Thinking About Scraping Otomoto or OLX? Read This First
Neither Otomoto nor OLX offers a public, self-serve API for reading market data, which is why so many teams consider building a scraper. A realistic budget for a well-maintained scraping pipeline is roughly 15–40 engineering hours per month plus $100–$500 in monthly proxy costs (our estimates, detailed below), before you touch deduplication, normalization, or legal review. If what you actually need is pricing statistics rather than raw listings, CarDossier's Market API serves valuations, price history, and regional breakdowns computed from our own database of 1.4M+ Polish market listings, updated daily. You can test it right now with 5 free keyless calls per IP per day — no registration required.
Data: CarDossier database, 1.4M+ Polish market listings, updated daily · Last updated: July 2026
Why scraping comes up at all
Let's be honest about the motivation: Polish automotive marketplace data is genuinely valuable, and there is no easy official way to get it in bulk. OLX operates an official developer portal (developer.olx.pl), but its API is oriented toward registering an application and managing your own adverts — it is not a bulk read API for other sellers' listings. Otomoto has professional tooling for dealers who publish inventory, but as of July 2026 there is no publicly documented, self-serve endpoint for reading market data at scale. When a marketplace has no official data product, people who need that data — dealers pricing trade-ins, fintechs underwriting car loans, analysts tracking the market — naturally start looking at the HTML.
That instinct is understandable. It is also worth understanding what you are actually signing up for before you write the first line of scraper code.
The real cost of a DIY scraper: five problems that never go away
1. Anti-bot countermeasures. Large marketplaces invest continuously in bot detection: rate limiting, TLS and browser fingerprinting, JavaScript challenges, and behavioral analysis. This is a moving target by design. A pipeline that works today can silently degrade next month — not fail loudly, but return fewer results, skewing every statistic you compute downstream. Detecting partial collection failure is one of the hardest problems in scraping operations, because the pipeline still reports success.
2. HTML structure drift. Marketplace front-ends ship changes constantly: renamed CSS classes, restructured JSON payloads, new listing card layouts, A/B tests that serve different markup to different sessions. Every change is a potential silent breakage of your selectors. In practice this is the single largest recurring maintenance cost — and it arrives on the platform's schedule, not yours.
3. Proxy infrastructure. Sustained collection at market scale requires rotating IP addresses, typically residential or mobile proxies billed per gigabyte. Costs scale with volume and page weight, and proxy quality itself varies over time, adding another failure mode to monitor.
4. Deduplication and normalization. This is the cost almost everyone underestimates. The same physical car is frequently listed on multiple platforms — and sometimes multiple times on one platform — so naive counting inflates supply and distorts averages. Model names arrive in every imaginable variant ("Seria 3", "320d", "3er", "3 Series"), trim and generation labels are free text, mileage may be entered in kilometers or occasionally miles, and prices may be gross, net, or "do negocjacji". Turning raw listings into statistics you can trust is a data engineering project of its own, separate from the scraping.
5. Legal uncertainty. We are not offering legal advice, and we are not accusing anyone of anything — but the factual landscape is genuinely unsettled and you should review it with counsel. In the EU, the Database Directive (96/9/EC) grants a sui generis right to database makers, and extracting or re-utilizing substantial parts of a protected database can infringe it. The CJEU has also held (Ryanair v PR Aviation, C-30/14) that where a database is not protected by that right, website terms may still contractually restrict its use. On the personal-data side, the CJEU ruled in 2023 (C-319/22) that a vehicle identification number constitutes personal data for anyone who can reasonably link it to an identifiable person — and listings routinely contain seller names and phone numbers, which are unambiguously personal data under GDPR, with all the storage and processing obligations that follow. None of this makes scraping automatically unlawful; all of it makes "we'll just scrape it" a decision that deserves a legal budget line, not a shrug.
Putting numbers on it (estimates, clearly labeled)
Based on our own experience operating large-scale collection and normalization pipelines, here is what a reasonably robust two-platform scraping operation tends to cost. These are estimates — your numbers will vary with scale and ambition:
- Initial build: 2–6 engineer-weeks for crawlers, parsers, a scheduler, storage, monitoring, and a first pass at dedup/normalization.
- Ongoing maintenance: 15–40 engineering hours per month responding to markup changes, anti-bot escalations, and data-quality regressions. In bad months, more.
- Proxies and infrastructure: roughly $100–$500 per month at moderate scale (residential proxy traffic, headless browser capacity, storage); materially more if you need full-market daily refresh.
- Data quality engineering: ongoing, hard-to-bound effort on cross-platform dedup and name normalization — the part that determines whether your statistics are actually usable.
- Legal review: a one-time assessment plus periodic re-review as case law evolves.
At typical European contractor rates, the recurring line alone often lands in the $2,000–$6,000/month range before anyone has analyzed a single data point.
DIY scraper vs. a maintained aggregated API
| Dimension | DIY scraper pipeline | CarDossier Market API |
|---|---|---|
| Upfront cost | 2–6 engineer-weeks before first usable statistic (estimate) | None — 5 free keyless demo calls per IP per day, real data |
| Ongoing maintenance | 15–40 engineer-hours/month plus proxy spend (estimate) | $0 — maintenance is our problem; plans from $49 for 5,000 credits |
| Data cleaning | You build dedup, model-name normalization, and unit handling yourself | Already done: model-family normalization, fuel-type aliases, statistical aggregation |
| Legal exposure | Database rights, GDPR (seller data, VINs), and ToS questions sit with you | You consume statistical aggregates from CarDossier's own database — no raw listing copies |
| Failure mode | Silent partial breakage that skews your statistics | Failed API calls are automatically refunded |
| Time to launch | Weeks to months | Minutes — one curl command, no account needed |
| Raw per-listing fields | Yes — this is the one thing DIY genuinely wins on | No — aggregated statistics only |
What the Market API actually delivers
CarDossier's Market API is built on our own database of 1.4M+ Polish market listings, aggregated from publicly available sources and updated daily. The important design choice: we deliver statistical aggregates, not reproductions of raw listings. Five endpoints, all under https://car-dossier.com/api/v1:
- /market/valuation (8 credits) — price distribution for a make/model/year: average, median, P25/P75, sample size.
- /market/price-history (10 credits) — monthly price trends, up to 24 months back.
- /market/liquidity (6 credits) — days-on-market: how fast comparable cars actually sell.
- /market/valuation-factors (12 credits) — how import status, transmission, and fuel type shift prices.
- /market/regional (8 credits) — price breakdowns across all 16 Polish voivodeships.
One credit is $0.01, so a full valuation costs $0.08. The normalization work described above is baked in: send 'VW Golf', 'BMW 3 Series' or just '320d', 'C-Class', 'A4', 'XC60' — the smart-matching layer resolves natural names and returns a matched block showing exactly what it resolved to. Fuel types accept plain English: petrol, diesel, hybrid, electric, lpg. The API is also machine-readable end to end: an OpenAPI spec at car-dossier.com/openapi.yaml, an llms.txt for AI agents, and an MCP server (pip install cardossier-mcp-server, or the remote endpoint at https://car-dossier.com/mcp) that works keyless.
Try it in 10 seconds — no key, no signup
curl "https://car-dossier.com/api/v1/market/valuation?make=BMW&model=3%20Series&year=2019"Every IP gets 5 free demo calls per day against real data, no registration required. An abridged example of the response shape:
{
"status": "success",
"data": {
"make": "BMW", "model": "3 Series", "year": 2019,
"matched": { "makes": ["BMW"], "models": ["Seria 3"], "match_type": "family" },
"currency": "PLN",
"valuation": { "average": 87404, "median": 87000, "p25": 66900, "p75": 105000 },
"sample_size": 866,
"credits_used": 8
}
}When you outgrow the demo limit, registering with just an email (OTP verification, no credit card) grants 50 free credits — enough for six valuations. Paid plans run from $49 for 5,000 credits to $699 for 100,000, and any failed call is automatically refunded. Full details on the pricing page and in the API documentation.
When building your own scraper still makes sense
An aggregated statistics API is not the right tool for every job, and pretending otherwise would be a poor way to earn your trust. Build (or buy) your own listing-level pipeline if you need raw per-listing fields — individual photos, full descriptions, or exact single-listing prices; if you need real-time monitoring of individual adverts, such as alerting the moment a specific car is listed or drops in price; or if your product is itself a listings search experience. CarDossier delivers market-level statistics — distributions, trends, factors, regions — not a feed of individual adverts, and no aggregate can substitute for the raw records if raw records are the product. If you do go the DIY route, budget the maintenance hours honestly, monitor for silent partial failures, and get a proper legal review of database rights and GDPR obligations before launch.
Skip the scraper. Query the statistics. Valuations, price history, liquidity, and regional data for the Polish market — from 1.4M+ listings, updated daily, first calls free.
Learn about the Market API Read the docs →