Spain Booking.com Data Scraping 2022 2026 Market Report
                     Spain Booking.com Data Scraping: 
Market Report 2022–2026 on 
Property, Listing and 
Accommodation Trends
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Executive Summary
Spain is one of Europe's largest accommodation 
markets, and Booking.com is one of its most 
important distribution channels—which makes the 
platform's listings a rich lens on how the Spanish 
hospitality market has moved since the pandemic. 
This report from Travel Data Scrape examines 
property, listing, and accommodation trends across 
Booking.com in Spain over 2022–2026, showing how 
inventory grew, how the mix of accommodation types 
shifted, how rates moved, and how the picture varies 
by region. It is built on
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Booking.com data scraping structured into a 
consistent, comparable dataset, and it demonstrates 
the market intelligence that historical, platform-wide 
accommodation data makes possible.
The figures throughout are representative sample 
data drawn from the structure of Travel Data Scrape's 
dataset, included to illustrate the analysis the data 
supports. They are not audited market claims about 
Booking.com or the Spanish market; published 
reporting should be regenerated from the live 
dataset. What the sample makes clear is consistent 
with the shape of a post-pandemic recovery: listing 
counts rebuilt and then grew past 2019 levels, non- \
hotel accommodation gained share, rates climbed 
through the recovery, and regional performance 
diverged sharply between cities, coasts, and islands.
Methodology and Data Source
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The analysis rests on historical Booking.com 
accommodation data for Spain, collected and 
structured into a consistent schema. For each 
property and listing, the dataset captures the 
accommodation identity—property name, location, 
accommodation type, and star tier—alongside the 
commercial and descriptive detail that defines it: 
room and rate types, nightly rates, availability, 
cancellation terms, guest-review scores as an 
aggregate signal, and amenities. Tracked over time, 
these fields form a longitudinal view of how the 
market evolved across 2022–2026.
Collection distinguishes accommodation types— \
hotels, apartments, vacation rentals, hostels, 
guesthouses—and regions, since both dimensions 
behave very differently. Review content is treated as 
an aggregate score and count rather than 
reproduced, respecting the source. All figures in this 
report are illustrative samples that mirror this 
structure; they exist to show the shape of the data 
and the analysis it enables, and any figure intended 
for publication should be regenerated from the 
current live dataset. The value of the approach is not 
any single number but the ability to track the whole 
market, consistently, over years.
Key Findings
Across the 2022–2026 window, four patterns stand 
out in the sampled data. First, listing inventory 
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gmrew beyond pre-2020 levels, odmriven especially by 
non-hotel supply. Second, the accommodation mix 
shifted: apartments and vacation rentals gained 
share
against traditional hotels as travelers and hosts 
favored self-catering options. Third, average nightly 
rates rose through the recovery, with the steepest 
increases in high-demand coastal and island 
destinations. Fourth, regional divergence widened—
major cities, Mediterranean coasts, and the islands 
followed distinctly different trajectories rather than 
moving together.
Each of these patterns is invisible in a single-year or 
single-region snapshot, and each is exactly what 
historical, platform-wide accommodation data 
surfaces over the full 2022–2026 window.
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Listing and Property Growth, 2022–
2026
The table below shows a representative index of 
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illustrating the recovery-and-growtPho st-patnrdaejmeicc tory. 
Fig20u2r2es are illu1s0t0rative samp—les. recovery 
underway
Strong rebound in 
2023 118 +18.0%
leisure demand
Non-hotel supply 
2024 131 +11.0%
expansion
Continued 
2025 142 +8.4% vacation-rental 
growth
Maturing, steadier 
2026 150 +5.6%
growth
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The trajectory the sample illustrates is the point: 
rapid early recovery giving way to steadier, supply-
led growth, with the composition of that growth 
mattering as much as its size.
Accommodation Type Mix
The composition of supply shifted meaningfully over 
the period. The table below shows a representative 
share of listings by accommodation type, illustrative 
samples comparing 2022 and 2026.
Accommodatio
2022 Share 2026 Share Trend
n Type
Hotels 44% 37% Declining
Apartments 28% 34% Rising \
Vacation Rentals 15% 19% Rising
Hostels 7% 6% Flat/soft
Guesthouses/Ot
6% 4% Declining
her
The representative shift from hotels toward 
apartments and vacation rentals mirrors a broader 
European move toward self-catering and longer stays
—one that platform-wide data captures directly, 
whereas a hotels-only view would miss it entirely.
Nightly Rate Trends
Average nightly rates rose through the recovery, 
unevenly across the market. The sample JSON below 
shows a
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representative average daily rate (ADR) index for 
Spain, set to 100 in 2022.
{
  "market": "Spain",
  "metric": "adr_index",
  "base_year": 2022,
  "currency": "EUR",
  "series": [
    { "year": 2022, "adr_index": 100 },
    { "year": 2023, "adr_index": 112 },
    { "year": 2024, "adr_index": 121 },
    { "year": 2025, "adr_index": 128 }, \
    { "year": 2026, "adr_index": 133 }
  ],
  "note": "illustrative sample; steepest gains in 
coastal and island regions"
}
The representative pattern—rates climbing through 
the recovery and then moderating—tracks demand 
and supply moving back into balance, with the 
sharpest increases concentrated in the highest-
demand destinations.
Regional Divergence
Spain is not one market but several, and the sample 
data shows regions on distinct paths. The table below 
gives a
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representative view of listing growth and rate 
movement by region over the window, illustrative 
samples.
Region Listing Growth ADR Trend Character
Regulated, high-
Barcelona Moderate High rise
demand city
Business + leisure 
Madrid Strong Moderate
capital
Costa del Sol Strong High rise Coastal leisure, 
seasonal peaks
Island leisure, sharp 
Balearic Islands Moderate High rise
seasonality
Year-round leisure 
Canary Islands Strong Moderate
destination
The representative divergence is the analytical 
value: a national average hides that a regulated 
city, a sun-and-beach coast, and a year-round \
island market move on entirely different logics. 
Regional, platform-wide data is what makes those 
differences visible and actionable.
Seasonality and Availability Signals
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Beyond long-run trends, the data captures the 
seasonal rhythm that defines Spanish 
accommodation. Coastal and island regions show 
sharp summer peaks in both rates and occupancy-
driven scarcity, while major cities show flatter, event- 
and business-driven patterns. Tracking availability 
alongside rates over time reveals not just what 
accommodation cost but how tight supply ran—when 
properties filled, how far in advance, and how rates 
responded. A representative sample of this signal 
would show island and coastal availability tightening 
months ahead of peak summer while city availability 
stays comparatively steady year-round. This is the \
kind of pattern that informs both traveler-facing tools 
and revenue strategy, and it emerges only from 
longitudinal, region-aware collection.
Review Scores and Quality Signals
Alongside price and supply, guest-review scores—
treated as an aggregate signal rather than 
reproduced content—offer a window into how quality 
tracked with the market's growth. As non-hotel 
supply expanded rapidly, a natural question is 
whether average quality held or diluted. The 
representative sample suggests a nuanced answer: 
aggregate review scores stayed broadly stable across 
the period, with newer apartment and 
vacation-rental listings gradually closing the gap 
to established hotels as hosts professionalized. 
Tracking these scores over time, by accommodation 
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frmom a race to the bottom. om
For a hospitality group or a platform, this signal 
matters as
much as price. A region where listings surged but 
average scores softened tells a different competitive 
story than one where supply grew and quality held. 
Aggregate review trends, captured longitudinally 
alongside rates and inventory, turn a vague sense of 
"more listings" into a measured read on whether the 
market got bigger, better, or merely more crowded—
exactly the kind of composite intelligence platform-
wide historical data provides.
Booking Windows and Length of Stay
The period also reshaped how travelers booked. The 
shift toward apartments and vacation rentals came \
with a shift toward longer stays, as self-catering 
accommodation favors trips measured in weeks 
rather than nights—a pattern visible in the 
representative length-of-stay data. Booking windows, 
too, evolved through the recovery, lengthening as 
confidence returned and demand for peak coastal and 
island dates pushed travelers to reserve further 
ahead. Capturing these behavioral dimensions 
alongside price and supply rounds out the market 
picture: it is not only what accommodation cost and 
how much existed, but how people used it.
For revenue teams and platforms, length-of-stay and 
booking-window trends are directly actionable—they 
inform minimum-stay policies, pricing curves, and 
inventory planning. A market moving toward longer 
stays and earlier bookings rewards different 
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bmreaks, and only longitudinaol,m platform-wide data 
makes the shift measurable rather than anecdotal.
What the Data Means
Taken together, the patterns point to a clear 
conclusion: the Spanish accommodation market did 
not simply recover—it recomposed. Inventory grew 
past pre-pandemic levels, but the growth came 
disproportionately from apartments and vacation 
rentals rather than hotels; rates rose, but unevenly, 
concentrated in coastal and island demand; and 
regions diverged rather than moving in step. Any 
view built on a single year, a single region, or hotels 
alone would miss the actual story. The value of 
platform-wide, historical accommodation data is 
precisely that it captures the composition and the \
divergence, not just a headline average—turning a 
complex, multi-year market shift into a picture that 
can be measured, compared, and acted on.
For businesses, this matters because strategy 
depends on which slice of the market they touch. A 
hotel group reads the shift toward self-catering as 
competitive pressure; a vacation-rental platform 
reads it as tailwind; an investor reads regional 
divergence as where to allocate. The same dataset 
answers all three questions because it holds the 
whole market over time—and because it captures not 
just price and supply but quality, length of stay, and 
booking behavior, it answers questions those teams 
have not yet thought to ask.
Who Uses This Data
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Bmooking.com accommodation om data into an 
advantage. 
Hospitality groups and revenue teams benchmark 
their properties and rates against the wider market 
and track how competitors and accommodation types 
are trending. Vacation-rental and short-stay platforms 
size their opportunity and monitor supply growth. 
Investors and analysts assess market and regional 
trajectories before allocating capital. Tourism boards 
and researchers study accommodation supply, 
pricing, and seasonality across regions. And travel-
tech products build market intelligence, 
benchmarking, and pricing features on a consistent 
historical foundation. In each case, the report above 
is not a one-time artifact but a repeatable capability, \
refreshed continuously.
How Travel Data Scrape Delivers It
Travel Data Scrape supplies the foundation this report 
is built on: Booking.com data scraping for the Spanish 
market, structured into a consistent, historical 
dataset across property, listing, and accommodation 
dimensions; accommodation-type and regional 
granularity that reveals composition and divergence 
rather than a flat average; rate, availability, and 
review-score signals tracked over time; and clean, 
application-ready delivery via feed or API. The same 
discipline extends across markets and platforms, so a 
research program or product can expand beyond 
Spain and beyond one channel on a single consistent 
foundation. Reports like this one can be produced 
continuously from the live dataset rather than 
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Conclusion
The Spanish accommodation market of 2022–2026 is 
a story of recomposition, not just recovery—more 
listings, a shift toward self-catering supply, rising and 
uneven rates, and regions on divergent paths. None 
of that is visible from a snapshot or a single-segment 
view; it emerges only from historical, platform-wide, 
region-aware accommodation data. With Travel Data 
Scrape delivering that data through structured 
Booking.com data scraping, hospitality groups, 
platforms, investors, and researchers can move from 
headline averages to genuine market intelligence—
measuring the shift, comparing the regions, and \
acting on where the market is actually going.
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