................................................................. 168 Step 1: Choosing a recipe ................................................................................................ 168 Step 2: Configuring a solution.......................................................................................... 204 Step 3: Creating a solution version ................................................................................... 217 Step 4: Evaluating a solution version with metrics .............................................................. 223 Creating a campaign ............................................................................................................... 228 Minimum provisioned TPS ............................................................................................... 229 Creating a campaign (console) .......................................................................................... 229 Creating a campaign (AWS CLI) ........................................................................................ 230 Creating a campaign (AWS SDKs) ..................................................................................... 231 Updating a campaign...................................................................................................... 233 Getting recommendations....................................................................................................... 235 Recommendation scores.................................................................................................. 235 Getting real-time recommendations .................................................................................. 235 Getting batch recommendations and user segments ........................................................... 249 Maintaining recommendation relevance ..................................................................................... 263 Keeping datasets current ................................................................................................. 263 Keeping solution versions up to date ................................................................................ 264 Recording events............................................................................................................................ 266 iv Amazon Personalize Developer Guide Requirements for recording events and training a model ............................................................. 266 How real-time events influence recommendations ...................................................................... 267 Creating an event tracker ........................................................................................................ 267 Recording events with the PutEvents operation .......................................................................... 269 Recording events for anonymous users ...................................................................................... 273 Recording impressions data ..................................................................................................... 273 Event metrics and attribution reports ....................................................................................... 274 Sample Jupyter notebook ........................................................................................................ 275 Sample implementations......................................................................................................... 276 Exporting a dataset ........................................................................................................................ 277 Dataset export job permissions requirements ............................................................................. 277 Service role policy for exporting a dataset ......................................................................... 278 Amazon S3 bucket policy for exporting a dataset ............................................................... 278 Creating a dataset export job (console) ..................................................................................... 279 Creating a dataset export job (AWS CLI) .................................................................................... 279 Creating a dataset export job (AWS SDKs) ................................................................................. 280 Filtering results.............................................................................................................................. 283 Filter expressions.................................................................................................................... 283 Creating filter expressions ............................................................................................... 284 Filter expression examples ............................................................................................... 286 Filtering real-time recommendations ......................................................................................... 288 Filtering real-time recommendations (console) ................................................................... 289 Filtering real-time recommendations (AWS CLI) .................................................................. 293 Filtering real-time recommendations (AWS SDKs) ............................................................... 294 Filtering batch recommendations and user segments .................................................................. 298 Providing filter values in your input JSON ......................................................................... 298 Filtering batch workflows (console) ................................................................................... 299 Filtering batch workflows (AWS SDKs) ............................................................................... 299 Measuring impact of recommendations ............................................................................................. 301 Guidelines and requirements .................................................................................................... 301 Giving Amazon Personalize access to CloudWatch ............................................................... 302 Giving Amazon Personalize access to your Amazon S3 bucket ............................................... 303 Creating a metric attribution .................................................................................................... 304 Creating a metric attribution (console) .............................................................................. 304 Creating a metric attribution (AWS CLI) ............................................................................. 305 Creating a metric attribution (AWS SDKs) .......................................................................... 306 Managing a metric attribution .................................................................................................. 307 Updating a metric attribution .......................................................................................... 308 Deleting a metric attribution ............................................................................................ 311 Publishing and viewing results ................................................................................................. 312 Viewing metrics in CloudWatch ........................................................................................ 312 Publishing metrics to Amazon S3 ..................................................................................... 313 Tagging resources........................................................................................................................... 317 Managing tags....................................................................................................................... 317 Additional information.................................................................................................... 318 Adding tags to Amazon Personalize resources ............................................................................ 318 Adding tags (console) ...................................................................................................... 318 Adding tags (AWS CLI) .................................................................................................... 319 Adding tags (AWS SDKs) .................................................................................................. 319 Using tags in IAM policies................................................................................................ 322 Using tags in IAM policies........................................................................................................ 322 Troubleshooting ............................................................................................................................. 325 Frequently asked questions ...................................................................................................... 325 Data import and management ......................................................................................... 325 Creating a solution and solution version (Custom dataset group) .......................................... 326 Model deployment (Custom dataset group campaigns) ........................................................ 326 Recommendations.......................................................................................................... 327 v Amazon Personalize Developer Guide Filtering recommendations.............................................................................................. 327 Error messages....................................................................................................................... 328 Data import and management ......................................................................................... 328 Creating a solution and solution version (Custom dataset group) .......................................... 328 Model deployment (Custom dataset group campaigns) ........................................................ 329 Recommenders (Domain dataset group) ............................................................................ 329 Recommendations.......................................................................................................... 329 Filtering recommendations.............................................................................................. 329 Specifying resources with AWS CloudFormation ................................................................................. 331 Amazon Personalize and AWS CloudFormation templates ............................................................ 331 Example AWS CloudFormation templates for Amazon Personalize resources ................................... 331 CreateDatasetGroup........................................................................................................ 332 CreateDataset................................................................................................................ 332 CreateSchema................................................................................................................ 333 CreateSolution............................................................................................................... 333 Learn more about AWS CloudFormation .................................................................................... 334 Security......................................................................................................................................... 335 Data protection...................................................................................................................... 335 Data encryption............................................................................................................. 336 Identity and access management .............................................................................................. 337 Audience....................................................................................................................... 337 Authenticating with identities.......................................................................................... 337 Managing access using policies ......................................................................................... 339 How Amazon Personalize works with IAM .......................................................................... 341 Cross-service confused deputy prevention ......................................................................... 344 Identity-based policy examples ........................................................................................ 344 Troubleshooting............................................................................................................. 348 Logging and monitoring.......................................................................................................... 350 Monitoring..................................................................................................................... 350 CloudWatch metrics for Amazon Personalize ...................................................................... 353 Logging Amazon Personalize API calls with AWS CloudTrail .................................................. 356 Compliance validation............................................................................................................. 357 Resilience.............................................................................................................................. 358 Infrastructure security............................................................................................................. 358 Endpoints and quotas..................................................................................................................... 359 Amazon Personalize endpoints and regions ............................................................................... 359 Compliance............................................................................................................................ 359 Service quotas........................................................................................................................ 359 Requesting a quota increase .................................................................................................... 363 API reference................................................................................................................................. 364 Actions.................................................................................................................................. 364 Amazon Personalize........................................................................................................ 366 Amazon Personalize Events .............................................................................................. 539 Amazon Personalize Runtime ........................................................................................... 545 Data Types............................................................................................................................ 554 Amazon Personalize........................................................................................................ 555 Amazon Personalize Events .............................................................................................. 664 Amazon Personalize Runtime ........................................................................................... 670 Common Errors...................................................................................................................... 673 Common Parameters.............................................................................................................. 675 Document history........................................................................................................................... 677 AWS glossary................................................................................................................................. 683 vi Amazon Personalize Developer Guide Pricing for Amazon Personalize What is Amazon Personalize? Amazon Personalize is a fully managed machine learning service that uses your data to generate item recommendations for your users. It can also generate user segments based on the users' affinity for certain items or item metadata. Common use case examples include the following: • Personalizing a video streaming app – You can use preconfigured or customizable Amazon Personalize resources to add multiple types of personalized video recommendations to your streaming app. For example, Top picks for you, More like X and Most popular video recommendations. • Adding product recommendations to an ecommerce app – You can use preconfigured or customizable Amazon Personalize resources to add multiple types of personalized product recommendations to your retail app. For example, Recommended for you, Frequently bought together and Customers who viewed X also viewed product recommendations. • Creating personalized emails – You can use customizable Amazon Personalize resources to generate batch recommendations for all users on an email list. Then you can use an AWS service (p. 3) or third party service (p. 3) to send users personalized emails recommending items in your catalog. • Creating a targeted marketing campaign – You can use Amazon Personalize to generate segments of users who will most likely interact with items in your catalog. Then you can use an AWS service (p. 3) or third party service (p. 3) to create a targeted marketing campaign that promotes different items to different user segments. Amazon Personalize includes API operations for real-time personalization, and batch operations for bulk recommendations and user segments. You can get started quickly with use-case optimized recommenders for your business domain, or you can create your own configurable custom resources. With Amazon Personalize, your data can come from both your historical bulk interaction records in a CSV file, and real-time events from your users as they interact with your catalog. Before Amazon Personalize can generate recommendations, your interactions data must have: • At minimum 1000 interactions records from users interacting with items in your catalog. These interactions can be from bulk imports, or streamed events, or both. • At minimum 25 unique user IDs with at least 2 interactions for each. Different use cases may have additional data requirements. If you don't have enough data, you can use Amazon Personalize to first collect real-time event data. After you have recorded enough events, Amazon Personalize can generate recommendations. Topics • Pricing for Amazon Personalize (p. 1) • Guidance for first-time Amazon Personalize users (p. 2) • Related AWS services and solutions (p. 3) • Third-party services (p. 3) • Learn more (p. 4) Pricing for Amazon Personalize With Amazon Personalize, there are no minimum fees and no upfront commitments. The AWS Free Tier provides a monthly quota of up to 20 GB of data processing per available AWS region, up to 100 hours 1 Amazon Personalize Developer Guide Guidance for first-time users of training time per eligible AWS region, and up to 50 TPS-hours of real-time recommendations/month. The free tier is valid for the first two months of usage. For a complete list of charges and prices, see Amazon Personalize pricing. Guidance for first-time Amazon Personalize users If you're a first-time user of Amazon Personalize, the following resources can help you get started. Topics • Discovering Amazon Personalize with the Magic Movie Machine (p. 2) • Navigating this guide (p. 2) Discovering Amazon Personalize with the Magic Movie Machine The Magic Movie Machine is an interactive learning experience. It helps you discover Amazon Personalize features and learn more about generating recommendations. For a short introduction, see the video below. Then try the Magic Movie Machine. Getting Started with Amazon Personalize Navigating this guide We recommend you read the following sections in order: 1. How it works (p. 5) – This section introduces the Amazon Personalize workflow and walks you through the steps to create personalized experiences for your users. This section also includes common Amazon Personalize terms and their definitions. Start with this section to make sure you have good understanding of Amazon Personalize workflows and terms before you start getting recommendations. 2. Setting up Amazon Personalize (p. 18) – In this section you set up your AWS account, set up the required permissions to use Amazon Personalize, and set up the AWS CLI and the AWS SDKs to use and manage Amazon Personalize. 3. Getting started (p. 29) – In this section you get started using Amazon Personalize with a simple movie dataset. Complete these tutorials to get hands-on experience with Amazon Personalize. You can choose to either get started with a Domain dataset group or a Custom dataset group: • To get started creating a Domain dataset group, complete the Getting started prerequisites (p. 29) and then start the tutorials in Getting started with a Domain dataset group (p. 31). • To get started with a Custom dataset group, complete the Getting started prerequisites (p. 29) and then start the tutorials in Getting started with a Domain dataset group (p. 31). 4. Depending on your application, complete either of the following sections: • Domain dataset groups (p. 94) – If you have a streaming video or ecommerce application, follow the procedures in this section to create a Domain dataset group and recommenders for your use cases. These procedures build upon what you learned when completing the Domain dataset group getting started exercises. They provide more in-depth information about recommenders and domain use cases. • Custom dataset groups (p. 137) – If you don't have a streaming video or ecommerce application, follow the procedures in this section to create a Custom dataset group. These procedures build 2 Amazon Personalize Developer Guide Related AWS services and solutions upon what you learned when completing the Custom dataset group getting started exercises. They provide more in depth information about custom recipes and models. 5. Recording events (p. 266) – This section covers how to record user interaction events in real time. After you have set up your Amazon Personalize resources, complete this section to learn how to keep your Interactions dataset up to date with your users' behavior. You do this by recording interaction events with an event tracker and the PutEvents (p. 540) operation. 6. Filtering recommendations and user segments (p. 283) – This section covers how to filter recommendations. Complete this section to learn how to construct filter expressions to filter recommendations based on custom criteria. For example, you might not want to recommend products that a user has already purchased, or recommend movies that a user has already watched. Related AWS services and solutions Amazon Personalize integrates seamlessly with other AWS services and solutions. For example, you can: • Use AWS Amplify to record user interaction events. Amplify includes a JavaScript library for recording events from web client applications, and a library for recording events in server code. For more information, see Amplify - analytics. • Automate and schedule Amazon Personalize tasks with Maintaining Personalized Experiences with Machine Learning. This AWS Solutions Implementation automates the Amazon Personalize workflow, including data import, solution version training, and batch workflows. • Use Amazon CloudWatch Evidently to perform A/B testing with Amazon Personalize recommendations. For more information, see Perform launches and A/B experiments with CloudWatch Evidently in the Amazon CloudWatch User Guide. • Use Amazon Pinpoint to create targeted marketing campaigns. For an example that shows how to use Amazon Pinpoint and Amplify to add Amazon Personalize recommendations to a marketing email campaign and a web app, see Web Analytics with Amplify. Third-party services Amazon Personalize works well with various third-party services. • Amplitude – You can use Amplitude to track user actions to help you understand your users' behavior. For information on using Amplitude and Amazon Personalize, see the following AWS Partner Network (APN) blog post: Measuring the Effectiveness of Personalization with Amplitude and Amazon Personalize. • Braze – You can use Braze to send users personalized emails recommending items in your catalog. Braze is a market leading messaging platform (email, push, SMS). For a workshop that shows how to integrate Amazon Personalize and Braze, see Amazon Personalize workshop. • mParticle – You can use mParticle to collect event data from your app. For an example that shows how to use mParticle and Amazon Personalize to implement personalized product recommendations, see How to harness the power of a CDP for machine learning: Part 2. • Optimizely – You can use Optimizely to perform A/B testing with Amazon Personalize recommendations. For information on using Optimizely and Amazon Personalize, see Optimizely integrates with Amazon Personalize to combine powerful machine learning with experimentation. • Segment – You can use Segment to send your data to Amazon Personalize. For more information on integrating Segment with Amazon Personalize, see Amazon Personalize Destination. For a complete list of partners, see Amazon Personalize Partners. 3 Amazon Personalize Developer Guide Learn more Learn more The following resources provide additional information about Amazon Personalize: • For a quick reference to help you determine if Amazon Personalize fits your use case, see the Amazon Personalize Cheat Sheet in the Amazon Personalize samples repository. • For a series of videos on how to use Amazon Personalize, see the Amazon Personalize Deep Dive Video Series found on YouTube. • For in-depth tutorials and code samples, see the amazon-personalize-samples GitHub repository. 4

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