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Reference models

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Luigi’s Box offers a wide scale of standard recommender models. Each model needs to be trained first. Once set up, you will be given the recommender_type to use in recommendation requests described in the API section. Contact support to discuss the options in detail.

Each recommender is personalized for users who granted cookie consent. The models consider user preferences based on the sent user identifier (user_id) and boost products with characteristics similar to the user’s past interactions.

Model titlerecommender_typeDescriptionLocationInput
Testtest_recoSimple, most popular recommender to test client requests.ArbitraryNone
Similar productsitem_detail_alternativesSimilar/alternative products, preferring slightly more expensive ones (upsell).PDPproduct id, user id (optional)
Visually similar productsitem_detail_visual_alternativesVisually similar products based on product images.PDPproduct id, user id (optional)
Related complementary productsitem_detail_complementsProducts usually bought together (cross-sell), preferring cheaper products.PDPproduct id, user id (optional)
Basket popup complementsbasket_popupCross-sell for the most recently added basket item.Basket popupproduct id, user id (optional)
Basket complementsbasketCross-sell for all products in the basket.Basket detailproduct ids, user id (optional)
FavoritesfavoritesProducts most likely to be repeatedly bought. Suitable for consumable products.Homepage, basketuser id
Conversion-baseduser_conversion_basedProducts related to past purchases, or trends for new users.Homepage, 404user id
Click-baseduser_click_basedProducts similar to recently clicked but not bought items.Homepage, 404user id
Top category productscategoryTrending products from a specific category, diversified by subcategories.PLPcategory id, user id (optional)
Top brand productsbrandTrending products from a specific brand, diversified by categories.PLPbrand id, user id (optional)
Top user categoriestop_categoriesMost relevant categories for the user.Homepage, 404user id
TrendstrendsMost popular products overall.Homepage, 404user id (optional)
Novel productsnewsNovel products based on _introduced_at date.Homepage, PLPuser id (optional)
Novel products by labelnews_by_labelPopular products with "label": "is_new".Homepage, PLPuser id (optional)
Discounted productsdiscountDiscounted products based on price_amount and price_old_amount.Homepage, PLPuser id (optional)
Discounted by labeldiscount_by_labelPopular products with "label": "is_sale".Homepage, PLPuser id (optional)
Recently visitedlast_seenProducts most recently visited, excluding already bought ones.Arbitraryuser id
Recently visited (same category)item_detail_last_seenRecently visited products from the same category as the input product.Arbitraryuser id
Recently orderedrecently_orderedProducts most recently ordered by a user.Arbitraryuser id
Article related productsarticle_itemsMost relevant products based on an article/blog post.Article detailarticle id, user id (optional)
Article related articlesarticle_articlesMost relevant articles based on an article/blog post.Article detailarticle id, user id (optional)
Random productsrandomRandom products. More useful when combined with filters.Arbitraryuser id (optional)
Random novel productsrandom_newsRandom novel products, primarily up to 30 days old.Arbitraryuser id (optional)
Autocomplete popupautocomplete_popupPopular products, queries, categories for autocomplete init screen.Autocompleteuser id (optional)

Some industry segments have specific model adjustments:

SegmentModels adjustedKey difference
Books and gamesitem_detail_complements, basket, basket_popupDoes not prefer cheaper products; allows same-category recommendations
Food and beveragesitem_detail_complements, basket, basket_popup, last_seenPrefers previously bought products; includes already bought in last_seen
Luxury goods and jewelryitem_detail_complements, basket, basket_popupPrefers products of similar price
Pharma, cosmetics, body careitem_detail_complements, basket, basket_popup, last_seenPrefers products from more different categories; includes already bought in last_seen