User Based

The User Based algorithm recommends items by finding users similar to the current user. It generates recommendations based on user behavior and product popularity.

In this algorithm, product recommendations are based on the behavior of similar users (users with close similarity index scores: viewed, purchased, or added the same or similar category products to their cart) with the current user. The algorithm recommends products that similar users have encountered in the past but that the current user has not visited. The user-based algorithm also takes the user-product-rating matrix as another input. For each product a user visits, a rating is calculated based on the number of visits, purchases, and add-to-carts within the last 30 days. This type of algorithm can be used on every kind of page.

Endpoint

GET https://recommendation.api.useinsider.com/v2/user-based

Visit our Postman collection to test this request.

Query Parameters

Parameter	Sample Value	Description	Data Type	Required
partnerName	mybrand	Partner Identifier assigned by Insider One. You can use PartnerID as well.	String	Yes
locale	us_US	Locale of requested product catalog	String	Yes
platform	web	Requested platform. Web comes by default.	Enum	No
userId	a1b2c3d4	User identifier that is assigned by Insider One	String	Yes
currency	USD	Requested currency of the products. If no value is set, the default currency in your settings is used.	String	No
size	50	Required number of items in response. Valid values are 0 to 100.	Integer	No
categoryList	[“Clothes”, “Skirts”]	Category filter of the products	Array (of string)	No
filter		Smart Recommender filtering. There can be more than one filter parameter.	String	No
details	true	Adds details to the products of the response	Boolean	No
shuffle	false	Shuffles the products of the response	Boolean	No
getGroupProducts	false	Shows variant products under the products of the response	Boolean	No
groupProductsFields		Adds these fields to the variant products’ details	String	No
excludeVariants	true	Exclude variants from the response	Boolean	No
excludeViewDay	30	After how many days should viewed products be excluded	Integer	No (Can be used only with userId)
excludeViewItem	100	How many viewed products should be excluded	Integer	No (Can be used only with userId)
excludePurchaseDay	30	After how many days should purchased products be excluded	Integer	No (Can be used only with userId)
excludePurchaseItem	100	How many purchased products should be excluded	Integer	No (Can be used only with userId)
hp	false	Makes affinities affect products of the response	Boolean	No
dayLimit	2	If FMT is published_time, it adds a day limit filter	Integer	No
productId	ABC123CBA	Current product ID	String	No

Sample Request

The sample below displays a request to User Based, a personalized recommendation algorithm that finds users similar to the current user.

https://recommendation.api.useinsider.com/v2/user-based?partnerName={Partner_Name}&locale={Locale}&currency=TRY&userId={User ID}

Sample Response

{
        "success": true,
        "total": 10,
        "types": {
        "mvop": 10
        },
        "data": [
        "QAZ-7890",
        "XYZ-1234",
        "QAZ-7899",
        "XYZ-1233",
        "QAZ-7898",
        "XYZ-1243",
        "QAZ-7891",
        "XYZ-1223",
        "QAZ-7892",
        "XYZ-1342"
        ]
        }

Fallback Algorithms

If the products come from User Based are not enough to fill the response data, some fallback algorithms below fill it:

View-to-view of the last visited product
Most viewed of the category
Most viewed of the category without excluding the right-most item in the categoryList
Most viewed of the Partner