E-Commerce Category Recommendation API

API ID 837

This API will recommend categories that are related to any text string that you pass to it. Ideal for cross-selling.

100% uptime 451 ms avg response

About the API:

This API will recommend e-commerce categories based on a search text string. This is a good fit for cross-seeling, where you can recommend other products and categories to a user based on their search. 

 

What this API receives and what your API provides (input/output)?

This API will receive a text string and it will deliver all possible categories that could match that search. 

 

What are the most common uses cases of this API?

 

Cross-Selling:
Cross-selling is the process of offering customers products that are compatible with the ones they're purchasing. 

 

Are there any limitations to your plans?

Besides API call limitations per month, there are no other limitations. 

API Documentation

Endpoints

Request

Recommend highly related categories for e-commerce and other uses.

 
Endpoint ID: 607
GET https://pr213-testing.zylalabs.com/api/837/e-commerce+category+recommendation+api/607/get+recommendations
INPUT PARAMETERS

Get Recommendations — Endpoint Features

Object Description
text Required Enter some text to find related categories:

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

text
API EXAMPLE RESPONSE
JSON
{"keywords":["coffee","maker"],"categories":["Coffee Maker Water Filters","Coffee Maker & Espresso Machine Accessories","Coffee","Pasta Maker Accessories","Popcorn Maker Accessories","Yogurt Maker Accessories","Pasta Maker Attachments","Coffee Cakes","Coffee Cups","Coffee Filters"],"keywords_scored":{"coffee":1,"maker":1},"categories_scored":{"Coffee Maker Water Filters":0.06249552,"Coffee Maker & Espresso Machine Accessories":0.04945657066666667,"Coffee":0.04701960266666667,"Pasta Maker Accessories":0.03924382666666667,"Popcorn Maker Accessories":0.03924382666666667,"Yogurt Maker Accessories":0.03924382666666667,"Pasta Maker Attachments":0.03924382666666667,"Coffee Cakes":0.038602158,"Coffee Cups":0.038602158,"Coffee Filters":0.038602158},"taxonomy_set":"product_categories","version":"7.5.7","author":"twinword inc.","email":"[email protected]","result_code":"200","result_msg":"Success"}
Get Recommendations — CODE SNIPPETS

curl --location --request GET 'https://pr213-testing.zylalabs.com/api/837/e-commerce+category+recommendation+api/607/get+recommendations?text=coffee maker' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the E-Commerce Category Recommendation API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Minimum annual contract: USD 10,000

Trusted by leading companies

E-Commerce Category Recommendation API FAQs

The Get Recommendations endpoint returns a JSON object containing recommended categories based on the input text string. It includes keywords, a list of related categories, and scored values indicating the relevance of each category.

The key fields in the response include "keywords" (input terms), "categories" (recommended categories), "keywords_scored" (relevance scores for each keyword), and "categories_scored" (relevance scores for each category).

The response data is structured as a JSON object. It contains arrays for keywords and categories, along with nested objects for scored values, making it easy to parse and utilize in applications.

The endpoint provides information on related e-commerce categories based on user input, including potential cross-selling opportunities and relevant product categories.

Users can customize their requests by varying the input text string to receive different category recommendations. The API analyzes the provided string to generate tailored results.

Typical use cases include enhancing e-commerce platforms with cross-selling features, improving product discovery, and personalizing user experiences based on search queries.

Data accuracy is maintained through continuous updates and quality checks performed by the API provider, ensuring that the recommended categories remain relevant and up-to-date.

If the API returns partial or empty results, users should consider refining their input text for better matches or implementing fallback logic to suggest popular categories as alternatives.

General FAQs

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