Attribute extraction from titles and descriptions.
Not every attribute has a field of its own. Half the useful information often sits inside the product title: Nike Air Max 270 Men's Running Shoes Black 42 EU has no colour, gender or size field, yet the string holds all three. On request, we parse attributes like these out of titles and descriptions into separate columns — the difference between a dataset you can filter and one you have to clean first. Useful for catalog import, product matching, or any category where five retailers describe the same item five different ways.
Attribute extraction from titles and descriptions.
Not every attribute has a field of its own. Half the useful information often sits inside the product title: Nike Air Max 270 Men's Running Shoes Black 42 EU has no colour, gender or size field, yet the string holds all three. On request, we parse attributes like these out of titles and descriptions into separate columns — the difference between a dataset you can filter and one you have to clean first. Useful for catalog import, product matching, or any category where five retailers describe the same item five different ways.
What Product Data You Can Extract
What Product Data You Can Extract
What Product Data You Can Extract
Every store builds its pages differently, but the underlying product record is the same everywhere. These are the fields we return as standard.
Every store builds its pages differently, but the underlying product record is the same everywhere. These are the fields we return as standard.
Identifiers
SKU, GTIN/EAN/UPC, MPN, ASIN, internal product ID. These are what let you recognise the same item across three different retailers. Without them a dataset is a list, not a comparison.
Product attributes
Title, brand, category path, specifications, variant options, size, colour. Extracted at variant level — a shoe in seven sizes returns seven rows, not one.
Commercial data
Current price, list price, currency, discount, promotional labels, stock status, shipping terms.
Content and media
Full description, bullet points, primary and gallery images, spec sheets. Images are delivered as URLs or downloaded and stored on our side.
Ratings and reviews
Average rating, review count, and where the store exposes it, the score distribution.
Identifiers
SKU, GTIN/EAN/UPC, MPN, ASIN, internal product ID. These are what let you recognise the same item across three different retailers. Without them a dataset is a list, not a comparison.
Product attributes
Title, brand, category path, specifications, variant options, size, colour. Extracted at variant level — a shoe in seven sizes returns seven rows, not one.
Commercial data
Current price, list price, currency, discount, promotional labels, stock status, shipping terms.
Content and media
Full description, bullet points, primary and gallery images, spec sheets. Images are delivered as URLs or downloaded and stored on our side.
Ratings and reviews
Average rating, review count, and where the store exposes it, the score distribution.
Need a field that isn't here? Custom fields are configured per project — see standard and custom data fields.
Need a field that isn't here? Custom fields are configured per project — see standard and custom data fields.
Need a field that isn't here? Custom fields are configured per project — see standard and custom data fields.
