(https://cloud.google.com/retail/docs/models)
The Retail API offers the following recommendation model types:
- Others You May Like
- Frequently Bought Together (shopping cart expansion)
- Recommended for You
- Similar Items
- Buy it Again
- On-sale
- Recently Viewed
- Page-Level Optimization
The Others You May Like recommendation predicts the next product that a user is mostlikely to engage or convert with. The prediction is based on the shopping and viewing history of the user and the candidate product's relevance to a current specified product.
Default optimization objective: click-through rate
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We could use something like this on HomePage
- Not sure how to use with Search/ Auto-suggestion
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Can be developed using directed graphs (currently using undirected) which preserves ORDER in product interaction.
The Frequently Bought Together recommendation predicts items frequently bought together for a specific product within the same shopping session. If a list of products is being viewed, then it predicts items frequently bought with that product list. This recommendation is useful when the user has indicated an intent to purchase a particular product (or list of products) already, and you are looking to recommend complements (as opposed to substitutes). This recommendation is commonly displayed on the "add to cart" page, or on the "shopping cart" or "registry" pages (for shopping cart expansion).
Default optimization objective: revenue per order
- We could compute an order embedding (aggregating embeddings of products in cart) exclude user-history, and perform a nearest neighbor search on product similiarity index.
The Recommended for You recommendation predicts the next product that a user is most likely to engage with or purchase, based on the shopping or viewing history of that user and contextual information of requests, such as timestamps. This recommendation is typically used on the home page.
Default optimization objective: click-through rate
- Perform a nearest neighbor search on product similiarity index using user-embedding.
The Similar Items recommendation predicts other products that have mostly similar attributes to the product being considered. This recommendation is typically used on a product detail page, or when a recommended product is out of stock.
- Find similar products by creating separate graph using only Also-View events (with filter on category and timestamp)
The Buy it Again model encourages purchasing items again based on previous recurring purchases. This personalized model predicts products that have been previously bought at least once and that are typically bought on a regular cadence. The interval at which a product is suggested depends on the product and site visitor. Recommendations from this model can be used on any page type. The Buy it Again model uses purchase-complete user events.
- Separately store products which are bought multiple times with same user-ids. Compute interval at which it is bought globally and on user level, recommend accordingly.