Platform · Hertz

Hertz Data Scraping

Q: What does Hertz collection cost?

We quote individually. The grid drives it: locations times classes times date ranges times observation dates. Location pairs multiply quickly if one-way routes are in scope. One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

Nobody rents a car. They rent a class, from a location, over a date range — and the headline rate is not the bill.

Hertz data scraping collects rental rates, vehicle class availability and fee structures across locations and date ranges. Two things separate car rental from every other travel source: the record is a vehicle class at a location pair over a date range, not a car; and the quoted base rate is a minority of what a renter pays, because the fee and insurance stack sits on top.

A hotel rate is most of a hotel bill. A car rental base rate frequently is not, and a dataset that captures only the base rate is measuring the least important number.

Get a free sample See sample data

Free pilot on your own Hertz list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

hertz.jsonl LIVE FEED

{"vehicle_class":"intermediate", "example_model":"Example Model or similar", "model_guaranteed":false, "pickup_location":"LHR-airport","dropoff_location":"LHR-airport", "is_one_way":false, "pickup_date":"2026-10-14","rental_days":3, "base_rate":102.00,"currency":"GBP", "fee_airport":18.40,"fee_licensing":7.20, "tax_amount":25.52, "total_estimated":153.12, "rate_per_day_derived":51.04, "note":"base rate is 67% of total — a base-rate-only feed measures the wrong number"} {"is_one_way":true,"dropoff_location":"MAN-airport", "base_rate":102.00,"fee_oneway":145.00, "caution":"drop fee EXCEEDS the base rental. invisible in a single-rate feed"} {"rental_days":7,"rate_per_day_derived":38.90, "note":"7 days is cheaper PER DAY than 3 — pricing is not linear in duration"}

3 of 1,880,220 class-location-date rows per-day DERIVED from total · cover never in the rate · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Hertz or its owners. Hertz and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

Our Data Powers

B2C Marketplace

amazon

D2C + Marketplace

NYKAA

D2C + Marketplace

Walmart

FMCG Marketplace

udaan

Food Delivery

Uber Eats

Quick Commerce

blinkit

Taxi Aggregator

Uber

E-Commerce

Tmall

Hertz at a glance

How we handle Hertz specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Source: Hertz — car rental, globally
The record: A vehicle class at a location pair over a date range
Not: A specific car. Classes are guaranteed, models are not
The headline trap: Base rate is a minority of the total
Fee stack: Location surcharges, airport fees, taxes, young-driver fees — each separate
One-way: Drop fees can exceed the base rate. Captured separately
Insurance: Optional cover captured as options, never added into the rate
Refresh: Daily per pickup date; lead time matters as it does on hotels

Platform specifics

What makes car rental structurally different

These are the reasons a Hertz dataset needs its own handling rather than a shared retail schema.

The record is a class, a location pair and a date range

A hotel record is a room at a property on a night. A car rental record needs four things before it means anything.

Vehicle class — economy, compact, intermediate and so on. The renter is guaranteed a class, not a model. "Or similar" is doing real work in that listing.
Pickup location, which is frequently an airport with its own surcharges.
Drop-off location, which may differ — and if it does, the price changes substantially.
The date range, because rate per day is not linear. Weekly rates frequently undercut five daily ones.

All four are on every record. A "Hertz price" without them is not reproducible, in the same way a Google Shopping price without its query is not.

Why rate-per-day comparison misleads

Pricing is not linear in duration. A three-day and a seven-day rental at the same location can have very different per-day rates, and the cheaper per-day is frequently the longer one. We record rental_days and the total, and derive per-day rather than collecting it — so a comparison is always between equal durations.

The fee stack is most of the analysis

On a hotel, the room rate is most of the bill. On a car rental it frequently is not.

Airport concession and facility fees apply at most airport locations.
Vehicle licensing and road fees vary by jurisdiction.
One-way drop fees can exceed the base rental entirely on some routes.
Young-driver and additional-driver fees apply conditionally.
Taxes differ by state, country and sometimes by airport.

Every component is a separate field. We record base_rate, each fee with its own label, and total_estimated where the platform shows one — with total_basis naming what is included.

Insurance is not folded in

Collision damage waiver, liability supplements and similar cover are options, not part of the rate. We capture them as available options with their prices, and never add them into the rate.

A renter declining all cover and a renter taking full cover pay very different totals for the same reservation, and a single number describes neither.

What we do not produce, and one thing worth watching

Fleet

We do not report fleet size, utilisation or how many vehicles are at a location. None of it is published, and availability of a class tells you a class is bookable rather than how many cars sit on the lot.

Specific vehicles

We do not report which model a renter will receive, because the platform does not commit to one. Where a listing names an example model, we capture it as example_model with model_guaranteed: false.

Worth watching: class availability as a supply signal

A class becoming unavailable at a location, across a fixed panel over time, is the closest observable proxy for supply tightness — and it is an observation rather than an inference.

We deliver it as availability transitions. We do not convert it into a utilisation estimate, which would require assumptions about fleet size that nobody outside the operator can check.

Scope

What we collect on Hertz, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

Vehicle class, pickup and drop-off location, and date range on every record
Base rate with rental_days, and per-day derived rather than collected
Each fee as its own labelled field — airport, licensing, one-way, driver
total_estimated with total_basis naming what is included
Insurance and cover options with prices, never added into the rate
One-way drop fees captured separately, since they can exceed the base rate
Class availability transitions across a fixed location panel
example_model captured with model_guaranteed false
Pickup date and observation date, with lead time derived

❌ What we do not, and why

A per-day rate collected rather than derived from a total
Insurance folded into the rental rate
Fleet size, utilisation or vehicles on the lot
A specific model promised where the platform guarantees a class
Customer, driver or booking data

Core Hertz fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
vehicle_class / example_model / model_guaranteed	The class, an example, and that it is not a promise
pickup_location / dropoff_location / is_one_way	The location pair
pickup_date / rental_days / observed_at / lead_time_days	The date range, and both dates
base_rate / currency	Before any fee
fee_airport / fee_licensing / fee_oneway / fee_driver	Each separately labelled
tax_amount / tax_basis	Varies by jurisdiction and sometimes by airport
total_estimated / total_basis	Where shown, with what it includes named
rate_per_day_derived	Computed from total and days, never collected
cover_options	Available cover with prices. Not added to the rate
class_available	Availability of the class, not a vehicle count
mileage_policy	Unlimited or capped, as published

Use cases

What teams do with Hertz data

Competitive rate benchmarking that reflects the bill

Base rate plus each fee as its own field, so a comparison is between what renters pay rather than between headline rates that omit most of the cost.

One-way route pricing

Drop fees captured separately, which on some routes exceed the base rental entirely — invisible in any dataset that reports a single rate.

Duration-curve analysis

Rental days recorded with per-day derived, so a three-day and a seven-day quote are compared correctly rather than through a per-day figure that hides non-linear pricing.

Class availability as a supply signal

Availability transitions across a fixed location panel, delivered as observations rather than converted into a utilisation estimate nobody can verify.

The 24-hour sample — run on your sources, not ours

Send us a Hertz item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Hertz is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Hertz data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what travel & hospitality data covers, and a Hertz-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Hertz data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because that is what the platform sells. A renter is guaranteed a vehicle class, not a model — 'or similar' is doing real work in the listing.

Where a listing names an example model we capture it as example_model with model_guaranteed: false, so nothing downstream treats it as a commitment.

Because pricing is not linear in duration. A three-day and a seven-day rental at the same location can have very different per-day rates, and the cheaper per-day is frequently the longer one.

We record the total and the days, and derive per-day — so a comparison is always between equal durations rather than between two different products.

Frequently a minority, which is why every fee is a separate field. Airport concession fees, vehicle licensing, one-way drop fees, young-driver charges and taxes all sit on top and vary independently.

On some one-way routes the drop fee alone exceeds the base rental.

No. Cover is an option, not part of the rate. A renter declining all cover and a renter taking full cover pay very different totals for the same reservation, and one number describes neither.

We capture available cover with prices as options.

No. Fleet size and utilisation are not published, and class availability tells you a class is bookable rather than how many vehicles are on the lot.

We deliver availability transitions across a fixed panel, which is the closest observable proxy for supply tightness, and we do not convert it into a utilisation estimate.

We quote individually. The grid drives it: locations times classes times date ranges times observation dates. Location pairs multiply quickly if one-way routes are in scope.

One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Hertz data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

▶

1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

▶

2 min

★★★★★

"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."

Iulen Ibanez

CEO / Datacy.es

▶

1:30

★★★★★

"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."

Febbin Chacko

-Fin, Small Business Owner