Recommendation offers a wide range of algorithms and filters suitable for various use cases.
Algorithm
Algorithms determine which items to recommend (such as the most popular items, items the user viewed in the past, and so on).
Filters
Additional filters you can apply based on product properties:
Only include: Recommend only products with a specific property (for example, items that cost more than $30).
Exclude: Never recommend products with a specific property (For example, never recommend items that are on sale).
Pin: Recommend only a specific product (For example, brand is Zara).
Recommendations Algorithm
Title | Description | Example | Algorithm Name | Best Page Placement | Fallback Behavior |
Best Sellers (Purchase) | Discover the items people consistently engage with the most. | “Our most-loved picks — people can’t get enough of these.” | Best-selling | Homepage | Fills with Most Popular and Newest |
Top Picks in Your Favorite Categories | Personalized suggestions from the categories you visit most. | “Since you explore this category often, here are recommended picks.” | Category Affinity | Homepage, Category Pages, Screener | Fills with Viewed with Recently Viewed, Most Popular and Newest |
Recommended for You (Based on Similar Users) | Suggestions informed by people with similar behavior or interests. | “People with similar interests also spent time with these options.” | Collaborative Filtering | Homepage, Product Detail Page, Watchlist Page | Fills with Most Popular and Newest |
Visually Similar Items | Items with similar appearance or visual attributes. | “Here are visually similar options you may find interesting.” | Image Similarity | Product Detail Page | Fills with Most Popular and Newest |
Popular Right Now | Items currently drawing the most overall interest. | “Popular right now — widely explored at the moment.” | Most Popular | Homepage, Category Page, Trending Page | Fills with Newest |
New Arrivals (Newest Products) | Fresh additions just introduced — be the first to explore. | “Just added — discover what’s new.” | Newest | Homepage | None |
Similar to What You Bought Before | New options aligned with your previous interests. | “New items that fit well with your past favorites.” | Product Affinity | Homepage, Product Page | Fills with Viewed with Recently Viewed, Most Popular and Newest |
Similar to This Item | Items with similar features, details, or characteristics. | “Options with similar attributes you might like.” | Product Similarity | Product Detail Page, Screener, Watchlist Page | Fills with Most Popular and Newest |
Co-Purchase (Often Purchased With) | Items frequently explored right after this one. | “People often pair this with the following options.” | Purchased Together | Product Page, Cart Page | Fills with Viewed Together, Most Popular and Newest |
Recommended Based on Your Orders (Session) | Suggestions based on what you explored during this session. | “Suggestions based on what you viewed today.” | Purchased With Recently Purchased |
| Fills with Purchased Together, Most Popular and Newest |
Just Purchased (Recently Purchased) | Items that were recently interacted with by others. | “Recently viewed or selected — happening now.” | Recently Purchased | Homepage, Product Page | None |
Your Recently Viewed Items (Click History) | Quickly return to items you looked at earlier. | “Here are the items you recently viewed.” | Recently Viewed | Product Page, Homepage | None |
You May Also Like (Best Alternatives) | Similar options thoughtfully matched to what you’re viewing. | “You may also like these similar options.” | Similarity | Product Page | Fills with Most Popular and Newest |
Recommended For You (Visitor Recommendations) | Personalized suggestions based on your recent activity. | “Recommended for you based on what you’ve been exploring.” | User Affinity | Homepage, Product Page | Fills with Most Popular and Newest |
What People Are Viewing Right Now | Live insights into what’s actively being explored at this moment. | “Popular right now — see what people are exploring today.” | Viewed Together | Homepage | Fills with Most Popular and Newest |
People Also Viewed | Items frequently viewed next by others. | “People who viewed this also explored these options.” | Viewed With Recently Viewed | Stock Detail Page (PDP), Homepage | Fills with Viewed Together, Most Popular and Newest |
Fallback logic for product recommendations
When the algorithm returns fewer products than required, a fallback mechanism ensures a seamless user experience by filling the gaps with alternative recommendations.
For example, User Affinity for users with no past behavior, or Viewed Together for items that were never viewed with other items in the same session. For these cases, this is the fallback logic.
Algorithm | Fallback | Fallback |
Category Affinity → | Viewed with Recently Viewed → | Most popular |
Product Affinity → | Viewed with Recently Viewed → | Most popular |
Keyword Similarity → | Viewed with Recently Viewed → | Most popular |
Purchased Together → | Viewed Together → | Most popular |
Viewed Together → | Most popular |
|
Viewed with Recently Viewed → | Viewed Together → | Most popular |
Purchased with Recently Purchased → | Purchased Together → | Most popular |
The following algorithms have no fallback: Recently Viewed and Recently Purchased
Recommendation Filters
When setting your recommendation strategy, you can add dynamic filtering to customize the algorithm. These filters are based on inclusion/exclusion/pin rules in addition to the algorithm chosen.
Name | Description |
Include | Only products that meet predefined conditions based on product attributes will be included in the product feed |
Exclude | Only products that do not meet predefined conditions based on their attributes will be excluded from the product feed. |
Pin | Specific products are pinned to the top based on predefined conditions related to their attributes. |
Recommendation using an API Call
You can use an API to retrieve product recommendations from Intempt and add them to your system. This allows you to display recommended products in your application, website, or any platform where you want to show personalized suggestions.
Response Format
The API returns the recommended products in JSON format.
Embed Code (Snippet)
Copy and edit the API snippet to customize the output as needed.
Adding Fields
The fields feature allows you to define which product attributes to display.
Use the "Add variable" button to include fields or remove them using the (X) icon.
This ensures product cards display only the most relevant information.
Parameters:
id: The feed ID used for recommendations.
quantity: The number of recommended items to return (default is 5).
fields: The product attributes to include in the response (default: title, image URL, and price).
Note: The product ID is required for recommendation cases, including:
Viewed together
Purchased together
Image similarity
Product similarity
Similarity
Collaborative filtering
In Shopify, Magento, the product ID is added automatically.
In IOS SDK, Android SDK, and Node JS SDK, users must manually add the product ID.