Platform · Brand D2C sites

Brand D2C Fashion Data

Every stockist comparison needs one number to compare against, and one code to match on. Both come from the brand's own site.

Brand D2C fashion data covers brands' own direct-to-consumer websites. Their role in fashion data is structural: the brand site sets the reference price and publishes the style and colourway codes that stockists inherit. So it anchors every stockist comparison — and because there are thousands of brand sites, the engagement starts with which brands, which markets, and verifying the site is the brand's.

Most fashion pages in this set are about one retailer. This one is about the thing every retailer page is measured against.

Get a free sample See sample data

Free pilot on your own Brand D2C sites list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

brand_d2c.jsonl LIVE FEED

{"brand_name":"brand-a","source_url":"brand site, verified", "site_verified":true,"storefront_type":"brand", "brand_style_code":"as published","colourway_code":"as published", "price":220.00,"market_observed_from":"GB"} {"storefront_type":"regional_distributor", "used_as_brand_reference":false} {"site_verified":false,"verification_basis":"domain not linked from brand", "caution":"an unverified site is never the reference"}

3 of 604,880 product rows · brand listthe anchor for every comparison · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Brand D2C sites or its owners. Brand D2C sites and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

Our Data Powers

B2C Marketplace

amazon

D2C + Marketplace

NYKAA

D2C + Marketplace

Walmart

FMCG Marketplace

udaan

Food Delivery

Uber Eats

Quick Commerce

blinkit

Taxi Aggregator

Uber

E-Commerce

Tmall

Brand D2C sites at a glance

How we handle Brand D2C sites specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Scope: Fashion brands' own websites
Role: The reference price and the canonical codes
So: Anchors every stockist comparison
Discovery: Brand list first; site verified as the brand's
Markets: Priced per country; geo-served
Brand clearance: A brand's own sale is kept apart from stockists'
Members: Member-only content is a measured gap
Refresh: Daily where comparison is the aim

Platform specifics

The anchor for every comparison

These are the reasons a Brand D2C sites dataset needs its own handling rather than a shared retail schema.

Reference price and canonical codes

A stockist's price means something only relative to the brand's. And matching a stockist's product to anything depends on codes the brand defines.

The brand site shows the reference price directly, per market.
It publishes the style and colourway codes stockists carry, which makes it the strongest matching source.
A brand-site markdown is the brand clearing stock — a different event from a stockist's markdown.
A brand outlet section makes the brand a competitor as well, which our adidas page covers.

brand_style_code, colourway_code and price_setter: brand on every record, on a panel_schedule_id shared with the stockist panel.

Discovery, verification and markets

Which site is the brand's

Brand sites are frequently accompanied by regional distributor sites, authorised resellers with similar names, and impersonating sites. site_verified and verification_basis travel with every record, and an unverified site is not used as a reference.

Markets and geo-serving

Brand sites commonly serve a market-specific storefront by visitor location. market_observed_from is recorded on every price, and a regional distributor's storefront is recorded as such rather than as the brand.

Members and exclusives

Member-only product is a measured gap; brand-site exclusives are flagged and unmatched by construction.

What we do not collect

Customer or member data, stock quantities, or prices from an unverified site used as the brand reference.

Scope

What we collect on Brand D2C sites, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

brand_style_code and colourway_code as canonical keys
price_setter as brand throughout
site_verified and verification_basis on every record
market_observed_from on every price
Regional distributor storefronts recorded as such
Brand markdowns kept apart from stockist markdowns
Shared schedule with the stockist panel
gated_share for member-only content
Brand-site exclusives flagged and unmatched

❌ What we do not, and why

An unverified site used as the brand reference
A distributor storefront presented as the brand
A brand markdown treated as a stockist markdown
Account creation for member content
Customer data or stock quantities

Core Brand D2C sites fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
brand_name / source_url / site_verified	Which site, and how we know
verification_basis / storefront_type	Brand or regional distributor
brand_style_code / colourway_code	Canonical keys
price / currency / market_observed_from	The reference, per market
on_sale / markdown_started_at	The brand's own clearance
surface	main_range or outlet
is_exclusive	Brand-site exclusives
member_only_signposted / gated_share	The gap
size_availability	Per size
panel_schedule_id	Shared with stockists
observed_at	Timestamp

Use cases

What teams do with Brand D2C sites data

Reference price for stockist comparison

The brand's own price on canonical codes, per market, on a schedule shared with stockists.

Canonical matching

Brand-defined codes as the matching source, which is the strongest available in fashion.

Brand clearance timing

When the brand itself starts discounting, kept apart from stockist markdowns.

Distribution and impersonation mapping

Which sites are the brand's, which are regional distributors, and which are not verified.

The 24-hour sample — run on your sources, not ours

Send us a Brand D2C sites item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Brand D2C sites is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Brand D2C sites data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what fashion & apparel data covers, and a Brand D2C sites-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Brand D2C sites data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because every stockist price is only meaningful relative to the brand's, and matching depends on codes the brand defines. The brand site is where both come from.

We verify it and record how. Brand sites sit among regional distributors, similarly named resellers and impersonating sites, and an unverified site is never used as the reference.

Usually yes. Brand sites serve market-specific storefronts, so we record the market observed from on every price.

No. It is the brand clearing stock. We keep the two apart.

As many as are named. The engagement starts from a brand list, not a category crawl, because each site needs verifying.

We quote individually on brand count, markets and refresh. Brand count is the driver, since each site is its own source.

One scoping call, a free pilot within 24 hours on your brand list, then a fixed monthly quote. Request a quote.

See real Brand D2C sites data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

▶

1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

▶

2 min

★★★★★

"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."

Iulen Ibanez

CEO / Datacy.es

▶

1:30

★★★★★

"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."

Febbin Chacko

-Fin, Small Business Owner