Industry overview
Data Extraction for Brand Protection
Counterfeits no longer hide. They list on every major marketplace, every social commerce surface, and hundreds of regional sites.
Tens of thousands live, always
A global brand can have tens of thousands of counterfeit and unauthorized listings live at any moment across marketplaces, social commerce, and classifieds. Each one erodes trust, damages reseller economics, and in regulated categories creates safety risk..
Investigation becomes pipeline
Brand protection at scale is a data operation. Extraction across every channel turns counterfeit detection from an investigation into a pipeline.
Every surface, every language
This is the surface we extract from. Every day, across every marketplace, social commerce platform, classifieds site, B2B wholesaler, domain registry, and app store where counterfeits can live.
Brands we help protect
A single viral counterfeit on social commerce can move more units in 48 hours than a marketplace counterfeit moves in a month. By the time a customer complaint reaches legal, the listing is past peak velocity and the damage to price perception and brand trust is done. Systematic extraction is the difference between catching counterfeits on day one and reviewing the aftermath on day thirty.
Use cases
Data extraction use cases
Every function in a brand protection company benefits from knowing what competitors are doing. From pricing teams to category managers to operations leads, here are the ways competitive data drives decisions.
Trademark and brand-term listing detection
Scan marketplaces and the open web for any listing using your brand name, product name, or a misspelled or homoglyph variant. In every language you operate in. Detection runs at brand-term, variant-spelling, and translation level, not just exact-match keyword.
Visual similarity and logo detection
Counterfeiters often avoid your brand name but steal your product photos, packaging, or logo. Match every listing image against your genuine product library. Image-similarity catches the long tail that exact-match keyword search misses entirely.
Unauthorized and gray-market seller detection
Find every seller listing your product online and cross-check against your authorized reseller list. Anyone not on the list gets surfaced. Authorization status, geography, and channel-licensing rules applied at the listing level.
Open web and standalone counterfeit site detection
Beyond marketplaces, counterfeiters run lookalike domains, mirror sites, and rogue e-commerce stores. Open-web crawling catches infringement that never appears on any marketplace. From search and ad landing pages to rogue online pharmacies.
Classifieds and regional marketplace coverage
Most counterfeits in India, Southeast Asia, and Latin America live on regional classifieds and lower-tier marketplaces, not the largest English-language sites. Coverage extends to where the counterfeits actually live, not just where they are easiest to extract from.
B2B wholesale source detection
Counterfeit retail listings trace back to factories and wholesalers. Extract from B2B wholesale platforms to find the source, not just the symptom. Upstream enforcement against the source cuts counterfeit supply, not one listing at a time.
Domain and app-store impersonation monitoring
Fake brand websites and fake brand apps are as damaging as counterfeit products. Monitor new domain registrations and app-store submissions for impersonation of your name, logo, and URL. New-registration alerts surface impersonation before customers find it.
Seller network and alias mapping
A single counterfeit operation often runs dozens of seller accounts across platforms. Correlate them by shared addresses, photos, and writing style. Network-level enforcement scales legal action, instead of taking down one listing at a time.
Evidence-grade capture for legal enforcement
Every flagged listing comes with full-page screenshots, seller details, image snapshots, timestamps, and a clean audit trail. Ready to file a takedown or a lawsuit without further work from your team. Captured the way courts and platforms accept it.
Takedown and repost tracking
Catching a counterfeit is half the job. Track whether listings actually stay down or get reposted under new seller names. Measure which platforms honor takedowns, reallocate enforcement spend by permanence. Effectiveness becomes measurable.
Review and Q&A consumer-signal mining
Customers often flag counterfeits themselves in marketplace reviews and Q&A threads. Extract and surface those signals so you catch counterfeits even when rule-based detection misses them. A leading detection signal no heuristic can replicate.
Counterfeit category and geographic trend analytics
Zoom out from individual listings to see which products are counterfeited most, in which regions, on which platforms. Strategic-level signal so leadership allocates enforcement budget where it matters, not just listing-by-listing alerts.
These are the most common use cases. Every engagement is scoped to your specific needs. If you have a use case not listed here, we will build it.
Data landscape
The data we extract
Here is what a structured brand-protection data feed looks like. We extract, clean, deduplicate, and deliver every data point listed below, across every marketplace, social commerce platform, and classifieds site you monitor.
This is a representative sample of the data we extract. We customize every extraction to your exact requirements. If you need a data point not listed here, we will add it to your pipeline.
Delivery formats
You tell us how you want the data. We handle everything else.
Impact
Why competitive data matters
The difference between having competitive intelligence and operating without it is measurable in revenue, market share, and speed.
With competitive intelligence
What you gain
Without it
What you risk
Challenges
Why brand protection data extraction is hard
If extraction were easy, you would do it yourself. Here is why it is not.
Scale and fragmentation
Counterfeits live across dozens of marketplaces, social platforms, classifieds, and regional sites. Each platform has its own architecture, anti-bot posture, and moderation stance. Systematic coverage across all of them is effectively dozens of separate extraction projects, each requiring continuous maintenance.
Aggressive anti-bot systems
Every major marketplace and social platform invests heavily in bot detection. CAPTCHA walls, device fingerprinting, session-based gating, and IP reputation scoring are standard. Extraction uptime across all counterfeit surfaces requires engineering teams that adapt continuously.
Image and visual similarity at scale
Detecting counterfeits through image similarity requires extracting millions of product images, computing perceptual hashes, and matching against genuine product libraries. The infrastructure for image extraction and similarity at global marketplace scale is a significant engineering investment.
Language and geographic diversity
Counterfeits often hide in non-English listings and regional marketplaces where most English-only brand protection tools do not cover. Meaningful protection requires language-aware extraction and translation across dozens of markets.
Social commerce API limitations
Facebook Marketplace, Instagram, and TikTok Shop each have distinct technical surfaces, and most do not expose structured APIs for bulk listing extraction. Capturing social commerce counterfeits requires specialized infrastructure and continuous adaptation as platforms update.
Seller network correlation
Mapping seller networks across platforms requires correlating seller identities through fulfillment addresses, product-image overlap, and writing-style similarity. Without structured correlation logic applied to extracted data, takedowns treat symptoms and counterfeiters simply relist under new aliases.
Evidence capture complexity
Legal enforcement requires evidence-grade data: full-page screenshots, seller details, image snapshots, timestamps, and chain-of-custody metadata. Delivering legal-grade evidence at scale requires more than simple scraping. It requires structured capture designed for downstream legal workflows.
Why us
Why Clymin for brand protection
We are not a tool. We are the team you call when the data matters too much to get wrong.
We solve what others can't
Brand protection needs coverage across marketplaces, social commerce, classifieds, B2B platforms, domains, and app stores, in every geography and language. We handle all of it. When other vendors say a surface is not covered or quietly deliver only exact-name matches, that is where we start.
You pay only for data delivered
No setup fees, no customization charges, no platform fees. One metric: cost per record. If we do not deliver, you do not pay. Your cost scales with your actual data consumption, nothing else.
We protect your identity
We do not display customer logos or names anywhere. Brand protection is a sensitive function. Counterfeiters actively watch for extraction traffic tied to brands that enforce aggressively. Your identity is protected. That is a promise, not a policy.
We prove it before you pay
No pitch deck replaces real output. We offer a free pilot: your trademarks, your channels, your data requirements, our execution. You evaluate the quality, coverage, and freshness of the data, then decide.
100B+
Data points extracted
24/7
Pipeline uptime
Real-time
Data delivery
100K+
Points of interest covered
Proven at enterprise scale. We operate continuous competitive intelligence infrastructure for one of the world's largest quick commerce platforms.
See what brand protection intelligence looks like for your legal team
Free pilot. 1-3 day turnaround. Your trademarks, your channels, our execution.
FAQ
Brand Protection data extraction FAQ
We extract from every major marketplace (Amazon, eBay, Alibaba, AliExpress, Flipkart, Shopee, Lazada, Mercado Libre, Temu, Shein, Walmart, Etsy, Snapdeal), social commerce (Facebook Marketplace, Instagram, TikTok Shop), classifieds (OLX and regional equivalents), B2B wholesaler platforms (Alibaba, Made-in-China, IndiaMART), domain registries, and app stores. If it is a surface counterfeiters use, we likely cover it.
We combine trademark detection with image-similarity matching, variant-spelling rules, price-threshold flagging, and review-signal mining. Exact-name matching alone misses most of the counterfeit long tail. Structured extraction across multiple signals catches the listings that evade single-rule detection.
Yes. Social commerce is one of the fastest-growing counterfeit channels and is a core part of our coverage. We extract from Facebook Marketplace, Instagram Shopping, TikTok Shop, and regional social commerce surfaces using specialized infrastructure designed for these platforms.
Yes. We capture evidence-grade data including full-page screenshots, seller details, image snapshots, timestamps, and chain-of-custody metadata. Your legal team receives enforcement-ready records, not raw scrape dumps.
Yes. We correlate seller identities through shipping-origin patterns, product-image overlap, and listing-text similarity to identify coordinated counterfeit networks operating across platforms. This enables enforcement at the network level, not just the listing level.
You share your requirements: which brands, trademarks, products, channels, and geographies. We build the extraction pipeline, run it for 1-3 days, and deliver structured flagged records in your preferred format. You evaluate the quality and coverage, then decide. No payment, no commitment.
No. We do not display customer logos or names anywhere, on our website, in sales materials, or in conversations with other prospects. Brand protection is a particularly sensitive function. Your identity is protected.
We charge per record delivered. One record is one structured row of data with the columns you define. Zero setup fees. Zero customization charges. Zero platform fees. Higher monthly volumes get lower per-record rates. You pay only for data we successfully deliver.