Every competitor shelf, read as structured data.
Online retail moves on price, availability and range, often several times a day. We extract product, pricing, stock and seller data from marketplaces and retailer sites, match it to your catalogue and deliver it in the formats your pricing and category teams already use.
What makes this industry hard to track.
Matching the same product across sites
One item appears under different titles, pack sizes and identifiers on every site. Without dependable matching, a price comparison quietly compares the wrong things.
Prices that depend on where you stand
Displayed prices and delivery promises change with postcode, device and logged-in state. Capture has to reproduce the view a real customer in that city would see.
Multiple sellers on one listing
On marketplaces the featured offer rotates between sellers, and the lowest price is not always the one shown. Recording only the headline offer hides most of the competition.
Large, fast-changing catalogues
Competitor ranges add and delist thousands of items each week. Coverage checks are needed so a missing product is reported as a delisting, not silently dropped.
Eight data points our clients rely on.
Shelf price
Current selling price per product, normalised to a single currency and unit where needed.
Promotional price and mechanic
Strike-through prices, coupons, multibuys and the dates they run.
Stock status
In stock, low stock, out of stock or pre-order, by city or delivery postcode.
Seller and fulfilment
Who is selling each offer and whether the platform or the seller ships it.
Featured offer holder
Which seller wins the default offer on a shared listing, and at what price.
Search and category rank
Position of your products and competitors for priority keywords and category pages.
Ratings and review count
Average rating and review volume, tracked over time per product.
Delivery promise
Quoted delivery date or window and delivery fee for a given location.
An illustrative extract.
| Date | Source | City | Product | Price | Currency | Stock | Seller type |
|---|---|---|---|---|---|---|---|
| 2026-03-14 | Marketplace A | Dubai | Wireless earbuds 40h | 249.00 | AED | In stock | Third-party seller |
| 2026-03-14 | Retailer B | São Paulo | Wireless earbuds 40h | 399.90 | BRL | In stock | Retailer |
| 2026-03-14 | Marketplace C | Singapore | Air fryer 5.5L | 139.90 | SGD | Low stock | Third-party seller |
| 2026-03-14 | Retailer D | Toronto | Air fryer 5.5L | 149.99 | CAD | Out of stock | Retailer |
| 2026-03-14 | Marketplace E | Madrid | Robot vacuum with mop | 279.00 | EUR | In stock | Retailer |
Illustrative rows. Sources, markets and fields are agreed with you during scoping.
How teams put it to work.
Daily price index
A price index against a defined competitor set, by category and city, so pricing teams see where they are above or below market before the weekly review.
Range gap review
A comparison of competitor catalogues against yours that shows which brands, sizes and price tiers you do not stock, and which of your lines are exclusive.
Marketplace seller watch
A record of every seller on your key listings, their prices and fulfilment method, to support channel and pricing conversations with brand partners.
Relevant solutions
Related industries
How do you match our products to competitor listings?
We combine identifiers such as barcodes and model numbers with title, brand, size and image attributes. Uncertain matches are flagged for manual review rather than guessed, and approved matches are kept so they carry forward to later runs.
Can you capture prices for a specific delivery location?
Yes. We set the delivery city or postcode before capture so prices, stock and delivery promises reflect that location. Each record carries the location it was collected for.
How often can data be refreshed?
Most retail projects run daily, and priority categories can be refreshed several times a day. The right frequency depends on how often your competitors change prices, which the free sample usually shows.
Do you collect customer data from reviews?
We collect review text, ratings and dates where needed, and minimise personal data such as reviewer names. Projects are scoped against the privacy laws of the countries involved.