Top 3 by supplier depth: Discover Cars (30), Do You Spain (28), Economy Bookings (25).
Evidence: Supplier ranking table•Type: Internal supplier snapshot•Confidence: High
Car Rental Brokers With The Broadest Supplier Networks
Compare inventory depth across brokers and see which platforms connect you to the most suppliers worldwide.
Methodology
Reliability Index is calculated as: 25% Review Signal (multi-source), 25% Traffic, 25% Suppliers, and 25% Language Support.
Last updated: March 2026
| # | Reliability IndexRI Reliability Index is calculated as: 25% Review Signal (multi-source), 25% Traffic, 25% Suppliers, and 25% Language Support. | CompanyCar Rental Comparison | Average suppliers per locationSuppliers/location Average suppliers per location across 20 popular travel destination airports balanced across continents, based on live search results. no data is displayed when unavailable and sorted as 0. |
|---|---|---|---|
| 1 | 92 | 30 | |
| 2 | 67 | 28 | |
| 3 | 62 | 25 | |
| 4 | 52 | 23 | |
| 5 | 49 | 22 | |
| 6 | 53 | 21 | |
| 7 | 47 | 21 | |
| 8 | 44 | 21 | |
| 9 | 41 | 21 | |
| 10 | 56 | 20 | |
| 11 | 74 | 16 | |
| 12 | 56 | 16 | |
| 13 | 53 | 16 | |
| 14 | 48 | 16 | |
| 15 | 41 | 16 | |
| 16 | 36 | 16 | |
| 17 | 34 | 16 | |
| 18 | 32 | 16 | |
| 19 | 51 | 15 | |
| 20 | 47 | 15 | |
| 21 | 32 | 15 | |
| 22 | 25 | 14 | |
| 23 | 37 | 11 | |
| 24 | 56 | 10 | |
| 25 | 34 | 10 | |
| 26 | 31 | 8 | |
| 27 | 30 | 8 | |
| 28 | 24 | 7 | |
| 29 | 17 | 2 | |
| 30 | 40 | n/a | |
| 31 | 39 | n/a | |
| 32 | 34 | n/a | |
| 33 | 32 | n/a | |
| 34 | 23 | n/a | |
| 35 | 21 | n/a |
Independent Method
How We Calculate Average Suppliers Per Location
Live search captureIndependent QA normalizationUpdated: March 2026
Independently collected, not self-reported by providers
We use live, destination-level checks instead of relying on company self-reported supplier totals. Self-reported totals can be hard to compare in practice because they may include inactive suppliers, duplicated entities, white-label entities, or suppliers concentrated in low-demand locations.
Method Steps
Define a benchmark set of 20 popular travel destination airports balanced across continents.
Run equivalent live searches across each comparison site.
Extract visible supplier availability from real result pages.
Normalize and quality-check extracted supplier entities.
Compute company-level average suppliers per location.
Apply QA reruns for unstable or blocked search sessions.
Why This Is Better For Comparison
Measures what users actually see in live search results.
Comparable across companies on the same destination benchmark set.
Reflects practical choice depth on popular demand locations.
More decision-useful than aggregate lifetime supplier totals.
How We Built The Airport Set
We selected locations from real Google demand, not from a pre-picked destination list. We started with the top source countries where people both travel a lot and frequently rent cars: this avoids over-weighting markets where group tours or strong public transport lower car-rental intent.
🇺🇸United States🇨🇦Canada🇦🇺Australia🇬🇧United Kingdom🇩🇪Germany🇮🇹Italy🇫🇷France🇪🇸Spain🇳🇱Netherlands🇧🇷Brazil
1. For each source-country locale, we extracted car-rental keywords in the "car rental + location" pattern with Ahrefs 12-month average monthly volumes.
2. We merged demand across all 10 source countries into one comparable demand table (`Total Volume`).
3. We selected the strongest airport locations globally, with a cap of 3 airports per country to prevent one country from dominating the benchmark.
Italy example: noleggio auto catania aeroporto (5,500 avg monthly searches)
Germany example: mietwagen mallorca flughafen (4,100 avg monthly searches)
Why airports? They are precise, globally comparable pickup points. City-level keywords have fuzzy geographic radius, while airport terms map to exact pickup intent and are more consistent across markets. In our last-12-month demand sample, airport-intent queries represented 90%+ of pickup-intent signals.
Top 20 Airport Benchmark
`Total Volume` = summed demand across the 10 source-country locales over the last 12 months. `Annual Flights (approx)` = latest available aircraft movements/operations per airport.
| Airport | IATA | Country | City | Total Volume | Annual Flights (approx) |
|---|---|---|---|---|---|
| Phoenix Airport | PHX | 🇺🇸United States | Phoenix | 17,200 | 487,143(2025) |
| Orlando Airport | MCO | 🇺🇸United States | Orlando | 13,800 | 386,904(2025) |
| Tampa Airport | TPA | 🇺🇸United States | Tampa | 13,700 | 226,398(2025) |
| Dublin Airport | DUB | 🇮🇪Ireland | Dublin | 13,350 | 226,181(2025) |
| Alicante Airport | ALC | 🇪🇸Spain | Alicante | 10,300 | 116,270(2024) |
| Mallorca Airport | PMI | 🇪🇸Spain | Palma de Mallorca | 10,000 | 246,486(2025) |
| Malaga Airport | AGP | 🇪🇸Spain | Malaga | 9,800 | 161,684(2023) |
| Olbia Airport | OLB | 🇮🇹Italy | Olbia | 8,800 | 42,313(2024) |
| Palermo Airport | PMO | 🇮🇹Italy | Palermo | 8,600 | 65,091(2024) |
| Faro Airport | FAO | 🇵🇹Portugal | Faro | 7,600 | 67,510(2025) |
| Brisbane Airport | BNE | 🇦🇺Australia | Brisbane | 7,000 | 218,010(2024) |
| Lisbon Airport | LIS | 🇵🇹Portugal | Lisbon | 6,850 | 226,990(2025) |
| Melbourne Airport | MEL | 🇦🇺Australia | Melbourne | 6,450 | 217,041(2023) |
| Nice Airport | NCE | 🇫🇷France | Nice | 5,750 | 109,455(2024) |
| Edinburgh Airport | EDI | 🇬🇧United Kingdom | Edinburgh | 5,350 | 115,076(2023) |
| London Heathrow Airport | LHR | 🇬🇧United Kingdom | London | 4,900 | 473,965(2024) |
| Sydney Airport | SYD | 🇦🇺Australia | Sydney | 4,600 | 295,767(2023) |
| Athens Airport | ATH | 🇬🇷Greece | Athens | 3,900 | 283,589(2025) |
| Rome Airport | FCO | 🇮🇹Italy | Rome | 2,850 | 315,597(2024) |
| Marrakech Airport | RAK | 🇲🇦Morocco | Marrakech | 2,350 | 48,150(2023) |
Sources
- Ahrefs Help: Monthly search volume vs Average search volume
- Ahrefs Help: How accurate is keyword search volume in Ahrefs?
- Google Ads Help: About Keyword Planner forecasts
- Google Ads Help: Use Keyword Planner
Airport traffic references by location (latest available year)
PHX - Phoenix Airport (2025)MCO - Orlando Airport (2025)TPA - Tampa Airport (2025)DUB - Dublin Airport (2025)ALC - Alicante Airport (2024)PMI - Mallorca Airport (2025)AGP - Malaga Airport (2023)OLB - Olbia Airport (2024)PMO - Palermo Airport (2024)FAO - Faro Airport (2025)BNE - Brisbane Airport (2024)LIS - Lisbon Airport (2025)MEL - Melbourne Airport (2023)NCE - Nice Airport (2024)EDI - Edinburgh Airport (2023)LHR - London Heathrow Airport (2024)SYD - Sydney Airport (2023)ATH - Athens Airport (2025)FCO - Rome Airport (2024)RAK - Marrakech Airport (2023)
How We Treat No Data
Some companies return no data because supplier brands are hidden in their booking flow, so supplier-level visibility cannot be validated.
Some companies return no data because search endpoints were not operational in the collection window, so no comparable supplier snapshot could be collected.
We display n/a in the table and treat supplier signal as 0 in Reliability Index calculations when supplier data is unavailable.
In our methodology, transparency on supplier visibility is considered an important quality signal for users.
Why This Analysis Is Hard
This work is operationally heavy: there is no universal supplier API across comparison sites, data structures differ by site, and repeated semi-manual QA is needed to keep extraction quality stable. To our knowledge, independent location-level supplier benchmarking at this breadth has rarely been published in a systematic way.
Key claims
Claim + evidenceBottom 3 by supplier depth: Vroom Vroom Vroom (8), Airport Rental Cars (7), TUI Cars (2).
Evidence: Supplier ranking table•Type: Internal supplier snapshot•Confidence: High
Top-3 companies represent 17.5% of total supplier coverage in the listed set.
Evidence: Supplier concentration from ranking table•Type: Internal supplier snapshot•Confidence: High
Supplier depth is a structural inventory signal and should be read together with reviews and traffic, not as a standalone quality verdict.
Evidence: Supplier methodology•Type: Interpretation rule•Confidence: High
Supplier depth uses average suppliers per location across 20 popular travel destination airports balanced across continents, measured from live search results.
Evidence: Supplier data source•Type: Data collection method•Confidence: Medium
Higher supplier count usually improves breadth of choice, but does not guarantee higher customer satisfaction.
Evidence: Supplier limitations•Type: Guardrail•Confidence: High
Reliability Index Methodology
Methodology
Score Mix
Coverage-focused weighting.
Signals
Review signal (multi-source)
Traffic
Suppliers
Languages
Balanced for trust.
Why It Matters
The Reliability Index blends multi-source reviews, traffic, supplier coverage, and language support to create a single ranking.
RI
Stable weights, refreshed data.25%Customer Trust
Review signal reflects service reliability, while the reviews page blends multiple sources.
25%Market Popularity
Traffic shows real-world demand and market visibility.
25%Inventory Depth
Supplier connections indicate coverage, availability, and choice.
25%Languages
Language support reflects accessibility for international travelers.
Reliability Index: 25% Review Signal (multi-source), 25% Traffic, 25% Suppliers, 25% Language Support. Reviews page aggregates multiple sources.
We keep weights stable so changes reflect performance shifts rather than rule changes.
Suppliers FAQ
FAQ
What does supplier count represent?
It shows the average number of suppliers found per location across a balanced set of 20 popular travel destination airports.
Does a higher supplier count always mean better prices?
Not always. More suppliers usually means more choice, but final price still depends on destination, dates, and policy terms.
Why can a broker with many suppliers rank lower overall?
Because the Reliability Index also weights review signal and traffic, not supplier coverage alone.
Can supplier coverage differ by country?
Yes. Local partnerships vary, while this table shows a global roll-up view.
Why focus on airports instead of city-level searches?
Airport locations are unambiguous and comparable across markets. City-level intent is noisier because users may mean a wide metro area, downtown, or nearby locations. In leisure travel, most pick-ups happen after landing, so airport demand is a cleaner global benchmark.
Why are some high-travel countries not in the top source-country set (for example, Japan)?
We filtered for countries with both high travel volume and high car-rental search intent. Some countries travel heavily but rent less often due to local travel behavior or public transport convenience. Japan is a typical example where search and rental propensity are lower relative to total travel volume.