Facebook Marketplace Listing Details Extractor (Rich Metadata)

Overview

This actor performs a deep extraction of Facebook Marketplace listing metadata, capturing comprehensive product details, seller information, geolocation data, and engagement metrics. Designed for high-fidelity data collection, the extractor operates without authentication requirements and ensures data integrity through structured JSON output with ISO 8601 timestamp validation and normalized field schemas.

Data Dictionary

Field Name	Data Type	Definition
listing_id	String	Unique identifier assigned by Facebook Marketplace to the listing
external_id	String	Composite identifier combining platform prefix, listing ID, and extraction year for cross-system tracking
scraped_at	String (ISO 8601)	UTC timestamp indicating when the data extraction occurred
title	String	User-generated listing title describing the product or service
price	Float	Numerical price value in the specified currency
currency	String	Three-letter ISO 4217 currency code
condition	String	Item condition descriptor (e.g., "New", "Used - Like New", "For Parts")
category	String	Primary marketplace category classification
subcategory	String	Secondary classification within the parent category
is_available	Boolean	Availability status indicating if the listing is currently active for purchase
is_verified_seller	Boolean	Verification flag indicating if the seller has completed Facebook's identity verification process
language_code	String	ISO 639-1 language code with regional variant (e.g., "en_US")
location.city	String	City name where the item is located
location.state	String	State or province abbreviation
location.zip	String	Postal code for the listing location
location.coordinates.latitude	Float	Geographic latitude coordinate in decimal degrees
location.coordinates.longitude	Float	Geographic longitude coordinate in decimal degrees
seller.id	String	Unique Facebook user identifier for the seller account
seller.name	String	Display name of the seller as shown on their Facebook profile
seller.rating	Float	Aggregate seller rating on a 0-5 scale based on buyer feedback
seller.member_since	String (ISO 8601)	Date when the seller account was created
seller.total_listings	Integer	Count of active and historical listings posted by the seller
engagement_metrics.views	Integer	Total number of times the listing has been viewed
engagement_metrics.saves	Integer	Count of users who have saved the listing to their watchlist
engagement_metrics.shares	Integer	Number of times the listing has been shared via Facebook or external channels
engagement_metrics.messages	Integer	Count of direct messages initiated by potential buyers
listing_status	String	Current lifecycle state of the listing (e.g., "active", "pending", "sold", "expired")
post_timestamp	String (ISO 8601)	UTC timestamp when the listing was originally published

Sample Dataset

Below is a sample of the high-fidelity JSON output:

{
  "listing_id": "251908473615492",
  "external_id": "fb_mkt_251908473615492_2025",
  "scraped_at": "2025-12-20T14:22:31Z",
  "title": "2020 Honda Civic EX - Excellent Condition",
  "price": 15999.00,
  "currency": "USD",
  "condition": "Used - Like New",
  "category": "Vehicles",
  "subcategory": "Cars",
  "is_available": true,
  "is_verified_seller": true,
  "language_code": "en_US",
  "location": {
    "city": "Sacramento",
    "state": "CA",
    "zip": "95814",
    "coordinates": {
      "latitude": 38.5816,
      "longitude": -121.4944
    }
  },
  "seller": {
    "id": "1234567890",
    "name": "John Smith",
    "rating": 4.8,
    "member_since": "2023-03-15",
    "total_listings": 12
  },
  "engagement_metrics": {
    "views": 342,
    "saves": 28,
    "shares": 5,
    "messages": 15
  },
  "listing_status": "active",
  "post_timestamp": "2025-12-19T08:15:22Z"
}

Configuration Parameters

To ensure optimal data depth, configure the following:

Parameter	Field Name	Data Type	Required	Description
Listing ID	listingId	String	Yes	The unique Facebook Marketplace listing identifier to extract. Format: numeric string (e.g., "251908473615492")

Analytical Use Cases

Competitive Price Intelligence: Analysts can aggregate pricing data across categories and geographic regions to identify market trends, pricing outliers, and optimal price points for dropshipping inventory.

Seller Reputation Scoring: Data scientists can construct multi-dimensional seller trust models using seller.rating, seller.total_listings, and seller.member_since to assess supplier reliability before establishing business relationships.

Geographic Inventory Mapping: Researchers can perform spatial analysis using location.coordinates to identify high-density product clusters, optimize logistics routes, and target underserved markets.

Engagement Pattern Analysis: Longitudinal studies of engagement_metrics enable predictive modeling of listing performance, optimal posting times, and content optimization strategies.

Temporal Market Dynamics: Time-series analysis comparing post_timestamp and scraped_at reveals listing lifecycle patterns, seasonal demand fluctuations, and inventory turnover rates.

Technical Limitations

Important Considerations:

• Rate Limiting: Extraction throughput is subject to Facebook's undocumented rate limits. Recommended batch size: 50-100 listings per execution with 2-3 second delays between requests.
• Data Freshness: Engagement metrics (views, saves, shares, messages) represent point-in-time snapshots and may lag real-time values by 5-15 minutes.
• Geographic Precision: Coordinate data is approximate and may be centroid-based for privacy protection, with accuracy typically within 1-5 km radius.
• Seller Data Availability: Fields within the seller object depend on user privacy settings; seller.name may return "Facebook User" for accounts with restricted visibility.
• Listing Persistence: Expired or deleted listings return null responses. Historical data is not retrievable once a listing status changes to "removed."
• Currency Normalization: Price values are extracted as-posted; cross-currency conversion requires external exchange rate services.
• Authentication: This cookieless implementation does not access private messages, saved searches, or user-specific recommendations.

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Keywords & Tags: facebook marketplace scraper, marketplace listing data extraction, scrape facebook marketplace listings, export marketplace listings, marketplace data mining, lead generation from marketplace, seller contact data extraction