How a Global Manufacturer Mapped Every Hotel Group, Chain & Brand in Europe — Without a Single Property Listing

Group→Sub-brand

full brand hierarchy mapped

Brand-level only

zero individual-property noise

Europe-wide

coverage across all major markets

Client: European arm of a global manufacturing major (name withheld)

Industry: B2B Manufacturing / Hospitality

Use Case: Brand/chain-level hotel market mapping

Geography: Europe-wide

Delivery: One-time structured dataset (CSV/Excel + API option)

Introduction

Our client is the European division of a global manufacturer whose products are specified into hotels (think building systems, equipment and fit-out categories). To plan its go-to-market — which groups to target, through which decision-makers, at what brand tier — the client needed a map of the European hotel industry structure: the groups, chains and brands, how they relate, and who to talk to. Crucially, it did not want a list of individual hotel properties. It wanted the org chart of the market, not the phone book.

The Challenge

• Brand-level, not property-level. Almost every hotel dataset on the market is property-level — millions of individual hotels. The client explicitly wanted the opposite: only groups, chains and brands, with no individual-property clutter diluting the dataset. This inverts how hotel data is normally sold.
• Hierarchy is the hard part. Hospitality brands nest — a group owns multiple brands, which have sub-brands. Capturing that group → brand → sub-brand hierarchy accurately, across Europe, was the core requirement.
• Attributes at the brand level. The client needed brand-level policies — amenities offered (pool, restaurant, air-conditioning), star-rating policy — plus, where available, management structure (franchise, management contract, lease, owner-operated) and development/operations contacts.
• Precise scope, precise exclusions. Getting this right meant being as disciplined about what to leave out (individual properties, overly granular detail) as about what to include.

The Actowiz Solution

1. Brand-Hierarchy Construction

We built the dataset around the hierarchy itself — mapping European hotel groups, their brands, and sub-brands into a clean parent-child structure. This structural backbone, not a property count, was the deliverable's spine.

2. Brand-Level Attribute Enrichment

Each brand was enriched with the requested policy-level attributes — brand HQ location, amenities policy, star-rating policy, and management structure where disclosed — assembled from multiple public sources into consistent fields.

3. Decision-Maker Contacts (Publicly Available)

Where publicly available, we added brand/chain-level contacts relevant to the client's outreach — development, operations and corporate roles — so the map was actionable for B2B targeting, not just descriptive.

4. Disciplined Scope Control

We deliberately excluded individual property listings and unnecessary granularity, keeping the dataset tightly at brand/chain level. The result is small, clean and high-signal — the opposite of the bloated property datasets the client wanted to avoid.

The Results

• Market org chart — the European hotel industry mapped as a clean group→brand→sub-brand hierarchy — the structural view the client's GTM planning actually needed
• High signal — zero individual-property noise; a small, curated brand-level dataset instead of a bloated property list nobody would use
• Actionable — brand-level policies and publicly available decision-maker contacts turned a market map into a targeting tool for the sales organization
• Exactly scoped — the discipline of excluding what the client didn't want was as valuable as including what they did — no wasted spend, no clean-up

Client Feedback

"Everyone tried to sell us millions of hotels. We wanted the map of who owns whom, at brand level, with the right contacts. Actowiz was the only one who understood we wanted less data, but the right data."

— Market Development Lead, Global Manufacturer (European division)

Why It Worked

• Understand the real ask. The insight was that the client wanted structure, not scale — inverting the default hotel-data product was the whole solution.
• Hierarchy over volume. A correct group→brand→sub-brand tree is worth more to a B2B seller than a million property rows.
• Discipline is a deliverable. Excluding property-level noise kept the dataset clean, actionable and precisely fit to the client's GTM process.

Need a Structured Market Map — Not a Data Dump?

Brand hierarchies, chain structures, decision-maker contacts, at exactly the granularity you need. Tell us your industry and geography; we'll scope a curated dataset and share a sample.

Frequently Asked Questions

Can you deliver brand/chain-level data instead of individual listings?

Yes — we scope datasets to exactly the granularity you need. Brand/chain-level market maps (with hierarchy) are as much a specialty as property-level datasets; the discipline of excluding noise is part of the value.

Can you map hierarchies in other industries?

Yes — group→brand→sub-brand structures apply to retail banners, restaurant groups, franchise networks and more. The parent-child mapping approach transfers across sectors.

Do you include decision-maker contacts?

Where publicly available, yes — development, operations and corporate roles at brand/chain level, so the dataset supports B2B targeting. We include only publicly available business contact information.

Is this a one-time dataset or refreshable?

Market maps are usually one-time, but can be refreshed periodically as brands launch, rebrand or restructure. We'll advise on a sensible cadence for your use.

Is this compliant?

We assemble the dataset from publicly available business and brand information, including only publicly available business contacts — no private personal data. Collection follows Actowiz's responsible-scraping framework.