Where we get prices and promotions, which chains we cover, how we keep the data clean – and how it reaches your systems.
Ongoing monitoring of retail chains, plus collection from online stores on your list
We collect prices and promotions from public sources. By default this is the chain-wide price; on request, the price at a specific store (not available for every chain), which also shows chain and brand presence by region and city.
Collection from websites on a list you provide. Launch timing and output format are agreed separately to suit the volume.
The chains, categories and regions we collect data for
Price history is an asset that compounds: it can’t be collected retroactively, so we record prices regularly and keep the whole archive.
| Chain update frequency | daily |
| History depth | since 2025 |
| Online stores | one-off or on an agreed schedule |
| Collection time | date and time are stored for every record |
Every chain names a product its own way; in the cabinet you see it as one item with prices across all chains
The same product in different chains is merged into one card, so you compare prices, not names
We keep checking catalogue accuracy, so similar-but-different products never end up in one comparison
If needed, we map products to your internal codes so the data drops straight into your reports
Before data reaches the cabinet or a file, it is checked for completeness and correctness.
A chain’s online price can differ from the shelf tag in a particular store because of local promotions, price-tag timing or channel specifics.
Data in the formats your team already works with
A browser-based app: filters by chain, brand, category and region, charts, a promotion calendar and exports. Access is opened after the demo.
Prices, promotions, history and stores for your internal systems and pricing models.
Methods and response format →Scheduled files in an agreed structure – by email or to your storage.
File structure →Connect Power BI, Tableau and other systems via the API or files.
A REST API that returns JSON. The access key is issued together with cabinet access.
| Method | Returns |
|---|---|
GET /prices | Prices on a date by product, chain and region |
GET /promos | Promotions: type, depth, start and end dates |
GET /history | A product’s price history for a period |
GET /stores | Chain stores with addresses and regions |
The full description of methods and fields is in the API documentation we provide with the access key.
# Coffee prices in Kyiv on 8 October GET /v1/prices?category=coffee®ion=kyiv&date=2026-10-08 Authorization: Bearer <API key> { "date": "2026-10-08", "items": [ { "barcode": "4820000000017", "name": "Ground coffee, Brand A, 250 g", "retailer": "silpo", "store_id": "kyiv-001", "regular_price": 219.00, "promo_price": 159.90, "promo_type": "Price of the week", "promo_end": "2026-10-14", "collected_at": "2026-10-08" } ] }
One row is one product’s price in a specific store on a date. The set of columns is agreed to fit your task.
| Column | Description | Example |
|---|---|---|
date | Price collection date | 2026-10-08 |
retailer | Chain or website | Silpo |
store_address | Store address | Kyiv, 1 Prykladna St |
region | Region / city | Kyiv |
barcode | Product barcode | 4820000000017 |
name · brand · category | Name, brand, category | Ground coffee 250 g · Brand A · Coffee |
regular_price | Regular price, UAH | 219.00 |
promo_price · promo_type | Promo price and promotion type | 159.90 · Price of the week |
promo_start · promo_end | Promotion dates | 2026-10-01 · 2026-10-14 |
We agree the format and delivery method with your team – together or one at a time: cabinet, files, API.
The browser-based B2B cabinet, Excel/CSV files, the API or a mix – whatever suits your people and systems.
Which chains, brands, categories and data fields you need, for which period and how often to update.
We issue cabinet or API access and set up the file schedule and the channel: email or your storage.
Review prices and promotions in the cabinet, build your own Excel reports or plug the data into BI and business systems.
Onboarding timelines and the list of supported systems are agreed separately.
Tell us where the data should go – the cabinet, Excel or your own systems. We will show an example in the demo.
