Know every competitor price before your customer does
Fresh competitor prices and a market median you can defend in a pricing meeting — collected daily from the shops that actually compete with you.
Most teams already have a repricing model. What they lack is a trustworthy input: every tracked listing collected on schedule, seen from the right country, with promo prices kept separate from shelf prices. That is the part we run for you.
What makes price data hard
These are the six problems teams hit within a month of building price monitoring in-house. Each one is handled by the stack below.
Coverage that keeps growing
Every new shop, category and marketplace is another crawler to build and maintain. In-house scrapers rarely keep pace with the catalogue.
Weekly reports, daily prices
By the time a spreadsheet is circulated, the market has moved. Repricing needs an input that refreshes on its own schedule.
Prices depend on where you look from
Currency, tax and local promotions change what a page shows. Collected from the wrong country, the number is simply wrong.
Blocking breaks the series
A crawler that works for two weeks and then gets throttled leaves gaps exactly where a trend line needs continuity.
Promo noise vs. the real price
Loyalty discounts, bundles and coupon prices are not the shelf price. Mixing them into a median produces a market that doesn’t exist.
It has to land in your systems
A dashboard nobody exports from is a dead end. Prices belong in the pricing engine, the warehouse and the BI layer.
What changes once the data is reliable
Pricing decisions stop being a debate about whose spreadsheet is newer, and start being a decision about margin.
You undercut where it wins volume and hold price where the market has already moved up.
Nobody opens eleven tabs per SKU. The category team reviews exceptions instead of collecting rows.
A competitor’s move shows up in the next run, with an alert, not in next Monday’s report.
Pricing, category and finance read the same dataset from the same runs, so the argument is about strategy.
The stack for price intelligence
Both products are bought separately, so you can start with residential access for your own tools and add collection when you want us to run the crawls.
Proxy IP
Makes the series continuous and locally correct: residential exits in the countries you sell in, so pages render the way a local buyer sees them.
Data Scraping
Collects the listings themselves — price, availability, promo flags and titles — on the schedule you set, validated against a schema per shop.
Questions about price intelligence
Any public listing page: your competitors’ own shops and the marketplaces they sell on. You supply the URLs or categories; we handle rendering, retries and the schema per source.
Yes. Promo flags, bundle indicators and loyalty prices are captured as separate fields, so a median can be built on shelf price alone or on the effective price.
As fresh as the schedule you set: daily is typical for a large catalogue, hourly for a short list of key SKUs. Each run reports what changed, so alerts fire on movement rather than on every crawl.
In the dashboard, and wherever else you need it: REST API, webhook per run, or scheduled exports into a warehouse. Most teams push it straight into the pricing engine.
Not necessarily. Proxy IP is the part price data cannot do without — it keeps the series continuous and locally correct, whether you crawl with your own tools or ours.
Start with one category
Pick a category and the shops that matter, and we will run the first price comparison with you.