Collect data from every market you operate in, simultaneously
Different countries, different prices, different product catalogues. Our multi‑region pipelines deploy local residential IPs, native language headers, and region‑specific browser profiles to collect exactly what a local customer sees — across 120+ markets, all from one dashboard.
target: "https://global-store.com"
regions:
- "US": { proxy: "residential", locale: "en‑US" }
- "DE": { proxy: "mobile", locale: "de‑DE" }
- "JP": { proxy: "residential", locale: "ja‑JP" }
delivery: "snowflake‑partitioned"
US, DE, JP, BR
All regions landed
Multi‑region pipelines powering
One configuration, a world of data
Multi‑region data collection is the ability to scrape the same target website from dozens of countries — simultaneously — and get the localised content, pricing, and availability that real local customers see. Instead of managing separate scrapers for each market, you define your target once, select the regions, and our platform automatically instantiates region‑specific pipelines with native IPs, browser languages, timezones, and even local payment methods.
All collected data is mapped to a shared schema, so you can compare apples to apples across markets — delivered into your data warehouse as a single merged table or partitioned by region, on the schedule you choose.
- 120+ countries with city‑level residential and mobile IPs
- Native language headers, timezone, and locale configuration
- Parallel execution — all regions scraped at the same time
- Unified schema with automatic field mapping per region
- Add or remove regions with a single configuration change
Why single‑region scrapers fail at global scale
Running one scraper per country quickly turns into a maintenance nightmare — here's why teams consolidate onto a multi‑region platform.
Geoblocked content returns wrong data
A US IP hitting a French site sees a generic international page, not the local catalogue. Without region‑native proxies, your global pricing intelligence is built on bad data.
Managing 50 scraper configs is unsustainable
Each new country requires a new proxy, new language headers, and often a slightly different DOM. Without a unified configuration layer, you're copying, pasting, and debugging endlessly.
Data arrives in inconsistent formats
Different locales mean different field names, currencies, and even data structures. Normalising all that into one clean dataset is a separate engineering project — unless your pipeline does it for you.
One pipeline to rule every region
Each feature below is designed to eliminate the operational overhead of multi‑market data collection.
Region‑native IP & browser profiles
Every region gets its own residential or mobile IP, matched language headers, and local timezone — so the target sees a genuine local visitor.
Auto‑cloned pipeline instances
Define your target and schema once. The platform automatically spawns region‑specific clones with the correct proxies and locales — no manual duplication.
Unified schema mapping
Fields that are named differently in each locale (e.g., “Preis” vs. “Prix”) are mapped to a single canonical field. You get one clean dataset, not a spreadsheet per country.
Synchronised delivery
Choose to have data from all regions arrive together in one batch, or stream region by region as they complete — with freshness timestamps for each market.
{
"price": {
"US": "span.price‑dollars",
"DE": "span.preis",
"JP": "span.price‑yen"
},
"delivery_format": "partitioned"
}
From target definition to global data coverage
Region scoping
We map your target site's region‑specific behaviour, identify URL patterns, and determine the optimal proxy types and locales for each market.
Unified pipeline design
Our engineers build a single pipeline template with region‑specific rules. Schema mapping ensures consistent field names across all locales.
Multi‑region validation
We run a sample extraction from every region in parallel and deliver a merged dataset for your review — validating schema, completeness, and data freshness.
Production deployment
All regions go live simultaneously on your chosen schedule. Adding a new market is a single configuration change — no new development required.
Deliverables for every multi‑region project
Region mapping document
A written scope listing every target region, the required proxy type, locale settings, and any region‑specific extraction rules — signed off before build begins.
Staging dataset — all regions
A sample dataset collected from every agreed region, merged into the unified schema. You validate that local data is accurate and complete.
Production pipeline + region‑runbook
Full‑scale deployment with all regions active. A runbook covers proxy pools, locale settings, and the process for adding new markets.
Monthly region health report
A summary of collection success rates per region, data freshness, and any locale‑specific changes on target sites — shared proactively.
Pay per region, or reserve capacity globally
Per‑Region
Best for projects with a fixed set of markets — billed monthly per active region with no volume commitment.
- Flat fee per region per month
- All proxy & locale features included
- Add regions anytime
Managed Global Pipeline
For ongoing multi‑market data needs — one price for up to 20 regions, with an SLA and dedicated support.
- Up to 20 regions included
- 99.5% per‑region delivery SLA
- Unified schema management
Enterprise Global
For unlimited regions, custom SLAs, dedicated proxy pools, and priority support.
- Unlimited regions
- Dedicated proxy & IP pool
- Custom SLA, SSO, quarterly reviews
Teams that compete on a global stage
Global E‑commerce
Monitor pricing, product availability, and promotions in every market — with real local visibility.
International Travel
Collect localised fares, hotel rates, and availability from booking platforms that vary content by country.
Media & Streaming
Capture regional content catalogues, localised metadata, and compliance‑specific data from streaming services.
Market Research
Build global datasets from multiple local sources — price indices, consumer sentiment, and competitive landscapes.
Multi‑region collection vs. the fragmented approach
| Capability | Managed Multi‑Region Collection | Single‑Region Scraper × N | DIY Proxy Rotation |
|---|---|---|---|
| Unified configuration for all regions | |||
| Native IP & locale per region | |||
| Automatic schema normalisation | |||
| Parallel execution | |||
| Add a new region in minutes | |||
| Engineering effort to maintain | Minimal | Multiplied by N | Constant ops |
“We finally see exactly what our customers see in every market”
"We used to run 12 separate scrapers for our 12 core markets — maintaining them was a nightmare. ScraperScoop's multi‑region pipeline replaced all of that with a single configuration. Adding a new country now takes us 10 minutes."
"The local IP and language handling is spot‑on. We're finally seeing the prices that actual customers in Japan and Germany see — not the generic international versions. Our revenue models are accurate for the first time."
"The unified schema across regions is the unsung hero. All our data now has the same column names, currencies converted, and timestamps aligned — it drops straight into our BI tool without any preprocessing."
Global data lands in your warehouse, partitioned or merged
Choose how you want your multi‑region data delivered — one table, one folder per country, or a live stream per market.
Start with three regions — see the global data difference
We'll run a sample collection from your target across the markets you care about. No commitment, no setup fees.
Common questions about multi‑region data collection
See what your global customers see — start with a free sample
Pick three regions and a target URL. We'll collect the local data, map it to a unified schema, and deliver a sample dataset within two business days — no commitment, no sales call.
Most global pipelines go from scoping to production in under 4 weeks.
