🛒 Facebook Marketplace Scraper

🚀 Pull public Facebook Marketplace listings by city and search term. Export titles, prices, categories, brands, vehicle specs, real-estate details, seller names and direct listing URLs into clean JSON, CSV or Excel.

The Facebook Marketplace Scraper queries Marketplace by city and keyword, paginates through the search feed, and returns each listing as a flat JSON record with 29 fields. The dataset covers titles, current price, currency, primary photo, seller name and id, category and subcategory, brand, condition, listing URL, delivery options, and typed blocks for vehicles (make, model, year, mileage, condition, transmission, fuel type) and real estate (bedrooms, bathrooms, square footage, property type).

The Actor classifies each listing into one of four types (general product, vehicle, rental or home-for-sale) based on the hydrated search feed plus title heuristics, so you can filter the output without post-processing. Vehicle fallback parses year, make and model from the title so older listings that don't expose structured vehicle fields still get typed.

🎯 Target Audience	💡 Primary Use Cases
Used-goods resellers, real-estate analysts, auto dealers, market researchers, price intelligence teams, data scientists	Price monitoring, inventory discovery, used-car pricing, rental market mapping, arbitrage detection, competitor listing analysis

📋 What the Facebook Marketplace Scraper does

Five common workflows in a single run:

• 🛒 City + keyword search. Pass a city slug and a query, get the current Marketplace feed.
• 🚗 Vehicle typed fields. Year, make, model, mileage, condition, transmission and fuel when Facebook exposes them, with title-based fallbacks for the rest.
• 🏡 Real-estate typed fields. Bedrooms, bathrooms, square footage and property type for rentals and homes for sale.
• 🏷️ Brand, category and delivery. Structured category, subcategory, brand and delivery-option tags per listing.
• 🔗 Direct listing URLs. Every record includes the canonical marketplace URL for follow-up.

💡 Why it matters: Marketplace has no official export and no public search API. Scraper alternatives usually return 5-10 fields and break when Facebook changes class names. This Actor reads the hydration JSON behind the search page, so the schema is stable and the output is already typed.

📊 Data fields

Each record includes: bathrooms, bedrooms, currency, deliveryOptions, images, isAvailable, isPending, isSold, listingId, listingType, location, price, scrapedAt, strikethroughPrice, title, url, vehicleMake, vehicleMileage, vehicleModel, vehicleYear. All 20 field names come from a real production run, so what you see here is what lands in your dataset.

🚀 How to use

1. Pick a Marketplace city slug (e.g. nyc, losangeles, miami, chicago).
2. Add a search query per city in searchQueries.
3. Set maxItems, run the Actor, and download JSON, CSV or Excel.
4. Sort by listingType to split vehicles, rentals and general products.

🔗 Recommended Actors

Actor	What it does
Facebook Comments Scraper	Pulls threaded comments, replies, reactions and mentions from any public Facebook post.
Facebook Groups Scraper	Pulls member count, privacy, rules and admin info from public Facebook groups.
Zillow Rentals Scraper	Rental listings with price, beds, baths and history from Zillow.
CarsForSale Scraper	Inventory and pricing from CarsForSale.com.
EquipmentTrader Scraper	Heavy equipment listings with full specs and seller details.

💡 Tips

• Run a small maxItems test first to confirm the city slug matches your target. Some cities use alternate spellings (e.g. sanfrancisco, not san-francisco).
• Use listingType as a downstream filter to split vehicles, rentals and general products before loading into your analytics tool.
• Schedule runs during off-peak hours. Marketplace refreshes its feed continuously, so evenings give the best new-inventory yield.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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