Implementing Recommendations
Steps
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Set up a project
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Import your product catalog You can add items to your Recommendations AI product catalog individually by using the import Files or API.
Information of the products sold to customers. This includes the product title, description, in stock availability, pricing, and so on.
- Record user events User events track user actions such as clicking on a product, adding an item to a shopping cart, or purchasing an item, and so on. Recommendations AI relies on user event data in order to generate personalized recommendations. User events need to be ingested in real time to accurately reflect the behavior of your users.
End user behavior on your website. This includes users searching for, viewing, or purchasing a specific item, your website showing users a list of products, and so on.
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Determine your recommendation types and placements Reviewing the available recommendation types, optimization objectives, and other model tuning options to determine the best options for your business objectives. The location of the recommendation panel and the objective for that panel impact model tuning.
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Import historical user events Your models need sufficient training data before they can provide accurate predictions.
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Create your model After you have met the data requirements, create your model to initiate model training and tuning.
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Create your placements and preview your recommendations After your model has been activated, you can create your placements and preview the recommendations from your model to ensure your setup is functioning as expected.
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Set up an A/B experiment (Optional) You can compare the performance of your website with Recommendations AI recommendations to a baseline version of your website without Recommendations AI recommendations.
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Evaluate your model You can associate recommendations and user events and Recommendations AI provides reporting of metrics to help you determine how incorporating the recommendations is affecting your business, then view recommendation metrics for your project in the Dashboard.
You can upload and manage product catalog information and user event logs for your websites. Recommendations AI uses this information to train and update recommendation models.
Recommendation model types
When you request recommendations from Recommendations AI, you provide the placement value, which determines which model is used to return your recommendations.
| Model type | Optimization objective | placement | User event types | Minimum data requirement | Data collection window |
|---|---|---|---|---|---|
| Recommended for you | Click-through rate | home_page | detail-page-view add-to-cart purchase-complete home-page-view |
1 week, with an average of 10 detail-page-view events per joined catalog item.OR60 days with at least one joined detail-page-view event. |
3 months |
| Recommended for you | Conversion rate | home_page | detail-page-view add-to-cart purchase-complete home-page-view |
1 week, with an average of 10 add-to-cart events per joined catalog item.OR60 days with at least one joined add-to-cart event. |
3 months |
| Others you may like | Click-through rate | product_detail | detail-page-view |
1 week, with an average of 10 detail-page-view events per joined catalog item.OR60 days with at least one joined detail-page-view event. |
3 months |
| Others you may like | Conversion rate | product_detail | add-to-cart detail-page-view |
1 week, with an average of 10 add-to-cart events per joined catalog item.OR60 days with at least one joined add-to-cart event. |
3 months |
| Frequently bought together | revenue per order | shopping_cart | purchase-complete detail-page-view |
An average of 10 purchase-complete events per joined catalog item.OR90 days of purchase-complete events. |
12 months |
User events
Event type priority
| Priority | User Events |
|---|---|
| Required for initial live experiment | add-to-cart, detail-page-view, home-page-view, purchase-complete |
| Important for improving model quality over time | checkout-start, category-page-view, remove-from-cart, search, shopping-cart-page-view |
| Nice to have | add-to-list, page-visit, refund, remove-from-list |
User event type examples and schemas
Hadoop/Bigquery/Snowflake/Redshift