RV Trader Scraper: 35 Data Fields, Up to 1,000 Free Results/Month

Each record carries 35 output fields, including core values like listingId, listingUrl, year, price, condition, and rvType, along with conditional enrichment like dealer details, photo lists, and VIN numbers. A thousand results cost $5.00 on the free-plan tier at $0.005 per result, with up to 1,000 results covered monthly by Apify's free plan. Built for pricing analysts, inventory tracking teams, and software developers building marketplace tools, but not for teams requiring private-seller contact details on every listing.

Try it: open RV Trader Scraper on Apify, sign in on the free plan and run the prefilled example.

Can you try RV Trader Scraper before paying?

Yes. Apify's free plan includes $5.00 of prepaid usage every month and asks for no credit card. At $0.005 per result, that covers up to 1,000 results of RV Trader Scraper a month, before run-start charges and platform usage.

RV Trader Scraper was last updated on 2026-09-01. It is one of 1,724 Actors CrawlerBros publishes on Apify, which together have 740,757 lifetime public runs and an average rating of 4.63 out of 5 across 416 reviews.

What does it cost to run RV Trader Scraper?

Each result costs $0.005 on Apify's free plan, which is $5.00 per 1,000 results. Starting a run is charged separately at $0.005 per GB of Actor memory. Apify also bills the platform usage each run consumes, at the rates of your Apify plan, on top of these charges.

Total run charges depend directly on how many dataset items are generated, so maxItems is the main factor governing your bill. Narrowing queries using make, model, or zipCode reduces total item output and keeps costs predictable. Run small tests with maxItems set to 30 before running nationwide extractions.

How do you run RV Trader Scraper from the API?

None of its 20 controls is strictly required, so the defaults below produce a valid run on their own. Nothing in the payload below is illustrative. Those are the schema's prefilled defaults for RV Trader Scraper, so the request works once your token is in place.

Call the synchronous endpoint to start a run and receive dataset items in one request:

curl -X POST "https://api.apify.com/v2/acts/crawlerbros~rvtrader-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keyword":"Winnebago"}'

The same run from Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run_input = {
  "keyword": "Winnebago"
}

run = client.actor("crawlerbros~rvtrader-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

And from Node.js:

import { ApifyClient } from 'apify-client'

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' })

const input = {
  "keyword": "Winnebago"
}

const run = await client.actor('crawlerbros~rvtrader-scraper').call(input)
const { items } = await client.dataset(run.defaultDatasetId).listItems()
console.log(items)

Because the call is synchronous, your client waits for the whole run. Keep it for exploration. For scheduled work, start the run without waiting and collect the dataset afterwards, so network trouble costs you a retry rather than the results.

Which RV Trader Scraper inputs matter, and which can you skip?

The schema contains 20 optional controls and zero required parameters, meaning an empty input object runs a broad search across all active listings. Use make, model, or rvType to filter results, and adjust maxItems to enforce strict boundaries on how many records are written to the dataset. Leave advanced filters like fuelType or sleepingCapacity unconfigured unless explicitly targeting those specs.

• keyword (string): Free-text keyword to search listing titles. Matches make, model or trim - example: "Winnebago", "Jayco Eagle", "Airstream Flying Cloud".
• rvType (string): RV category to filter by. Leave empty to search all RV types. Default: "".
• make (string): Filter to a specific RV manufacturer, e.g. "Forest River", "Keystone", "Jayco", "Grand Design", "Coachmen", "Thor Motor Coach", "Winnebago", "Heartland", "Airstream". Matches RVTrader's structured make field (partial match, case-insensitive) rather than free-text title search, so it's more precise than 'Keyword' for this purpose. Leave empty to search all makes.
• model (string): Filter to a specific RV model, e.g. "Eagle", "Montana", "Wildwood", "Flying Cloud". Matches RVTrader's structured model field (partial match, case-insensitive) rather than free-text title search, so it's more precise than 'Keyword' for this purpose. Works well combined with 'Make'. Leave empty to search all models.
• condition (string): New or used listings. Default: "".
• state (string): US state or Canadian province the RV is listed in. Leave empty to search nationwide. Default: "".
• minPrice (integer): Minimum listing price in USD.
• maxPrice (integer): Maximum listing price in USD.
• minYear (integer): Minimum model year.
• maxYear (integer): Maximum model year.
• minLengthFt (integer): Minimum RV length in feet.
• maxLengthFt (integer): Maximum RV length in feet.

The other 8 controls, with their defaults, are listed in the input schema on RV Trader Scraper on Apify.

Fixed-choice controls: rvType accepts 13 values (default ""), including "" (All RV types), Class A (Class A motorhome), Class B (Class B motorhome (camper van)), Class C (Class C motorhome); condition accepts "" (Any condition), New, Used; state accepts 62 values (default ""), including "" (All states/provinces), AL (Alabama), AK (Alaska), AZ (Arizona).

What does RV Trader Scraper return?

Returned dataset records work well for market price benchmarking, competitive dealership inventory audits, and aggregating structured RV specifications. They do not contain full multi-page description details or secondary contact forms from individual listing pages, as extractions rely solely on search-result data feeds.

• recordType - always "listing"
• listingId - RVTrader's internal listing ID
• title - e.g. "2024 Jayco Eagle 355MBQS"
• year, price, priceCurrency, condition
• rvType - the RV category the listing was found under (Class A, Travel Trailer, etc.) - always known, since every search request is scoped to a specific type
• listingUrl - the live rvtrader.com listing page
• scrapedAt - ISO-8601 timestamp of when the record was collected
• make, model, trim
• mileage - odometer reading in miles
• lengthFt - RV length in feet
• sellerType - "Dealer" or "Private"
• dealerName, dealerPhone, dealerWebsite, dealerId - for dealer-listed RVs
• dealerGroupName, dealerGroupId - the dealer chain/group name and ID (e.g. "Camping World"), when the selling dealer belongs to a multi-location dealer group
• stockNumber, vin - when the seller listed them
• msrp - manufacturer's suggested retail price in USD, when the dealer published one
• rebate - manufacturer/dealer rebate amount in USD, when one is being offered on the listing
• locationCity, locationState, latitude, longitude
• images - array of listing photo URLs; primaryImageUrl - the first photo; photoCount - total photos on the listing
• description - the listing's summary text
• listedDate - when the listing was first published
• dealerListingUrl - the dealer's own website listing for this exact RV, when the dealer maintains one separately from RVTrader
• isFeaturedListing - true when the seller paid for premium/top placement on RVTrader (omitted for standard listings)

These are the documented fields. Optional ones can be empty on a given record, so measure how often each field your deliverable depends on is populated across a real sample before automating the handoff.

How do you build the workflow end to end?

Open RV Trader Scraper and work through these in order. Each step ends with something to check, so a bad configuration surfaces on a small run rather than a scheduled one.

1. Run an initial test with maxItems set to 30 and rvType set to Travel Trailer to verify dataset outputs without spending platform usage on large runs.
2. Inspect the returned JSON object in the dataset tab to confirm presence of core fields including listingId, listingUrl, price, and year.
3. Verify whether rich enrichment fields like dealerName, vin, and mileage are present on the returned items for your selected inventory category.
4. If dealerName is omitted and required for your workflow, adjust sellerType to Dealer to narrow the search results to dealer-hosted listings.
5. Set location parameters using zipCode and radiusMiles to restrict geographic coverage, or leave them empty to run nationwide extraction.
6. Configure maxItems to your target result count and set sortBy to create_date:desc to collect the newest marketplace additions first.
7. Schedule recurring runs using Apify schedules to continuously append dataset output over time.

How do you apply it? Three worked playbooks

These are RV Trader Scraper's own documented use cases, each worked through as an operating pattern rather than a description.

Use case 1: RV dealers

Outcome: Monitor competitor inventory and pricing across RV types and regions

Configure: Set rvType to "Class A", condition to "Used", state to "TX", sortBy to "price:asc", and maxItems to 30.

Working method: Execute a baseline extraction across target states, then run weekly scheduled runs filtered by create_date:desc to compare new market arrivals against historic dealer pricing trends.

Deliverable: A structured dataset of competitor listings containing listingId, title, price, year, dealerName, and locationCity.

Stop condition: Stop execution if 10 consecutive records return null for dealerName while sellerType is expected to be dealer-dominated.

Use case 2: Lead generation

Outcome: Find sellers of specific RV types for B2B outreach

Configure: Set sellerType to "Dealer", make to "Winnebago", minYear to 2020, sortBy to "create_date:desc", and maxItems to 30.

Working method: Extract targeted dealer listings daily to parse commercial seller information from newly posted high-value inventory.

Deliverable: A list of B2B seller leads including dealerName, dealerPhone, dealerWebsite, dealerId, and locationState.

Stop condition: Stop execution if dealerPhone and dealerWebsite are missing across more than 50% of extracted records.

Use case 3: Price comparison tools

Outcome: Enrich listings with cross-referenced market pricing

Configure: Set make to "Keystone", model to "Montana", minYear to 2018, maxYear to 2024, maxItems conscientiously within limits, and proxyConfiguration to {"useApifyProxy": true}.

Working method: Extract active listings across a multi-year model span, then calculate mean listing values grouped by year and lengthFt to establish regional market averages.

Deliverable: A cross-referenced pricing dataset containing price, msrp, rebate, year, lengthFt, and mileage.

Stop condition: Stop execution if fewer than 20 results are returned for a high-volume make and model pair.

What breaks, and how do you design around it?

When search templates omit rich per-listing attributes like VIN, mileage, or dealer phone numbers, rely on the core fields like listingUrl and listingId instead. If sellerType filters cause longer execution times due to server-side scanning, drop the filter and perform client-side filtering on the returned dataset records. If requests encounter network blocks, ensure proxyConfiguration retains Apify's rotating proxies.

When should you not use RV Trader Scraper?

Do not use this Actor if you require full long-form property text, direct owner email forms, or deep listing history pages that are omitted from search result data feeds. If your target inventory focuses on marine craft rather than land vehicles, use Boat Trader Scraper instead. If you are tracking commercial hauling units or heavy towables, consider using Trailer Trader Scraper or RVUSA Scraper. For agricultural machinery, use MachineryPete Equipment Price Scraper.

What should you check before trusting the output?

• Check that listingUrl and listingId are populated and non-null on 100% of captured records.
• Verify that price is numeric and greater than zero, flagging records where sellers set price to null or 0.
• Monitor sellerType for empty strings if downstream B2B outreach scripts require explicitly identifying Dealer versus Private entities.
• Halt execution or alert if photoCount is zero across an entire batch, indicating a layout change on the source search result pages.
• Confirm that scrapedAt reflects an ISO-8601 timestamp within the expected run window to prevent processing stale cached records.

None of this proves a record is correct. It gives a scheduled RV Trader Scraper run defined points where it should stop instead of quietly passing bad data downstream.

Frequently asked questions

How much does it cost to extract 1,000 RVTrader listings?

Extracting 1,000 results costs $5.00 on Apify's free plan, based on the rate of $0.005 per result written to the dataset. Apify's free plan includes $5.00 of monthly credit, covering up to 1,000 results each month before platform usage fees.

Does this Actor require an RVTrader account or paid proxy?

No account or login is required. The Actor normally uses the free Apify AUTO proxy group, though it can automatically switch to a residential proxy during a run if AUTO is blocked repeatedly, meaning separate residential proxies do not need to be configured manually from the start.

Are contact details for private sellers included in the dataset?

No. While dealer listings frequently include structured attributes like dealerName, dealerPhone, and dealerWebsite, private seller listings typically restrict direct contact details to website forms that do not exist in search feeds.

Why are some optional fields like vin or mileage missing?

Optional fields are omitted from a JSON record when RVTrader does not provide rich per-listing data for that specific item in the search results template. Core fields like price, year, and listingUrl always appear.

How can I filter search results by location?

Set the zipCode parameter to a 5-digit US ZIP code and choose a radiusMiles value such as 100 or 250. Alternatively, select a specific two-letter US state or Canadian province from the state control.

Where to go next

When you are ready to run it, open RV Trader Scraper on Apify; the free plan covers up to 1,000 results a month.

Start with the RV Trader Scraper Actor page for the current input schema, pricing tier, and run history.

Other Actors we maintain for related data:

• RVUSA Scraper: Scrape RVUSA.com RV, motorhome, travel trailer and fifth wheel classifieds.
• Boat Trader Scraper: Scrape boattrader.com boat-for-sale listings - browse by type, class, make, condition, fuel, hull shape, US state, and price/year/length range, or fetch full listing detail by ID/URL.
• Trailer Trader Scraper: Scrape Trailer Trader - a free U.S.
• ParuVendu Used Cars Scraper: Scrape used-car listings from ParuVendu.fr, a major French car classifieds marketplace.
• MachineryPete Equipment Price Scraper: Scrape used ag and construction equipment listings from MachineryPete.com - tractors, combines, planters, tillage, hay & forage, construction equipment, trucks & trailers, and more.

Related guides:

• Boat Trader Scraper: 3 Practical Use Cases
• AutoTempest Car Listings Scraper: 21 Data Fields per Record (2026)
• Mobile.de Car Scraper: Up to 2,500 Free Results a Month (2026)
• DBA.dk Scraper: Up to 1,000 Free Results a Month (2026)
• Bring a Trailer Car Auctions Scraper: 21 Data Fields per Record (2026)
• Otomoto Car Listings Scraper: 200,000+ Listings Covered (2026)
• Row52 Junkyard & Salvage Yard Parts Scraper: $5.00 per 1,000 Results

Resources

• Actor documentation, input schema, and pricing: verified against the published Actor on 2026-10-05.

• Actor last updated by its maintainers on 2026-09-01.

• Run outcome figures cover the 30 day public window ending 2026-10-05.

• RV Trader Scraper on Apify