An AI product feed API should do more than fetch links. For affiliate marketing teams, the job is to keep product data fresh, comparable, and publish ready as discounts and stock change. This article shows how to use an AI product feed API to normalize data, barcode match identical items

Affiliate marketing is the performance model where you earn a commission for driving measurable actions (clicks, leads, sales) to a merchant. In 2025 the winners operate like product publishers: they normalize messy data, compare prices and payouts, and surface the best offer at the exact moment of intent. This guide

LLM ranking and generation models learn faster when examples are unambiguous. Product feed training data is only as good as its identifiers. Use barcode and MPN matching to group identical items across merchants, then layer price, discount, and availability to produce clean labels that teach models to compare, rank, and

AI shopping product feeds work when the inputs are consistent and comparable. In reality, titles vary, attributes drift, and two listings for the same item can appear unrelated. That creates cluttered pages and missed savings for users and revenue teams. Affiliate.com aggregates normalized product data across more than 30

Comparison pages win in search when the data is structured, consistent, and easy to parse. Schema ready product feeds take messy titles and uneven attributes and convert them into clean product entities that a crawler can understand. Affiliate.com provides normalized product data across more than 30 networks, tens of