Bots Scraping Product Images and Copy for Counterfeit Listings
Scraping a catalogue is not always about prices. Images, descriptions, and reviews get lifted to build counterfeit listings elsewhere, and the traffic pattern looks different from price monitoring.
Most scraping coverage is about price: competitors and resellers watching what you charge. There is a quieter use for a scraped catalogue that matters more. Your product photographs, your descriptions, your size tables, and sometimes your reviews, reassembled on a marketplace or a standalone fake store, selling a counterfeit or nothing at all, with your content doing the persuading.
The scrape that feeds that operation looks different from price monitoring. Price bots revisit often and read a narrow set of fields. A content harvester comes less predictably, takes everything on the page including the large images most price tools skip, and often works through a catalogue once, thoroughly, before moving on. If you only watch for high frequency revisits, you will file this traffic as a quiet week.
Signs a harvest is happening
Look for sessions that request full size image files at a rate no shopper produces, in catalogue order, including colour variants a human would filter past. Look at image bandwidth by referring page and by network: a spike in image delivery with no matching rise in product page engagement is a shape worth a second look, because real marketing success brings the two together.
New or unusual referrers matter after the fact as well. Your own image URLs hotlinked from domains you have never heard of means someone built pages with your photography served from your bandwidth, which is both evidence and an ongoing cost. Search your own distinctive description phrases in quotes from time to time. Counterfeit operations rarely rewrite copy well, and a sentence you wrote is a fingerprint that survives being copied better than an image does.
What the harvest feeds, and why it is your problem
A convincing fake listing needs exactly what a good store page has: credible photography from several angles, accurate specifications, and social proof. Shoppers defrauded on a fake store do not always distinguish it from the real brand, especially when the content is identical. The chargebacks may not reach you. The support emails, the reviews on your real profiles, and the reputational damage do.
There is a search cost as well. Duplicated product copy across counterfeit domains muddies which page is the original, and marketplaces listing your products at impossible prices distort the price picture shoppers carry into your store. None of this is solved by a block alone, but a block informed by evidence, plus takedown filings that cite your original content and its dates, is a stronger hand than either on its own.
Raising the cost without punishing shoppers
Serve images at the size the page needs, with larger versions behind the product gallery interaction rather than as open files a crawler can enumerate, and watermarking review or campaign photography where the channel justifies it. Rate limit image delivery by session behaviour, not by blunt address caps that catch shared networks and real customers in the same net.
Keep a dated archive of original product content, images and copy, as it was published. In a takedown, the party who can show they published first, with records, usually wins the argument faster. That archive is a folder and a habit, nothing more, and it is almost impossible to reconstruct convincingly after the fact, which is the entire reason to start it before you need it.
Related reading
If this topic is useful, these earlier guides go deeper on connected questions: Not All Bots Are Waste: Separating Search Crawlers and Monitoring From Scraping, Bots in Your Wishlist Data: When Favourites Stop Meaning Demand, and Scrapers That Hit Size Guides, Stock Feeds, and the Quiet Corners.
Frequently asked questions
How is content scraping different from price scraping?
Price scrapers revisit often and read pricing fields. Content harvesters visit less predictably, download full size images, descriptions, and specifications, and often work through a whole catalogue once to build listings elsewhere.
How can a store detect image scraping?
Watch for catalogue order browsing with high full size image requests, image bandwidth rising without matching product page engagement, and your images hotlinked from unknown domains. Searching your own distinctive copy in quotes also finds copied listings.
Why does counterfeit scraping hurt the real store?
Shoppers blame the brand whose content convinced them, so support contacts and reputational damage arrive at the real store. Fake listings also distort prices and duplicate your content across the web.
What records help with takedowns?
A dated archive of your original images and product copy as published. Being able to show prior publication with records makes takedown filings faster and more convincing.