The used-car market is huge, fragmented, and priced inconsistently - the same model varies widely across marketplaces and regions. Seeing that variation means used car price scraping across CarGurus, Cars.com, and AutoTrader.
This report uses web scraping of public listings to measure how prices vary by make, mileage, and region, and how listings age. It is context for any dealer, marketplace, or analyst relying on automotive data scraping or a pricing feed.
Key findings at a glance
Three patterns stand out across the listing data. (Figures are illustrative previews - the full report breaks them down by make, mileage and region.)
Key finding 1: mileage drives price after model
Once model is fixed, mileage is the biggest price lever, with value dropping in clear bands. Trim, condition, and region matter, but mileage sets the baseline.
Capturing this means used car price scraping with structured fields - make, model, trim, year, mileage, region - so prices compare like for like rather than across mismatched vehicles.
Key finding 2: the same car varies by marketplace and region
The identical vehicle can list at different prices across sites and regions. The sample shows spread (illustrative).
| Marketplace | Avg list (same model/mileage) | Note |
|---|---|---|
| CarGurus | $18,400 | Deal-rating pressure |
| Cars.com | $18,950 | Dealer-heavy |
| AutoTrader | $19,200 | Broad mix |
Only cross-marketplace used car price scraping reveals these gaps, which is exactly where buyers and dealers find edge.
Key finding 3: listing age is a pricing signal
How long a car sits is a strong signal - fast-moving listings are keenly priced, stale ones are over-market. Used car price scraping that tracks listings over time, with a timestamp and first-seen date, surfaces days-on-market and price drops, which dealers use to reprice and buyers use to negotiate.
What the underlying data looks like
The report is built from listing records like the one below - the structure buyers receive in a sample.
{
"marketplace": "CarGurus",
"listing_id": "CG-88231",
"make": "Example",
"model": "Sedan",
"trim": "SE",
"year": 2021,
"mileage": 42000,
"price": 18400,
"region": "Midwest",
"zip": "60614",
"first_seen": "2026-06-10",
"days_on_market": 19,
"captured_at": "2026-06-29T09:00:00Z"
}
Aggregated to a make-and-region view, the data rolls up into a flat file analysts can model on:
make,model,mileage_band,region,avg_price,avg_days_on_market
Example,Sedan,30-60k,Midwest,18400,28
Example,SUV,60-90k,West,22600,41
Example,Truck,<30k,South,34900,17
Who this report is for
This report is built for the automotive teams that price and analyze inventory via used car price scraping.
- Price variation by make, mileage & region
- Cross-marketplace price gaps
- Days-on-market & price-drop patterns
- Vehicle matching methodology
- Complete methodology, sample size and sources
Methodology & data
The findings are based on used car price scraping of public listings across CarGurus, Cars.com and AutoTrader in 2026, captured by make, model, trim, year, mileage and region, and tracked over time for days-on-market. No personal data is involved. The full report details the marketplaces, method and how each metric is calculated.
The numbers and charts shown on this page are illustrative previews of the kind of analysis in the report. They are based on publicly available, non-personal web data in aggregate and do not represent any single named company. The full report contains the complete dataset, methodology and sources.
Frequently asked questions
Yes. Enter your details and we will email you the PDF.
Through used car price scraping of public listings, captured by make, mileage and region and tracked over time.
They are illustrative previews of the report's analysis. The full PDF contains the complete dataset, methodology and sources.
Yes - tracking listings over time surfaces days-on-market and price changes.
Yes. We deliver structured listing data for your makes, marketplaces and regions via API or file.