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Luxury marketplace & e-tail

Farfetch Product Data

Prices, variants, availability, and images from farfetch.com — normalised, validated, and delivered into your stack. No collector to build, and none to maintain.

source specification

Source
farfetch.com
Segment
Luxury marketplace & e-tail
Origin
United Kingdom — founded 2007 in London
Categories
Luxury womenswear, Menswear, Shoes, Bags, Watches
Formats
JSON · CSV · Parquet
Refresh
Continuous to daily

about the source

What Farfetch sells, and how its catalogue behaves

Farfetch is the largest luxury marketplace in the world, aggregating stock from hundreds of independent boutiques and brand partners into a single storefront. Because inventory is federated rather than owned, the same designer product frequently appears at different prices from different sellers in different countries.

why teams track it

Why Farfetch data is worth having

That federated structure is exactly what makes Farfetch valuable as data: it is the widest available view of luxury inventory and the only practical way to observe cross-boutique price dispersion on the same SKU. Brands use it to monitor how their products are actually being priced in the wholesale channel.

Visit farfetch.com

collection method

How we collect Farfetch

Farfetch is collected through Farfetch's internal JSON API, which returns the multi-boutique inventory with seller attribution intact. Every source gets a dedicated collector rather than a generic crawler, because the field detail that makes this data useful only survives if the extraction is built for the site it runs against.

Structured at the source

Records are read from farfetch.com's own structured responses wherever they exist, rather than reconstructed from page markup. That keeps the feed stable across visual redesigns.

Validated every run

Each field is checked against expected types and historical ranges. A collector producing anomalies is quarantined and repaired upstream instead of emitting bad prices into your pipeline.

Normalised to one schema

Every brand in the catalogue lands on the same schema, so adding a source is a configuration change on your side rather than another integration to write.

15min
Fastest refresh
99.9%
Uptime SLA
3
Delivery formats
49+
Fashion sources

what you get back

Fields in the Farfetch feed

A normalised core that is identical across every source, plus the attributes that are specific to this one.

Standard across every source

  • Product name, brand, and source URL
  • Current price, original price, and currency
  • Category and subcategory as the source classifies them
  • Colour, size, and variant availability
  • Product images, deduplicated across variants
  • Description, composition, and care text
  • Collection timestamp on every record

Specific to Farfetch

  • Seller and boutique attribution per listing
  • Designer and brand as separate fields from the product name
  • Cross-boutique price dispersion on identical products
  • Size availability per seller

SOC 2 Type II

Audited controls across security, availability, and confidentiality. Report available under NDA.

GDPR & CCPA

Public catalogue data only. No personal data collected, and a DPA is available on request.

99.9% Uptime SLA

Contractual availability with monitored collectors and a public status page.

Data residency

Choose EU or US processing and storage regions to match your obligations.

questions

Frequently Asked Questions

Everything you need to know before you send us your first request.

Yes. Seller attribution is preserved per listing, and for a marketplace it is the most important field in the record. Without it you cannot tell whether a price gap reflects a genuine market move or simply two different boutiques in two different countries.
Yes. Designer is a first-class field, so the feed can be filtered to one brand and used to monitor how that brand is priced and discounted across every boutique on the platform. That is the most common use for this source among brand-side customers.
Into the systems you already run, rather than through an API you have to integrate against. Normalised records land as JSON, CSV, or Parquet in S3, GCS, or Azure Blob, or straight into Snowflake or BigQuery, on whatever cadence you set. Webhooks can push price and availability changes as they are detected. A solutions engineer fixes the schema, cadence, and destination with you during onboarding, so the first delivery already matches your pipeline.
Maintaining the collector is our job, not yours. Every field is validated against expected types and historical ranges on each run, and a collector that starts producing anomalies is quarantined rather than allowed to emit bad records. We repair it upstream, and the schema we deliver to you does not move — which is the entire reason to buy this rather than run a scraper in-house.
We collect only publicly visible catalogue data — the prices, descriptions, images, and availability any shopper sees without logging in. We do not bypass authentication, we do not collect personal data, and we honour rate limits so the source is never disrupted. Our infrastructure is SOC 2 Type II certified, our processing is GDPR and CCPA compliant, and we sign DPAs as part of procurement.
Pricing is scoped per engagement, driven by catalogue size, refresh cadence, the number of locales you need, and the delivery destinations involved. Historical backfill is quoted separately. Every engagement starts with a free sample pulled from the live farfetch.com catalogue, so you can check the data against your own benchmarks before committing to anything.

Still have questions?

Talk to an engineer

Ready to Get Started?

Talk to us about your sources and volume. We'll return a sample dataset from your target sites before you commit to anything.

SOC 2 Type II
GDPR & CCPA compliant
99.9% uptime SLA

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