Collecting publicly listed prices is the best-supported activity in all of scraping law. A price is a fact, and Feist Publications v. Rural Telephone (1991) settled that facts are not copyrightable no matter how much effort went into gathering them. Prices are published deliberately, to be read. No personal data is involved, so the privacy statutes that complicate other scraping do not apply. Price monitoring is a mainstream, decades-old commercial practice.
Two constraints do apply, and neither is about copyright. The first is contract: if you accepted a retailer's terms of service, those terms may prohibit automated collection and are enforceable against you. The second is antitrust, which governs what you do with the prices rather than how you got them.
This page is not legal advice. Competition law in particular is fact-specific and differs sharply between the US and the EU.
Feist is the anchor. The Supreme Court held that a compilation of facts is protected only in its original selection and arrangement, not in the facts themselves, and rejected the idea that effort alone earns copyright. A price, a SKU, and a stock status are facts. Copying a competitor's product photography or their written description is a different act, and that is where copyright re-enters.
The access statutes point the same way. Under Van Buren v. United States (2021) and hiQ Labs v. LinkedIn, reading a page served freely to any visitor is not access "without authorization" under the Computer Fraud and Abuse Act, because there is no gate. A public catalogue page has its gate up.
The realistic exposure is contractual, and it turns on one question: did you agree to anything? In Meta Platforms v. Bright Data (January 2024), the court held that a scraper operating logged out was not a "user" bound by the site's terms of service, and struck down a clause purporting to bar public scraping forever after an account closed. Collecting anonymously from public catalogue pages is a materially better position than collecting from behind an account whose terms you accepted.
Antitrust does not care how you obtained a price. It cares what happens next.
Monitoring competitor prices and setting your own is ordinary competition. The problem arises when price data becomes a mechanism for coordination: sharing collected prices with competitors, or using shared algorithmic pricing infrastructure in a way that aligns behaviour across a market. Regulators on both sides of the Atlantic have brought cases about algorithmic pricing, and the fact that a price was public when collected is not a defence to a coordination claim.
The rule of thumb is simple to state and worth stating plainly. Use competitor prices to make your own decisions. Do not use them to make decisions jointly.
Retail and travel pages are among the most heavily defended on the web, which is a technical problem rather than a legal one. In the Web Data Frontier Benchmark, fifteen providers were sent the same 99 bot-protected targets, five attempts each, in the August 11, 2026 run. Retail and ecommerce is one of the weakest categories across the field. String returned verified content on 97.0% of all requests, the highest in the run.
That is a measurement of retrieval, not of permission. It tells you which pages come back; it does not tell you which pages you should be asking for. Those are separate questions and the second one belongs to your counsel.
Collecting publicly displayed prices is generally lawful in the US. Prices are facts and facts are not copyrightable under Feist, and reading a public page is not unauthorised access under the CFAA. The constraints are terms of service you actually accepted, and antitrust rules governing what you do with the data.
No. Feist Publications v. Rural Telephone holds that facts are not copyrightable and that effort alone does not create protection. A compilation can be protected in its original selection and arrangement, and product photography and written descriptions are protected expression, so copy the numbers rather than the page.
They can bind you if you accepted them, typically by creating an account. In Meta v. Bright Data a scraper operating logged out was found not to be a "user" and so not bound. Anonymous collection from public catalogue pages is the stronger position.
It comes from use, not collection. Setting your own prices from public data is competition. Sharing collected prices with competitors, or using shared pricing algorithms in ways that align market behaviour, can raise coordination concerns regardless of how the data was obtained.
Retail and travel sites carry the heaviest anti-bot deployments on the web, mostly Cloudflare, DataDome, Akamai, and PerimeterX. That is a commercial decision by those sites about automated traffic, and it is a technical obstacle rather than a legal one.
