Product Recommendations Algorithms

Product algorithms work like a set of rules that applied to our recommendations engine will display the right products to each user.

Below we present how each algorithm works and what are its custom settings.

Abandoned basket products

For addtocart events we add items to user cart. Currently we do not support removing items from cart, but you can overwrite entire cart by passing checkout event with a list of items.

Best seller by Conversion Rate

Customize “days”: either 7 or 30 to give best seller by conversion rate from this period

{ “days”: 30 }

Best seller by Units

Customize “days”: either 7 or 30 to give best seller products from this period

{ “days”: 30 }

New products added

Customize “days”: either 7 or 30 to give new products added from this period

{ “days”: 30 }

Products Cross-Sell

This algorithm works based on an item related event: viewitem, addtocart, addtowishlist. Before using the algorithm, make sure you created a cross-sell under Setup and use it in algorithm settings.

You can use cross-sell algorithm to match multiple product attributes: category, type & brand. You can choose this attribute when you create the cross matrix in Setup -> Algorithms.

The value you enter for “cross” can also be a list: [“alg1”, “alg2”] or a simple value: “alg1”. In the case for lists, not finding any matching in the first value will fallback to check second algorithm.

Also, this algorithm allows for various strategy of matching elements: match from all values, match first value found on item, match first value found on cross matrix. This value will be set in algorithm params as “cross_type” and one of the following values: all, first_cross, first_item.

Recommendation: when applying a first_cross type algorithm is better to start from lower(smaller) categories up to main ones, in order to give better results. For example, start adding matching for Men Shoes Accessories, second for Men Shoes and leave at last Men category.


Products Upsell

More expensive products, based on the current product. Products from same category are considered.

Products related to search results. Items matching search query will be returned.

The most popular products within last days, based on entire shop activity.

Products from viewed categories

Based on the view category events, we are able to display products from those categories that are most relevant to the user.

User viewed products

Based on items viewed, we can display products that are most relevant to the user from the ones viewed.

Similar to basket products

We match other products to the ones from the cart

Products bought together

Our system analyses purchases and matches products that are usually bought together in the same purchase.

Products with best discounts

For users who are more inclined to purchase discounted products, we can display those with the best discount.

Product accessories (Other products matching specific fields from an Item)

This algorithm depends on information found in the product feed. You need to manually configure the feed, by adding a list of items that one product matches.

Last purchased

Products from last purchase.

Similar to last purchase

Products similar to last purchase.

Advanced settings for each algorithm

There are some common settings that can be customized for each algorithm. To edit those advanced settings, click the small cog button for each listed algorithm.

Change Results Order

Under each algorithm settings enter:

{ "sortBy": {"field_name": "asc"}}

Field_name can be any field from the product. Direction can be only “asc” or “desc”

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