Platform · Accor

Accor Data Scraping

A European-weighted estate with a large economy presence. The portfolio mix is different from the US groups, and so is what a panel here shows.

Accor data scraping collects rates, room types, plan conditions and availability across the group's brands. What distinguishes it from the US-headquartered groups: the estate is European-weighted with a large economy and midscale presence. So a European hotel panel that omits it is missing a large share of the market it claims to cover, and its portfolio mix makes it a different comparator.

Most hotel-group data work is built around the US groups. In European markets this one frequently has the density the others do not.

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accor.jsonl LIVE FEED

{"group":"accor","brand_tier":"economy", "property_id":"ac-44120","country":"FR", "rate_public":68.00,"currency":"EUR", "fx_observed_at":"2026-08-25T06:02Z", "ownership_model":"franchised"} {"brand_tier":"luxury","country":"FR", "rate_public":420.00, "note":"same market, same group. tier scope decides what your panel actually covers"} {"property_count_by_tier":{"economy":214,"midscale":96,"upscale":41,"luxury":12}, "caution":"a panel can look complete at upscale and be thin at economy"}

3 of 3,404,110 property-plan rows · EU-weightedproperty count BY TIER per market · schema v1.0

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

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Accor at a glance

How we handle Accor specifically

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

Group: Accor — European-weighted, global
The point: Large economy and midscale estate in Europe
Consequence: A European panel without it is thin
Portfolio: Economy through luxury. Tier is a dimension
Member rates: Loyalty rates below OTA-displayable. Gated
Markets: Many European markets, priced independently
Currency: Several, with FX stamped per observation
Refresh: Daily per stay date; lead time matters

Platform specifics

European density, and what a panel needs

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

Economy and midscale density is the coverage argument

The group's European estate is weighted toward economy and midscale brands, at a density the US-headquartered groups do not match in most European markets.

For a European hotel panel that has two consequences:

Omitting it leaves a coverage hole concentrated in the tiers where volume is.
Including only its upscale brands misses the part of the estate that gives it density.
So tier scope matters more here than on a group whose estate is evenly spread.
And a market-level panel can look complete at upscale and be thin at economy.

brand_tier is on every record and we report property_count_by_tier per market, so a panel's tier coverage is visible rather than assumed — the discipline our coverage page sets out.

Which changes the comparison

In a European market, an economy property here competes against economy properties from other operators and from independent hotels — not against this group's own upscale brands. Tier-matched comparison is the only valid one.

Many markets, several currencies, and the group mechanics

Markets and currency

The European estate spans markets with different price levels, currencies and competitive structures. country is a dimension, FX is stamped per observation, and a regional average is a computed rollup rather than a primary figure — the argument on our country dimension page.

Group mechanics

Member rates gated below OTA-displayable levels with the share reported, points captured and never converted, rate plans as the record, property as the unit. All set out on our hotel chain direct page, applied here unchanged.

Ownership

The estate includes owned, managed and franchised properties in differing proportions by market. ownership_model is recorded where published and unstated where not, because rate latitude differs between them.

What we do not collect

Owner or franchisee identities, management agreements, occupancy, bookings, guest data or loyalty account data. No accounts created, in any market.

Scope

What we collect on Accor, 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_tier on every record, with property_count_by_tier per market
country as a dimension, with FX stamped per observation
Regional figures as computed rollups, not primary figures
ownership_model where published, unstated where not
Publicly visible rates, with gated ones null and a reason
gated_share reported per brand and tier before quoting
One record per rate plan, with conditions structured
Point cost as displayed, never converted
Property as the unit, with property_count_observed on rollups

❌ What we do not, and why

A tier-mismatched comparison within or across groups
A European average presented as a primary figure
A public rate substituted for a gated member rate
An ownership model assumed where not published
Occupancy, bookings, guest, owner or loyalty account data

Core Accor fields

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

Field	What it is on this platform
group / brand / brand_tier	Tier is the dimension that matters here
property_id / city / country	The unit, and its market
property_count_by_tier	Per market. So tier coverage is visible
ownership_model	Where published. Rate latitude differs by model
rate_plan_id / rate_plan_type	The record is the plan
rate_public / rate_member / gated_reason / gated_share	Visible, gated, and the share
currency / fx_rate / fx_observed_at	Stamped at observation
stay_date / observed_at / lead_time_days	Both dates and the derived axis
points_cost / points_cash_equivalent	As displayed, never computed
property_count_observed	Stated on any rollup
availability_state	Available, sold out or not listed

Use cases

What teams do with Accor data

European market coverage

Property count by tier per market, so a European panel's coverage is visible at economy and midscale rather than looking complete because upscale is well covered.

Tier-matched European benchmarking

Brand tier on every record, since an economy property competes against other operators' economy estates and independents rather than against its own group's upscale brands.

Multi-market rate analysis

Country as a dimension with FX per observation across European markets that differ in price level and competitive structure.

Parity monitoring with the hole stated

Gated share per brand and tier, so a parity study states what proportion of the direct channel it could not see.

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

Send us a Accor 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.

Accor is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Accor 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 travel & hospitality data covers, and a Accor-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

Accor data scraping: frequently asked questions

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

Because its European estate is weighted toward economy and midscale brands at a density the US-headquartered groups do not match in most European markets.

Omitting it leaves a coverage hole concentrated in the tiers where volume is, and including only its upscale brands misses the part that gives it density.

We report property count by tier per market. A panel can look complete at upscale and be thin at economy, and without the tier breakdown that is invisible.

As a computed rollup with country detail retained, if you ask. Not as a primary figure.

European markets differ in price level, currency and competitive structure, so a regional average describes none of them.

Rate latitude differs between owned, managed and franchised properties, so yes. We record the model where the group publishes it and leave it unstated where it does not.

Only where publicly displayed. We do not create accounts or use client credentials in any market.

We report gated share per brand and tier so the parity hole is quantified rather than hidden.

We quote individually on properties times stay dates times rate plans times observations, with market count affecting it since each European market needs its own currency handling.

One scoping call, a free pilot within 24 hours including property count by tier, then a fixed monthly quote. Request a quote.

See real Accor 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.

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