Data On Demand, one-stop data solution
Markets Local sources. Your time zone.

Teams in five regions rely on us for local-language, multi-currency data.

Global coverage
Company A decade of data expertise.

An in-house team of 20+ engineers and analysts serving clients in 12+ countries.

About us
Data type

Every competitor range, mapped to your taxonomy.

Understanding what competitors sell is as important as what they charge. We extract complete catalogues, including category trees, product attributes, images and descriptions, and map them to your taxonomy so ranges can be compared directly.

The challenge

Every retailer structures its catalogue differently, so comparing ranges means reconciling thousands of categories and inconsistent attribute names. Range reviews often rely on store visits and partial exports that miss new launches.

With Data On Demand

You get a like-for-like view of competitor ranges by category, brand, price tier and attribute. New listings and delistings are tracked, so range changes are spotted as they happen.

What’s included

Everything needed to run it in production.

01

Full catalogue crawl

All product pages across the category tree, including variants such as size and colour, with stable product identifiers.

02

Attribute extraction

Specifications and attributes are parsed from tables and descriptions into structured fields such as material, capacity or wattage.

03

Taxonomy mapping

Competitor categories are mapped to your internal hierarchy, with a mapping table you can review and adjust.

04

Content capture

Titles, descriptions, bullet points, image counts and image URLs are captured for content quality analysis.

05

New and delisted tracking

Each crawl is compared with the previous one to flag new products, delistings and changes to key attributes.

06

Brand and private label tagging

Products are tagged by brand, with private label lines identified where the retailer's own brands can be recognised.

Sample output

What lands in your systems.

Typical fields
product_idsourcecategory_pathmapped_categorybrandvariantattributes_jsonfirst_seen
Assortment extract mapped to a client taxonomy
sourcemarketcategory_pathmapped_categorybrandproductpricecurrency
Retailer NUAEHome > Kitchen > Small appliances > KettlesKettlesPrivate labelElectric kettle 1.7L glass79.00AED
Marketplace CMalaysiaRumah > Dapur > CerekKettlesBrand PElectric kettle 1.7L steel89.00MYR
Retailer QGermanyKüche > WasserkocherKettlesBrand RVariable temperature kettle 1.5L59.99EUR
Retailer SUnited StatesKitchen > Coffee & Tea > KettlesKettlesBrand PGooseneck kettle 0.9L49.99USD
Marketplace TColombiaHogar > Cocina > HervidoresKettlesBrand UElectric kettle 1.8L119,900COP

Illustrative rows. Your schema, field names and formats are agreed during scoping.

Use cases by team

Who uses it, and for what.

Range reviews compare competitor depth by brand, price tier and attribute in each category. Gaps and over-ranged areas are visible before the review meeting.

How it runs
  1. Scope. Tell us the sources, fields and frequency. We confirm feasibility within a day.
  2. Free sample. A real sample from your own target source, in your format.
  3. Build. Engineers build extractors tuned to each source. No generic templates.
  4. Validate. Automated and manual QA on every run before anything ships.
  5. Deliver and monitor. Scheduled delivery, monitored pipelines, fast fixes when sites change.
How we work
FAQ

Questions about catalogue & assortment data

Can’t find your answer? Ask an engineer

How do you map competitor categories to ours?

We build a mapping table from each source's category tree to your taxonomy, using category names, product titles and attributes. You can review and adjust the mapping, and changes are applied to future deliveries.

Do you capture product variants?

Yes. Size, colour and other variants are captured as separate rows linked to a parent product, so you can measure range depth accurately.

Can you detect new product launches?

Each crawl is compared with the previous one, so new listings are flagged with a first-seen date. Weekly or daily crawls give earlier detection.

Can we get product images?

We capture image URLs and counts by default. Image files can also be downloaded and delivered to your storage where the use case and source terms allow.

Start with proof

See your own data before you commit.

Name the sources and fields you need. Within 24–48 hours you receive a real sample from your target sites, in your format, free of charge.

Request a free sample Talk to a data engineer Sample in 24–48 hours · NDA on request · Any format, any schedule