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How Product Logics Work

Details on their functionality and the endpoints they use.

Clerk is built around a powerful API that offers many different ways to display results to customers. These are called Product Logics and offer various functionalities suited to different use cases.

This article explains the available logics for Email and how they work.

The names of these Product Logics match what you see in the my.clerk.io backend when using Content. Each of them has a matching Endpoint in Clerk’s API, which you can inspect in our developer docs using the links provided below.

Best Sellers #

Endpoint: recommendations/popular

Displays the most popular products in your store, specifically those that have been included in the most orders over an extended period. The quantity of the same product in each order doesn’t impact this ranking. It generally remains the same for longer periods as long as you maintain the same products in stock.

Hot Products #

Endpoint: recommendations/trending

Highlights items that have had a recent increase in sales. There’s no fixed timeframe - instead, it’s dynamically calculated based on changes in product sales. For example, if a product typically sells three times a week but suddenly sells 20 times in two days, it’s identified as trending.

Newest Products #

Endpoint: recommendations/new

Shows items that were most recently added to your store, with the latest ones shown first. It requires either the “age” or “created_at” attribute to be available on the products.

Best Sellers In Category #

Endpoint: recommendations/category/popular

Displays the most popular products within a specific category.

Hot Product In Category #

Endpoint: recommendation/category/trending

Highlights products that have recently seen an increase in sales within a specific category.

Newest Products In Category #

Endpoint: recommendations/category/new

Displays the latest products added to a specific category, sorted by the newest items first. This requires either the “age” or “created_at” attribute to be present on products.

Best Alternative Products #

Endpoint: recommendations/substituting

Shows the closest similar items to the product being viewed, sorted by popularity. It compares products based on available attributes such as name, brand, category, price, and other relevant data.

Fallbacks #

If an unknown product ID is provided, Visitor Recommendations are shown. If the visitor is unknown, Best Sellers are shown.

Best Cross-Sell Products #

Endpoint: recommendations/complementary

Displays items most likely to be bought with the product being viewed. It considers products that are commonly bought together and those that are likely to complement each other, such as a belt with pants.

It does this by analyzing typical buying patterns to display suitable recommendations, even for products that have yet to be bought together.

E.g. if it’s normal to buy a pair of footbal boots and shinguards in the same brand and color, Clerk will prioritise these pairs for all brands and colors even if they have not sold together yet.

Fallbacks #

If an unknown product ID is provided, Visitor Recommendations are shown. If the visitor is unknown, Best Sellers are shown.

Most Sold With #

Endpoint: recommendations/most_sold_with

Identifies products that have been frequently purchased alongside any given product or set of products. This logic is simpler than Best Cross-Sell Products, as it only counts items that have been sold with the specified product(s), without predicting anything.

Recommendations Based On Keywords #

Endpoint: recommendations/keywords

Displays products that match a specific keyword or phrase, sorted by their sales performance.

Specific Products #

Does not have an endpoint as it is exclusive to my.clerk.io.

Displays exactly the products specified. If at any point the Number of products is higher than the selected product, the results will be supplemented with Best Sellers.

This also happens if some selected products are removed from Clerk, like when they go out of stock.

Visitor Recommendations #

Endpoint: recommendations/visitor/complementary

Shows products that a visitor is most likely to buy based on their recent browsing. It combines cross-sell and alternative recommendations to find the best matches for each visitor.

Fallbacks #

If the visitor is unknown, Best Sellers are shown.

Visitor Alternatives #

Endpoint: recommendations/visitor/substituting

Displays similar products that are likely to be bought by a visitor, based on their recent browsing history.

Fallbacks #

If the visitor is unknown, Best Sellers are shown.

Visitor Click History #

Endpoint: recommendations/visitor/history

Shows the exact products a visitor has clicked on.

Fallbacks #

Best Sellers are shown when the visitor is unknown.

Recommendations Based On Orders #

Endpoint: recommendations/customer/complementary

Displays products a customer is most likely to buy, based on their past purchases. It combines cross-sell and alternatives to find the best recommendations.

Fallbacks #

If the customer is unknown, Visitor Recommendations are shown. If the visitor is unknown, Best Sellers are shown.

Similar To Order History #

Endpoint: recommendations/customer/substituting

Displays similar items that a customer is most likely to buy, based on their past purchases.

Fallbacks #

If the customer is unknown, Visitor Recommendations are shown. If the visitor is unknown, Best Sellers are shown.

Customer Order History #

Endpoint: recommendations/customer/history

Displays the exact products a customer has bought.

Fallbacks #

Best Sellers are shown when the visitor is unknown.

What Customers Look At Right Now #

Endpoint: recommendations/currently_watched

Shows the most recently clicked products by any visitor on the website.

Recently Purchased Products #

Endpoint: recommendations/recently_bought

Displays items most recently bought by any customer on the website.

Best Page Alternatives #

Endpoint: recommendations/page/substituting

Suggests similar pages to the one currently viewed. It analyzes each pages body of text to identify keywords associated with other relevant pages.

Endpoint: recommendations/page/product

Finds the best matching pages for the product being viewed. It analyzes the products data and compares it to pages that mention the product or related concepts.

Endpoint: recommendations/page/category

Finds the best matching pages for the category being viewed. It analyzes the category’s data and compares it to pages mentioning the category or related concepts.

Endpoint: recommendations/page/related_products

Shows the best-matching products for the page being viewed, sorted by popularity. It analyzes page text to identify keywords relevant to specific products.

Endpoint: recommendations/page/related_categories

Finds the best-matching categories for the page being viewed, sorted by the popularity of the products within them. It analyzes page text to find keywords associated with specific categories.