We extract vehicle availability, base rates, tax structures, and location networks from Avis. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Vehicle Pricing objects from avis.com. All fields typed and schema-versioned.
"pickup_location": "JFK", "vehicle_class": "Intermediate SUV", "acriss_code": "IFAR", "make_model": "Toyota RAV4 or similar", "pay_now_rate": 64.5, "currency": "USD", "status": "Available"
| # | pickup_location | dropoff_location | pickup_datetime | dropoff_datetime | vehicle_class | acriss_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Location Data objects from avis.com. All fields typed and schema-versioned.
"location_code": "JFK", "name": "John F. Kennedy International Airport", "city": "New York", "latitude": 40.6413, "longitude": -73.7781, "location_type": "Airport", "operating_hours": "24 Hours"
| # | location_code | iata_code | name | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Add-ons & Extras objects from avis.com. All fields typed and schema-versioned.
"quote_id": "AV-99382-NY", "insurance_cdw": 29.99, "child_seat_fee": 14.0, "gps_fee": 16.99, "toll_pass_fee": 5.95, "currency": "USD"
| # | quote_id | vehicle_class | insurance_cdw | insurance_ali | child_seat_fee | gps_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Taxes & Fees objects from avis.com. All fields typed and schema-versioned.
"base_rate": 322.5, "total_tax": 28.62, "total_fees": 45.1, "concession_recovery_fee": 35.8, "energy_surcharge": 1.49, "grand_total": 396.22, "currency": "USD"
| # | quote_id | base_rate | total_tax | total_fees | concession_recovery_fee | vehicle_license_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Fleet Metadata objects from avis.com. All fields typed and schema-versioned.
"acriss_code": "IFAR", "category": "Intermediate", "transmission": "Automatic", "passenger_capacity": 5, "luggage_capacity": "2 Large, 1 Small", "example_make_model": "Toyota RAV4"
| # | acriss_code | category | type | transmission | fuel_air_con | passenger_capacity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Our Avis scraper handles every layer of the platform: dynamic availability, point-of-sale pricing, location mapping, and fee structures - with session token hydration and proxy routing built in.
Extract Pay Now and Pay Later rates across varying date ranges and booking lead times.
Scrape all Avis rental stations globally including operating hours, address details, and IATA mappings.
Map Avis vehicle classes to standard ACRISS codes for cross-brand fleet comparison.
Capture base rates separately from concession recovery fees, vehicle license fees, and local taxes.
Extract daily rates for CDW, ALI, child seats, GPS, and toll pass services per location.
Monitor pricing penalties and availability for asymmetric pickup and drop-off locations.
Execute searches from specific regional IPs to capture point-of-sale pricing variations.
Extract unlimited mileage indicators or per-mile overage charges for specific vehicle classes.
Track fleet utilisation signals by monitoring sold-out vehicle classes for peak travel dates.
Brief in. Clean data out.
Provide location pairs, date ranges, and vehicle classes. We design the extraction schema together.
We configure Scrapy crawlers, residential proxy rotation, and session token management for avis.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Avis employs strict rate limiting and session validation. Here is how we maintain extraction velocity.
Avis search endpoints require specific session tokens and encrypted payloads generated during the initial page load. We execute full browser sessions to acquire these tokens before shifting to high-throughput API extraction.
Car rental rates vary heavily based on the user's IP location. We route requests through residential ISP proxies matching your target point-of-sale to capture accurate regional pricing.
High-frequency date-range searches trigger Avis's rate limiters. Our infrastructure distributes queries across thousands of IPs with randomised delays to maintain continuous extraction without blocks.
Avis displays taxes and fees differently across jurisdictions. We parse raw booking summaries to normalise base rates, local taxes, and mandatory fees into a consistent schema.
Avis utilises heavy CDN caching for availability. We inject cache-busting headers and manipulate search parameters to ensure we extract live inventory rather than stale cached states.
OTA platforms and rival car rental brands track Avis rates across key airport locations to optimise their own pricing algorithms.
Financial analysts monitor sold-out states and price surges to estimate Avis fleet utilisation and revenue performance.
Travel management companies audit corporate negotiated rates against public Avis pricing to ensure contract compliance.
Revenue managers ingest historical Avis pricing data to train machine learning models for travel demand forecasting.
Meta-search engines verify API feeds against live site data to detect caching errors and price discrepancies.
Mobility startups analyse Avis station density and operating hours to identify underserved markets for new vehicle deployments.
"Car rental pricing is highly volatile and heavily gated by session tokens. Accessing historical and live Avis rates requires infrastructure built specifically for travel aggregators."
Most teams fail at extracting travel data because they rely on basic HTTP clients. Reliable Avis scraping requires full session hydration, point-of-sale IP routing, and complex payload generation. DataFlirt manages this entire extraction layer so your engineers can focus on yield management and pricing analysis.
Everything supported by our avis.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Avis requires complex token generation. We use Playwright to simulate the initial user journey, extract necessary cookies and tokens, and pass them to Scrapy for high-speed API consumption.
Pricing varies by user location. We maintain residential proxy pools across 40+ countries to simulate searches from specific geographic regions, ensuring accurate rate capture.
Travel data is notoriously unstructured. Our pipeline automatically maps Avis vehicle classes to standard ACRISS codes and separates bundled prices into discrete tax and fee columns.
Data delivered to where your team already works — no new tooling required.
About avis.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and availability data is generally permissible. DataFlirt extracts only public, non-authenticated search results. We do not bypass login walls or extract personal customer data.
Our pipeline automatically detects expired search tokens and triggers a headless browser session to acquire fresh credentials, ensuring uninterrupted data extraction.
We do not extract data using proprietary Avis Worldwide Discount (AWD) codes or corporate accounts, as this requires authenticated access and violates our terms of service.
Yes. We extract line-item costs for Collision Damage Waiver (CDW), Additional Liability Insurance (ALI), child seats, GPS units, and toll transponders.
Yes. We cover all international Avis domains and can extract location data including operating hours, IATA mappings, and available services for every branch.
We support extraction cadences ranging from real-time API polling for specific routes to daily bulk updates across thousands of location pairs.
Yes. The pipeline parses the final booking summary to provide a discrete breakdown of the base rate, concession recovery fees, local taxes, and total payable amounts.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off location extraction or a continuous price-monitoring feed across 10,000 routes - we scope, build, and operate the pipeline. Tell us what you need.
