AI Product Matcher

AI Product Matcher is an Apify Actor that compares product listings scraped from two or more e-commerce websites and finds the pairs that refer to the same item. It is built for market research, competition analysis and pricing intelligence work that depends on tracking exact product matches across competitor shops. Matching runs on the Apify platform alongside the scrapers that collect the data, so extraction and matching come from one provider.

A user first runs a scraper to collect product data from each shop, choosing an Apify Actor, a community scraper or a self-built one. The two datasets are then handed to the matching Actor, which processes hundreds of potential product pairs per minute, and the matches are downloaded in JSON, HTML, Excel or other formats. The Actor needs only two inputs, the datasets and the attributes to compare, and it can be tested with its default input.

The model behind AI Product Matcher is trained on datasets containing thousands of labeled product pairs, and it handles 1K or 1M pairs alike. New categories and shops can be mapped within a few hours, and the whole scraping and matching pipeline can be scheduled to run every week, day or hour. A recall-focused setting returns as many candidate pairs as possible so that human mappers only check pre-selected pairs.

AI Product Matcher is priced per result at $10 per 1,000 checked product pairs, counting both matched and unmatched pairs, plus the cost of the scraping runs. A new Apify account's Free plan includes credits to try the Actor; regular or larger-scale use needs a paid Apify plan such as Starter at $19 per month plus pay as you go. Uploaded datasets and results go through the Apify API, and custom scrapers are available on request.

Use cases

• Competition analysis by tracking exact product matches on competitor websites as a data source for product and revenue teams
• Market research to avoid overstocking and slow reactions to market changes
• Pricing intelligence that matches inventory across websites to manage dynamic price changes and feed dashboards
• Pre-selecting candidate pairs so human mappers check results instead of searching competitor sites by hand