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Automotive data extraction

Vehicle listings and price history, delivered as clean data.

We collect listings and prices, specs, mileage and dealer details from public car marketplaces and dealer websites.

Built around your sources and markets, delivered on your schedule.

Get a free sample from your own sources within 24 hours and see the data before you commit.

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vehicles.csvsample data
Illustrative sample of scraped vehicle listings. Select a vehicle to see its price history.
modelmakeyearmileage_miprice_usddays_listedstatus
Toyota202138,40022,90021▼ 6.5%
Ford201961,20031,50012unchanged
Honda202222,90023,8003new
Tesla202045,10027,90030▼ 6.7%
Subaru201874,30019,90024delisted
Illustrative data. Select a vehicle to see its price history.

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What you get

Every field you need from a vehicle listing.

These are the usual building blocks. We add or drop fields to fit your project, and the free sample shows exactly what comes back.

Vehicle

What the car is.

  • make
  • model
  • trim
  • year
  • body_type
  • fuel_type
  • transmission
  • drivetrain
  • vin

Price and offer

What it costs, and how that changes.

  • price
  • currency
  • previous_price
  • price_history
  • price_change_pct
  • monthly_payment
  • price_rating

Condition and history

What the listing says about its past.

  • mileage
  • condition
  • owners_count
  • accident_reported
  • service_history
  • inspection_status
  • warranty
  • title_status

Dealer and seller

Who is selling it. Public business details only.

  • seller_type
  • dealer_name
  • dealer_address
  • dealer_phone
  • dealer_website
  • dealer_rating
  • dealer_review_count
  • location

Listing history

How each listing changes over time.

  • first_seen
  • last_seen
  • days_listed
  • listing_status
  • delisted_on
  • relisted
  • listing_id
  • listing_url
  • duplicate_of

Features and media

The listing content that sells the car.

  • title
  • description
  • features
  • packages
  • color
  • photo_count
  • image_urls
  • video_url

On requestAuction results, parts and accessories prices, recalls and public vehicle records, and service pricing, where they are published.

Who uses it

How teams put automotive data to work.

Dealers and dealer groups

Watch competitor inventory and pricing in your market, price your own stock against what is actually listed, and spot cars that sit unsold on other lots.

Typical refresh: daily

Marketplaces and apps

Fill your own listings or valuation app with vehicles from many sources, matched to one record per car, with the fields your schema expects.

Typical refresh: hourly to daily

Lenders, insurers and fleets

Value vehicles on real asking prices, track depreciation by make, model and mileage, and price loans and policies on current market data.

Typical refresh: weekly

Analysts and researchers

Follow supply, asking prices and days on market across a segment or a whole market, from one consistent history.

Typical refresh: weekly
Why it is hard

Why vehicle data is harder than it looks.

Listings are easy to collect once and hard to keep accurate. These are the five problems we plan for, and how we handle each.

The problem

Search results are capped.

Car marketplaces show only the first few pages of results for each search, so a single query sees only a slice of the market.

How we handle it

We split the search by make, model, region and price band so coverage is complete, and each run reports how many listings it found.

The problem

The same car is listed in many places.

Dealers post one vehicle to several marketplaces and to their own site, each with slightly different titles and details.

How we handle it

We match listings by VIN where it is published, and by make, model, year, mileage and location where it is not, then merge them into one record that keeps every source and price.

The problem

Listings change and disappear.

Prices drop, ads are edited and cars vanish without notice, so a single snapshot misses most of the story.

How we handle it

Scheduled re-checks store every change with a timestamp, so you get price history, days on market and delisting dates.

The problem

Fields are messy.

One listing says "Mercedes-Benz" and another says "Mercedes", and mileage shows up in miles, kilometers or free text.

How we handle it

We normalize makes, models, trims, units and currencies into one consistent format.

The problem

Sites block and change.

Large marketplaces use bot protection and redesign their pages, and scrapers quietly return half the rows.

How we handle it

Every pipeline is monitored with row-count and field checks. When a site changes or blocks us, we fix it. Maintenance is part of the service.

How it works

From your list of sources to a live data feed.

Tell us what you need

Share the marketplaces or dealer sites, the makes and regions, and the fields. A short call or a message is enough.

See a free sample

Within 24 hours of the call, depending on the sources, you get a sample from your own sources. You see the fields, the quality and the refresh rate before you commit.

Pick the schedule

Hourly, daily, weekly or monthly. We scope the price once you have seen the sample.

Receive and rely on it

Data arrives as CSV, JSON, Excel, Google Sheets, Airtable, in your database, through an API or in cloud storage. We monitor it and fix what breaks.

Common questions

Straight answers.

What teams ask before they start.

What automotive data can you collect?

Vehicle listings with make, model, year, trim, mileage, price and options, plus photos, descriptions and public dealer details. On request we also collect auction results, parts and accessories prices, recalls and public vehicle records. Tell us the fields you need and the free sample shows what is possible.

Can you track price changes and cars that disappear?

Yes. We re-check your sources on a schedule from hourly to monthly and store every change. You get price history, days on market and delisting dates, not just a snapshot. A listing that disappears is marked delisted. We cannot tell whether the car sold or was simply taken down.

How do you handle the same car on several marketplaces?

We match listings by VIN where it is published, and by make, model, year, mileage and location where it is not. Matches merge into one record that keeps every source and price. You can receive merged records, raw records or both.

Which marketplaces and countries can you cover?

Large national marketplaces, dealer group websites and small local lots, in any country and language. If a source is not practical, for example because of heavy blocking, we tell you upfront, before you commit to anything.

Is scraping car listing websites legal?

We collect publicly available data only. Rules differ by country and by site, a site's terms may restrict automated access, and listings by private sellers can include personal details such as names and phone numbers, which need extra care under laws like GDPR. We flag risky sources and fields before we build. We are not lawyers, so for sensitive uses we recommend checking with your own counsel.

How do I receive the data?

CSV, JSON, Excel, Google Sheets, Airtable, your own database, an API or cloud storage, on a schedule you choose.

How much does it cost, and how fast can we start?

Pricing depends on sources, volume and frequency. We scope it after a free discovery call and sample. Most samples are ready within 24 hours of the call, depending on the sources.

Your free vehicle data sample, built on your actual sources.

Tell us the marketplaces, makes, regions and fields you need. We reply with a plan and a sample.

Prefer to talk first? Book a call with the founder

Lazar Telebak, founder of REData Analytics

Lazar Telebak

Founder, REData Analytics

You work directly with the person who builds your data feed. In 10+ years he has worked with 500+ startups, agencies and companies, from one-time extractions to long-running systems processing tens of millions of records.

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