Commerce

Track competitor pricing exactly as local shoppers see it

Accurate, geo-correct pricing data on a schedule you control.

340

cities with residential coverage

99.4%

success on major retailers

< 1 s

typical page fetch

The problem

Retail prices are not a single number. The same SKU shows a different figure depending on the visitor's country, city, device, loyalty status and sometimes the weather. A price scraped from a datacenter IP in Virginia tells you almost nothing about what a shopper in Manchester is being charged.

Worse, retailers actively serve stale or inflated prices to traffic they suspect is automated. You end up making margin decisions on numbers that were never real.

The solution

Residential exits in the exact market you care about return the same page a genuine local shopper loads, including regional promotions, local currency and delivery-inclusive totals.

City-level targeting matters more than most teams expect. Grocery, fuel, pharmacy and marketplace pricing frequently varies between metros in the same country.

Mechanics

How proxies solve it

1

Geo-accurate to the city

Pull Berlin pricing from a Berlin household connection rather than a Frankfurt data centre.

2

Avoid anti-scraping price masking

Residential traffic is not served the degraded, cached or inflated variants that suspected bots receive.

3

Consistent baskets

Sticky sessions keep the currency, delivery region and cart state stable across a multi-step checkout probe.

4

Schedule without penalty

Rotating exits let you re-check high-velocity SKUs hourly without any single address building a suspicious pattern.

Workflow

How we would build it

  1. 1

    Define your market matrix

    List the country and city pairs that actually drive pricing decisions. Most teams over-collect here.

  2. 2

    Build one session per basket

    Use a sticky session for each product-page-to-checkout probe so shipping and tax stay consistent.

  3. 3

    Capture the total, not the sticker

    Delivery, tax and promotional stacking are where competitors hide margin. Scrape the basket, not the PDP.

  4. 4

    Re-run on a jittered schedule

    Randomise collection times within your window so your fingerprint is not a perfect hourly heartbeat.

  5. 5

    Alert on movement, not on runs

    Pipe deltas into your BI tool and alert on price changes rather than on collection completing.

FAQ

Price monitoring questions

For electronics and fashion, country is usually enough. For groceries, fuel, pharmacy, tickets and anything with delivery-based pricing, city targeting changes the answer materially.
As often as their infrastructure tolerates. Rotating exits remove the per-IP limit, but you should still respect the target's capacity. Hourly on high-velocity SKUs and daily on the long tail is a sane default.
Technically yes with sticky sessions, but check the terms of the account you are using. Our Acceptable Use Policy prohibits credential stuffing and unauthorised account access.
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Ready to start price monitoring?

Your first gigabyte is free, which is normally enough to validate the approach against your real target before you commit to anything.