Every product has an identifier. We find it.
Extract unique SKUs — along with prices, stock levels, and variant details — from any e‑commerce site. Our pipelines dig into page source, JavaScript objects, and API responses to capture identifiers that aren't visible on the page. The result: a clean, deduplicated SKU feed ready for your inventory system, repricer, or marketplace analysis.
{"sku":"NB-574-GRY-9","retailer":"shoestore.com","price":89.99,"stock":12}
{"sku":"NB-574-GRY-10","retailer":"shoestore.com","price":89.99,"stock":3}
{"sku":"NB‑574‑GRY‑9","retailer":"anothermart.com","price":94.50,"stock":7}
142,000 from 5 retailers
98% match rate
SKU‑level pipelines running for
Turn any storefront into a clean, deduplicated SKU feed
SKU data collection goes deeper than product titles — it hunts for the unique identifiers that power inventory management, repricing, and catalog matching. Our pipelines crawl product pages, variant selectors, and even JSON‑LD embedded data to extract every SKU, UPC, and GTIN associated with a product, along with its price, stock level, and images.
We normalise identifiers across retailers, deduplicate where requested, and deliver the data in a structured format that plugs directly into your ERP, PIM, or marketplace repricer — so your internal systems always know what's being sold, by whom, and at what price.
- Extracts SKU, UPC, GTIN, EAN from page source and APIs
- Captures variant‑level identifiers (size, colour, style)
- Deduplicates across retailers with configurable matching
- Maps to your internal catalog using GTIN or title matching
- Delivered as JSON, CSV, or Parquet to your warehouse
Why SKU data is surprisingly hard to collect at scale
Identifiers are often hidden from view — and even when they're visible, matching them across retailers is a data‑science challenge.
SKUs hide in JavaScript and JSON‑LD
Many sites embed identifiers in structured data layers, JavaScript variables, or API payloads — invisible to simple scraping. Without deep parsing, you capture the product name but miss the unique code that identifies it.
Identifiers vary across retailers
The same shoe might be “NB-574-GRY-9” on one site and “574GRY9” on another. Without intelligent normalisation and cross‑referencing, your dataset is a fragmented mess that can't power automated workflows.
Deduplication is a moving target
A product that appears on three retailers with slightly different SKU formats creates false duplicates in your system. Our pipelines apply fuzzy matching and GTIN anchoring to merge duplicates while preserving per‑retailer pricing.
Every identifier, from every source, deduplicated and mapped
Each feature is purpose‑built to find, extract, and structure the identifiers that power retail operations.
Deep identifier discovery
We parse HTML data attributes, JSON‑LD structured data, JavaScript variables, and network API responses — finding SKUs that are never rendered in visible text.
Cross‑retailer normalisation
We normalise SKU formats using configurable rules — stripping separators, converting case, and anchoring on GTIN/UPC where available — to produce a clean, comparable dataset.
Internal catalog mapping
Using GTIN, UPC, or title similarity, we map collected SKUs to your internal product identifiers — so the data lands pre‑matched to your existing catalog.
SKU‑level change monitoring
Track price changes, stock‑outs, and new SKU additions at the individual identifier level — with alerts pushed to your warehouse or messaging system within minutes.
{
"canonical_gtin": "0195925123456",
"sources": [
{ "retailer": "shoestore", "sku": "NB-574-GRY-9", "price": 89.99 },
{ "retailer": "anothermart", "sku": "574GRY9", "price": 94.50 }
]
}
From raw storefront to structured SKU master file
SKU source audit
We audit the target site's pages and network traffic to identify all locations where identifiers appear — visible and hidden.
Extraction & normalisation logic
Our engineers build the extraction rules and define normalisation patterns — aligning variant‑level SKUs, GTINs, and internal codes.
Sample SKU feed delivery
A representative sample of SKUs is delivered in your schema — you validate identifier accuracy, deduplication, and attribute completeness.
Full production deployment
All SKUs go live on your schedule. Ongoing monitoring tracks new identifiers, price changes, and stock‑outs in real time.
Deliverables for every SKU data project
SKU source map & normalisation plan
A document showing exactly where each identifier lives on the target site and the rules for normalising them — approved by your team before build.
Sample SKU feed (5,000 identifiers)
A deduplicated, normalised SKU dataset covering your core categories, delivered in your schema for accuracy and completeness review.
Full SKU master file + runbook
All identifiers extracted and mapped. A runbook details the extraction sources, normalisation logic, and update cadence.
Weekly SKU change digest
Summary of new SKUs discovered, delisted identifiers, and significant price/stock movements — proactively shared with your team.
Flexible plans for any SKU coverage need
One‑Time SKU Audit
Best for a baseline snapshot of identifiers from one or more retailers — ideal for catalog gap analysis.
- Fixed scope & price per retailer
- All identifiable SKUs extracted
- Normalised and deduplicated output
Managed SKU Feed
Ongoing collection with scheduled refreshes, change detection, and mapping to your internal catalog.
- Daily or weekly SKU updates
- Incremental change detection
- 99.8% identifier accuracy SLA
Enterprise SKU Program
For multi‑retailer, high‑volume SKU collection with custom mapping, deduplication rules, and dedicated support.
- Unlimited retailers & SKUs
- Custom identifier matching logic
- SSO, audit logs, quarterly reviews
Teams that run on product identifiers — not just product names
Inventory Management
Feed your ERP with competitor SKU‑level stock data — improve demand forecasting and safety stock calculations.
Dynamic Repricing
Match competitor prices at the SKU level — never reprice the wrong variant because you only had parent‑level data.
Marketplace Intelligence
Collect SKUs from Amazon, eBay, and regional marketplaces — build a master catalog of who sells what, and at what price.
Brand Protection
Monitor your own SKUs across unauthorised retailers — detect MAP violations and grey‑market sales at the identifier level.
SKU data collection vs. generic product scraping
| Capability | Managed SKU Collection | Generic Product Scraping | Manual SKU Entry |
|---|---|---|---|
| Deep identifier discovery (JSON‑LD, JS, API) | |||
| Cross‑retailer normalisation & dedup | |||
| Internal catalog mapping (GTIN, UPC) | |||
| SKU‑level change monitoring | |||
| Ongoing maintenance | Included | Your team | N/A |
| Time to complete SKU dataset | 2–3 weeks | Weeks of custom scripts | Months |
“Our repricer finally operates at the SKU level — not the product level”
"We had no idea competitor SKUs were hiding in JSON‑LD data. ScraperScoop extracted 200,000 identifiers we never knew existed. Our catalog coverage jumped from 40% to 95% overnight."
"The cross‑retailer deduplication is brilliant. We now have a single view of every shoe sold across 12 retailers — with SKU‑level pricing and stock. Our buyers use it daily."
"Mapping their SKUs to our internal IDs was the game‑changer. Now when a competitor changes a price, our system knows exactly which of our SKUs is affected — and reprices automatically."
SKU data lands exactly where your operational systems expect it
Structured, deduplicated, and pre‑matched — plug directly into your ERP, PIM, or repricer.
Get a fixed‑price quote for your SKU data collection project
Share the target retailers and the identifiers you need — we'll provide a scope, price, and timeline within two business days.
Common questions about SKU data collection
Your competitor's SKU catalog — deduplicated and mapped to your systems
Send us a retailer URL and a sample of your internal SKU list. We'll return a matched sample feed within two business days — no commitment, no sales pitch.
Most SKU pipelines deliver the full dataset within 2–3 weeks of kickoff.
