Product intelligence
Collect ecommerce data by market
Feed regional product and storefront data into the commerce intelligence pipelines your teams already run.
Who this is for
Data and commerce-intel teams who extract product fields at scale. Use price monitoring if you only track price changes.
Comparable product fields across markets
Collect prices, stock, listings, and details with location and session controls that make scheduled pipelines repeatable.
Pipeline outcomes
Market-tagged product rows
Every record can include the dashboard location you used.
More than price
Listings, availability, and public product attributes in the same access pattern.
Your warehouse, your parsers
Premip does not host the pipeline. Credentials plug into workers you own.
Collection controls
Product-level visibility
Reach public PDPs and catalogs through the chosen location.
Flexible monitoring
Sticky for a category walk; rotate between scheduled cycles if you want a new IP.
Pipeline-ready access
HTTP proxy URL in workers, queues, and replay jobs.
Ecommerce data jobs
Availability
Public in-stock and listing presence by market.
Pricing and promotions
Regional price and offer fields.
Marketplace listings
Compare public offer pages across storefronts.
Recommended setup
Residential or mobile
Product pages frequently differ on consumer networks. Use residential or mobile per selling market; datacenter only when validation still looks correct.
Sessions
Sticky while walking category → PDP. Rotate after a completed batch if the next cycle should use a new IP.
Location
One location parameter per pipeline run. Store it on every row.
Before you start
- Storefronts, SKU or URL lists, and markets.
- A parser schema: price, currency, stock, title, and identifiers.
- Workers that support HTTP or SOCKS5.
- A Premip plan covering those locations.
How to collect ecommerce data
Validate parsers on one SKU and market, then scale catalogs and countries.
Step 1
Choose markets and identifiers
Define countries, storefronts, and product keys (SKU, GTIN, or canonical URL).
Step 2
Provision access
Sign up, pick a proxy product, and copy credentials into the worker secret store.
Step 3
Pin the run to a location
Set the dashboard location to the market for this job. Pass the same market name into job config.
Step 4
Point workers at the proxy
Use http://USERNAME:PASSWORD@HOST:PORT for HTTP clients. Confirm SOCKS5 only if the worker requires it.
Step 5
Fetch a golden PDP
Save HTML or JSON. Confirm price, currency, and availability. Freeze parser tests against this sample.
Step 6
Crawl with a session policy
Sticky for linked category walks. Do not rotate in the middle of a paginated category.
Step 7
Write rows with lineage
Store timestamp, market, storefront, URL, and extracted fields. Alert on parse miss rates.
Step 8
Add markets and volume
Clone the job per location. Increase concurrency after error rates stay low.
curl -x http://USERNAME:PASSWORD@HOST:PORT https://example.comEcommerce data questions
- How is ecommerce data different from price monitoring?
- Ecommerce data can include prices, stock, listings, product details, and search visibility. Price monitoring focuses primarily on price changes.
- Can I monitor several markets at once?
- Yes. Use supported location targeting and run separate jobs (or tagged partitions) per market so rows stay comparable.
- Do you deliver a product data API?
- No. You collect public pages through the proxy and parse them in your pipeline.
- What if parsers break after a site redesign?
- Keep golden samples per market. Re-fetch one URL through the same location and update the parser.
Message us
Reach support on Telegram, email, phone, or the contact form. Include your account email and, if you have one, your order ID.