# Private Car Seller Leads — Under-Market Cars for Dealers (`studio-amba/private-car-seller-leads`) Actor For a make, model and country, runs that country's car-classifieds scrapers, splits dealer vs private listings, computes the dealer-market median per year bucket, and flags private cars priced under it. An acquisition lead feed for dealer buying teams. Poland live (Otomoto + OLX.pl). - **URL**: https://apify.com/studio-amba/private-car-seller-leads.md - **Developed by:** [Studio Amba](https://apify.com/studio-amba) (community) - **Categories:** Business, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 result scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Private Car Seller Leads — Under-Market Cars for Dealer Acquisition Find **private (non-dealer) car sellers priced under the dealer-market median** — a ready-to-call acquisition lead feed for car dealer buying teams. Give it a make, a model and a country. The actor runs that country's car marketplace, splits every listing into **dealer** vs **private seller**, computes the **dealer-market median asking price for each model-year bucket**, and returns the private listings priced under that median. Those are the cars a dealer can buy from a private owner for less than the trade is asking for the same car, same age. ### Why use it Dealer stock-acquisition desks spend their day hunting private sellers who under-price their car. This actor does that hunt automatically: - **The median is built only from dealers.** The benchmark is the price the trade actually asks for that car at that age — not a blended average across all sellers. - **Only private sellers come back as leads.** Every row is a person a buyer can contact, never another dealer. - **Age-matched, not blended.** A 2018 car is compared to 2018-ish dealers, never to a median dominated by newer stock. A listing with no same-age dealer comparison is left out rather than flagged against an irrelevant number. - **A new-lead delta.** Each run marks which leads are new since the last run, so a scheduled run can feed a CRM without re-surfacing yesterday's cars. It is a lead generator, not a price index. If a query has no under-market private cars, it returns nothing — that is a correct, honest empty result. ### How to find private car seller leads in Europe 1. Pick a **country** (Romania is the production-verified flagship market; Czechia is also supported). 2. Enter a **make** and **model**. High-volume pairs (for Romania, `Dacia Logan` or `Dacia Sandero`) give the densest dealer sample and therefore the most reliable median. 3. Optionally set a **year range**, the **year bucket window** (how many model years around a listing count as "same age"), the **minimum dealer sample**, and the **parts-noise floor**. 4. Run it. The actor fans out to the country's marketplace scraper, dedupes by listing URL, filters to your make/model, and computes per-year dealer medians. 5. Read the dataset: every row is a private listing priced under the dealer median for its age, sorted by the biggest discount first. Set **Only new leads** on a schedule to receive just the fresh ones. ### How to scrape private car seller leads The actor does the scraping for you: it drives the national car marketplace's own search, pulls the listings for your make and model, reads each one's price, model year and dealer/private flag, and returns only the private cars that come in under the dealer median for their age. You never touch a selector or a proxy — you give it a make, a model and a country, and it returns the leads. ### Input | Field | Type | Description | |-------|------|-------------| | `make` | string | Car manufacturer, e.g. `Dacia`, `Volkswagen`, `BMW`. Default `Dacia`. | | `model` | string | Car model, e.g. `Logan`, `Golf`. Default `Logan`. | | `country` | select | `RO` (Autovit) or `CZ` (Sauto). Default `RO`. | | `sources` | array | Advanced: override the child scrapers, ignoring the country default. | | `yearMin` / `yearMax` | integer | Optional model-year bounds. | | `yearWindow` | integer | Model years around a listing counted as "same age" for the median (±N). Default 1. | | `minDealerSample` | integer | Minimum dealers in the age bucket before a median is trusted. Default 4. | | `minPctFloorPercent` | integer | A lead must cost at least this % of the median (drops parts/typos). Default 15. | | `onlyNew` | boolean | Only emit leads not seen in a previous run. Default false. | | `maxItemsPerSource` | integer | Cap on listings pulled before filtering. Default 60. | | `timeoutPerSourceSecs` | integer | Per-source wait before treating a source as failed. Default 240. | | `proxyConfiguration` | object | Residential proxy, scoped to the market country. | ### Output Each row is one qualified private-seller lead. | Field | Example | Description | |-------|---------|-------------| | `make` | `Dacia` | Manufacturer | | `model` | `Logan 1.5 dCi` | Model / variant | | `year` | `2018` | Model year | | `price` | `4550` | The private seller's asking price | | `currency` | `EUR` | Local currency of the market | | `marketMedian` | `6750` | Median dealer asking price for this model-year bucket | | `pctBelowMedian` | `32.6` | How far under the dealer median this listing is priced | | `dealerSampleSize` | `6` | Number of dealer listings the median was computed from | | `medianBasis` | `2018±1y` | The age bucket used for the median | | `sellerType` | `private` | `private` (explicit) or `unknown` (no dealer signal); dealers are never emitted | | `sellerContact` | `null` | Phone where the listing card exposes it (usually hidden behind a detail page) | | `listingTitle` | `Dacia Logan 1.5 dCi Preference` | Full listing title | | `mileageKm` | `168000` | Odometer, where available | | `fuelType` | `Diesel` | Fuel type, where available | | `location` / `city` | `Cluj` | Where the car is | | `country` | `RO` | Market country | | `portal` | `Autovit` | Which marketplace the lead came from | | `url` | `https://www.autovit.ro/...` | Direct link to the listing | | `isNew` | `true` | Not seen in a previous run | | `firstSeenAt` | `2026-07-21T...` | When this lead was first detected | | `detectedAt` | `2026-07-21T...` | This run's timestamp | #### Example output ```json { "make": "Dacia", "model": "Logan 1.5 dCi", "year": 2018, "price": 4550, "currency": "EUR", "marketMedian": 6750, "pctBelowMedian": 32.6, "dealerSampleSize": 6, "medianBasis": "2018±1y", "sellerType": "private", "sellerContact": null, "listingTitle": "Dacia Logan 1.5 dCi Preference", "mileageKm": 168000, "fuelType": "Diesel", "location": "Cluj-Napoca", "city": "Cluj-Napoca", "country": "RO", "portal": "Autovit", "url": "https://www.autovit.ro/autoturisme/anunt/dacia-logan-...", "isNew": true, "firstSeenAt": "2026-07-21T13:54:56.891Z", "detectedAt": "2026-07-21T13:54:56.891Z" } ```` ### How the median works For each private listing, the actor collects every **dealer** listing of the same make/model within `yearWindow` model years (default ±1) of that listing's year. If there are at least `minDealerSample` of them (default 4), it takes their median asking price as the market benchmark. The private listing qualifies as a lead when its price is under that median and above the parts-noise floor. There is deliberately **no all-years fallback**. Comparing a 2008 car to a median dominated by 2022 cars would manufacture a fake "80% below market" signal. A private listing with no same-age dealer comparison is simply not flagged — the actor would rather return fewer, trustworthy leads than a pile of misleading ones. ### Cost estimate Pricing is pay-per-event: a small start fee plus a per-lead charge. You pay for qualified leads returned, not for the raw listings scanned. A typical run of a high-volume make/model returns a handful to a few dozen leads. ### Limitations - **Contact is usually hidden.** Most marketplaces expose a seller's phone only on the detail page behind an interaction, so `sellerContact` is often `null`. The listing `url` is always present for follow-up. - **Lead volume follows inventory.** A rare make/model, or a narrow year range, may have too few same-age dealers to form a median — those listings are skipped, and the run can legitimately return nothing. - **Markets.** Romania (Autovit) is the verified flagship; Czechia (Sauto) is supported. More countries are added as their national-marketplace scrapers are verified for clean make/model filtering and priced dealer/private data. - **It reflects asking prices**, not sold prices. A cheap private ask can mean a motivated seller, a needed repair, or a mistake — the actor surfaces the candidate, the buyer still qualifies the car. ### Related scrapers - **EU Car Arbitrage Scanner** — the same car data, scored for cross-border resale gaps instead of private-vs-dealer. - **Autovit Scraper** / **Sauto Scraper** — the underlying single-market car scrapers. - **France Pige Pro** / **Belgium Property Pige** — the same private-seller lead approach for real estate. # Actor input Schema ## `make` (type: `string`): Car manufacturer, e.g. 'Dacia', 'Volkswagen', 'BMW'. Mapped into the source's own search params. High-volume make/model pairs give the densest dealer sample for the market median. ## `model` (type: `string`): Car model, e.g. 'Logan', 'Golf', 'Sandero'. ## `country` (type: `string`): Country to source listings from. Romania ('RO', Autovit) is the production-verified flagship market. Czechia ('CZ', Sauto) runs the identical lead logic on its national marketplace. ## `sources` (type: `array`): Override which child scrapers to run, ignoring the country default. Leave empty to use the country's default source set. ## `yearMin` (type: `integer`): Minimum model year. Leave empty for no lower bound. ## `yearMax` (type: `integer`): Maximum model year. Leave empty for no upper bound. ## `yearWindow` (type: `integer`): How many model years around a private listing's year to include when computing the dealer median (±N years). Wider = larger dealer sample but looser price comparison. ## `minDealerSample` (type: `integer`): Minimum number of dealer listings required before a market median is trusted. Below this, a private listing cannot be qualified (no defensible median off 1-2 cars). ## `minPctFloorPercent` (type: `integer`): A lead must be priced at least this percent of the dealer median (e.g. 15 = 15%). Drops parts/accessory ads that leak in from general classifieds. Raise it to require more plausibly whole cars. ## `onlyNew` (type: `boolean`): Only emit leads not seen in a previous run (run-over-run delta). Useful for scheduled runs feeding a CRM. ## `maxItemsPerSource` (type: `integer`): Cap on listings pulled from each source scraper before filtering. ## `timeoutPerSourceSecs` (type: `integer`): How long to wait for each source run before treating it as failed. ## `proxyConfiguration` (type: `object`): Passed through to the child scrapers. Residential is recommended — the marketplaces are anti-bot protected and geo-scoped. ## Actor input object example ```json { "make": "Dacia", "model": "Logan", "country": "RO", "yearWindow": 1, "minDealerSample": 4, "minPctFloorPercent": 15, "onlyNew": false, "maxItemsPerSource": 60, "timeoutPerSourceSecs": 240, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "RO" } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "make": "Dacia", "model": "Logan", "country": "RO", "yearWindow": 1, "minDealerSample": 4, "minPctFloorPercent": 15, "maxItemsPerSource": 60, "timeoutPerSourceSecs": 240, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "RO" } }; // Run the Actor and wait for it to finish const run = await client.actor("studio-amba/private-car-seller-leads").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "make": "Dacia", "model": "Logan", "country": "RO", "yearWindow": 1, "minDealerSample": 4, "minPctFloorPercent": 15, "maxItemsPerSource": 60, "timeoutPerSourceSecs": 240, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "RO", }, } # Run the Actor and wait for it to finish run = client.actor("studio-amba/private-car-seller-leads").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "make": "Dacia", "model": "Logan", "country": "RO", "yearWindow": 1, "minDealerSample": 4, "minPctFloorPercent": 15, "maxItemsPerSource": 60, "timeoutPerSourceSecs": 240, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "RO" } }' | apify call studio-amba/private-car-seller-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=studio-amba/private-car-seller-leads", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Private Car Seller Leads — Under-Market Cars for Dealers", "description": "For a make, model and country, runs that country's car-classifieds scrapers, splits dealer vs private listings, computes the dealer-market median per year bucket, and flags private cars priced under it. An acquisition lead feed for dealer buying teams. Poland live (Otomoto + OLX.pl).", "version": "0.1", "x-build-id": "5s4XJawBYy0KtNdwO" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/studio-amba~private-car-seller-leads/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-studio-amba-private-car-seller-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/studio-amba~private-car-seller-leads/runs": { "post": { "operationId": "runs-sync-studio-amba-private-car-seller-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/studio-amba~private-car-seller-leads/run-sync": { "post": { "operationId": "run-sync-studio-amba-private-car-seller-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "make": { "title": "Make", "type": "string", "description": "Car manufacturer, e.g. 'Dacia', 'Volkswagen', 'BMW'. Mapped into the source's own search params. High-volume make/model pairs give the densest dealer sample for the market median.", "default": "Dacia" }, "model": { "title": "Model", "type": "string", "description": "Car model, e.g. 'Logan', 'Golf', 'Sandero'.", "default": "Logan" }, "country": { "title": "Country", "enum": [ "RO", "CZ" ], "type": "string", "description": "Country to source listings from. Romania ('RO', Autovit) is the production-verified flagship market. Czechia ('CZ', Sauto) runs the identical lead logic on its national marketplace.", "default": "RO" }, "sources": { "title": "Sources (advanced override)", "type": "array", "description": "Override which child scrapers to run, ignoring the country default. Leave empty to use the country's default source set.", "items": { "type": "string", "enum": [ "autovit", "sauto" ], "enumTitles": [ "Autovit (RO)", "Sauto (CZ)" ] } }, "yearMin": { "title": "Year from (optional)", "minimum": 1950, "maximum": 2030, "type": "integer", "description": "Minimum model year. Leave empty for no lower bound." }, "yearMax": { "title": "Year to (optional)", "minimum": 1950, "maximum": 2030, "type": "integer", "description": "Maximum model year. Leave empty for no upper bound." }, "yearWindow": { "title": "Year bucket window", "minimum": 0, "maximum": 5, "type": "integer", "description": "How many model years around a private listing's year to include when computing the dealer median (±N years). Wider = larger dealer sample but looser price comparison.", "default": 1 }, "minDealerSample": { "title": "Minimum dealer sample", "minimum": 2, "maximum": 50, "type": "integer", "description": "Minimum number of dealer listings required before a market median is trusted. Below this, a private listing cannot be qualified (no defensible median off 1-2 cars).", "default": 4 }, "minPctFloorPercent": { "title": "Parts-noise floor (% of median)", "minimum": 0, "maximum": 90, "type": "integer", "description": "A lead must be priced at least this percent of the dealer median (e.g. 15 = 15%). Drops parts/accessory ads that leak in from general classifieds. Raise it to require more plausibly whole cars.", "default": 15 }, "onlyNew": { "title": "Only new leads", "type": "boolean", "description": "Only emit leads not seen in a previous run (run-over-run delta). Useful for scheduled runs feeding a CRM.", "default": false }, "maxItemsPerSource": { "title": "Max items per source", "type": "integer", "description": "Cap on listings pulled from each source scraper before filtering.", "default": 60 }, "timeoutPerSourceSecs": { "title": "Per-source timeout (seconds)", "type": "integer", "description": "How long to wait for each source run before treating it as failed.", "default": 240 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Passed through to the child scrapers. Residential is recommended — the marketplaces are anti-bot protected and geo-scoped.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "RO" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```