Global Hotel Data Scraping Index 2026 Top 30
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- June 26th, 2026
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The Global Hotel Data Scraping Index: Methodology and Purpose
Travel Data Scrape's Global Hotel Data Scraping Index 2026 is the hospitality industry's most comprehensive ranking of international hotel chain expansion opportunities, built entirely on data extracted through live hotel data scraping — not modeled, not estimated, not sourced from static industry reports. The index synthesizes over 8 million hotel property data points extracted from 195 countries across 14 source types: Booking.com, Expedia, Hotels.com, Agoda, Trip.com, Traveloka, MakeMyTrip, Despegar.com, Jalan.net, Almosafer, Otelz, TripAdvisor, Google Maps, and individual brand direct websites in 47 languages.
The result is a ranking system that reflects the actual state of hotel chain supply globally — not the state as reported by chains themselves, which inevitably reflects marketing positioning rather than verified property counts. Travel Data Scrape's hotel data extraction approach provides an independent, third-party verified supply picture that our clients use to challenge vendor claims, validate investment theses, and identify opportunities that standard industry research consistently misses.
Top 30 Global Hotel Expansion Markets — Ranked by Hotel Data Scraping Gap Score 2026
| Rank | Market | Region | Scraping Score | Leading Chain | Key Data Signal |
|---|---|---|---|---|---|
| 1 | Riyadh, Saudi Arabia | Middle East | 94.2 | Marriott | Almosafer scraping: 890% demand growth |
| 2 | Boise ID, USA | North America | 91.8 | Hilton | Expedia search: 67% YoY demand surge |
| 3 | Da Lat, Vietnam | SE Asia | 90.4 | Accor | Traveloka: 6.8M visits, 3 branded props |
| 4 | Qiddiya, Saudi Arabia | Middle East | 89.7 | All Chains | Zero OTA listings — confirmed via scraping |
| 5 | Manaus, Brazil | Latin America | 88.1 | Accor | Hoteis.com: 187 props, 0 luxury chain |
| 6 | Kanazawa, Japan | NE Asia | 87.9 | Hyatt (Dream) | Jalan.net: 12 chain props, 400K intl arrivals |
| 7 | Belitung, Indonesia | SE Asia | 87.3 | Accor | Traveloka: 43 props, viral IG growth |
| 8 | Tulum, Mexico | Latin America | 86.8 | Marriott | Despegar: 31% growth, 6 chain props |
| 9 | Medellín, Colombia | Latin America | 85.9 | IHG | Despegar: 89% search increase 2025-26 |
| 10 | Bhubaneswar, India | South Asia | 85.4 | IHG (HIX) | MakeMyTrip: 847 total, 1 intl chain |
| 11 | Abha, Saudi Arabia | Middle East | 84.7 | Hilton | Almosafer: mountain tourism 40% growth |
| 12 | Quy Nhon, Vietnam | SE Asia | 84.1 | All Chains | Mytour: 89 props, gov priority zone |
| 13 | Labuan Bajo, Indonesia | SE Asia | 83.8 | Hyatt (Alila) | Traveloka: 187 props, 6 branded only |
| 14 | Tulsa OK, USA | North America | 83.2 | Wyndham | Hotels.com: 13 chain props, corp gap |
| 15 | Oaxaca, Mexico | Latin America | 82.9 | Marriott | Despegar: 22% growth, 9 chain props |
| 16 | AlUla, Saudi Arabia | Middle East | 82.4 | IHG | Saudi TA registry: UNESCO demand surge |
| 17 | Florianopolis, Brazil | Latin America | 81.8 | Hilton | Hoteis.com: affluent leisure, 8 chains |
| 18 | Kadikoy, Istanbul | Europe | 81.3 | IHG | Otelz: Asian-side first mover signal |
| 19 | Lombok Mandalika | SE Asia | 80.9 | Marriott | Traveloka: SEZ designation, 5 chains |
| 20 | Huntsville AL, USA | North America | 80.2 | Hilton | Expedia: 8-day lead time compression |
| 21 | Batumi, Georgia | Europe | 79.8 | Wyndham | Booking.com: Black Sea 44% growth |
| 22 | Tbilisi, Georgia | Europe | 79.4 | Marriott | Booking.com: Caucasus gateway surge |
| 23 | Nairobi, Kenya | Africa | 78.9 | Radisson | Booking.com Africa: East Africa hub |
| 24 | Merida, Mexico | Latin America | 78.4 | Hilton | Despegar: 18% growth, 12 chain props |
| 25 | Busan, South Korea | NE Asia | 77.9 | Hyatt | Agoda: K-culture boom, 8-prop gap |
| 26 | Phu Quoc, Vietnam | SE Asia | 77.3 | IHG | Agoda: casino resort demand signal |
| 27 | Aswan, Egypt | Africa | 76.8 | Accor | Booking.com: Nile cruise gateway |
| 28 | Raja Ampat, Indonesia | SE Asia | 76.4 | Accor (Mantis) | Traveloka: dive tourism, 3 chains |
| 29 | Spokane WA, USA | North America | 75.9 | Marriott (Fairfield) | Hotels.com: 9 chains, healthcare growth |
| 30 | Belem, Brazil | Latin America | 75.4 | IHG | Hoteis.com: Amazon COP city, 4 chains |
Source: Travel Data Scrape Global Hotel Data Scraping Index 2026 | 8M+ property data points | 14 OTA platforms | 195 countries | 47 languages | Extracted: June 2026
How Each Gap Score Is Calculated Through Hotel Data Scraping
Every score in the Global Hotel Data Scraping Index is derived from live-extracted data — not analyst estimates. The scoring engine combines five weighted hotel data extraction signals: international chain property count per 100,000 population (scraped from all major OTAs, weighted 20%), OTA search demand growth rate (extracted from Booking.com and Expedia search data via our demand scraping pipeline, weighted 25%), supply-demand gap ratio (total scraped supply vs projected demand, weighted 25%), political and economic stability index (sourced from publicly available government databases, weighted 15%), and tourism infrastructure score (airport capacity, transport connections, government investment announcements — all extracted via data scraping, weighted 15%).
The combination of demand-side scraping (what travelers are searching for) with supply-side scraping (what hotel properties are available) is what makes Travel Data Scrape's index uniquely reliable. An OTA demand scraping signal showing 890% growth in Riyadh searches without the corresponding supply count from our hotel location extraction would be meaningless in isolation — it is the gap between the two scraped datasets that creates actionable intelligence.
Wyndham Hotels: The Scraping Intelligence Story in Tier-2 USA and Eastern Europe
Wyndham Hotels & Resorts appears as the recommended leading chain for Tulsa (#14) and Batumi (#21) in Travel Data Scrape's index — two markets that most hotel data scraping services underanalyze because they fall outside the premium segment focus of most intelligence platforms. Wyndham's economy and midscale brands (La Quinta, Days Inn, Ramada, Super 8) target exactly the Tier-2 USA and emerging Eastern European markets where Travel Data Scrape's hotel chain location data extraction shows the strongest supply-demand gaps relative to price-point demand signals.
For Tulsa specifically, Travel Data Scrape's hotel data scraping across Hotels.com, Booking.com, and Expedia confirms only 13 combined Marriott-Hilton properties — but the corporate travel demand signal extracted from Expedia for Business search data shows Tulsa's corporate travel volume growing at 14% annually, driven by energy sector expansion and manufacturing facility openings. This is exactly the demand profile that generates consistent occupancy for Wyndham's La Quinta brand.
Hotel Data Scraping for Competitive Strategy: Using the Index
The Global Hotel Data Scraping Index is designed as a strategic screening tool for hospitality investors, franchise development teams, and travel technology companies. Markets scoring above 85 warrant immediate custom hotel data extraction reports — Travel Data Scrape can deliver city-specific supply-demand analysis, complete competitive set mapping via hotel location data scraping, pipeline intelligence, and daily pricing extraction for any of the 30 ranked markets within 48 hours of request.
For OTA platforms and travel technology companies, the index identifies markets where search-to-booking conversion rates are likely to be highest due to supply constraints — the markets where demand exceeds supply predictably create the urgency-driven booking behavior that generates premium OTA margins. Travel Data Scrape's hotel data scraping platform can deliver daily pricing and availability extraction for any index market to support dynamic content and yield optimization strategies.
About Travel Data Scrape
Travel Data Scrape is the world's leading hotel data scraping and location intelligence company. Our platform extracts 8 million+ hotel property data points across 195 countries from 14 OTA platforms in 47 languages with daily refresh. Clients include global hotel investment funds, OTA platforms, franchise development teams, revenue management consultancies, and travel technology companies.
Request a demonstration, custom report, or API access at www.traveldatascrape.com. Our hotel data scraping specialists respond within 24 hours.
