Craigslist For Sale Scraper

Scrape Craigslist for-sale listings with AI-powered deal scoring, trust analysis, and opportunity metrics. Get intelligent insights on every listing to find the best deals.

What it does

This actor scrapes Craigslist "for sale" listings across any US city and enriches each result with 16 intelligence metrics including deal scoring, trust analysis, freshness indicators, and market demand signals.

Input Parameters

Parameter	Type	Default	Description
location	string	(required)	Craigslist subdomain (e.g. sfbay, newyork, chicago)
category	string	sss	Category code (sss=all, ele=electronics, fua=furniture, etc.)
searchQuery	string		Keywords to search for
maxResults	integer	50	Max results (1-500)
minPrice	integer		Minimum price filter
maxPrice	integer		Maximum price filter
postedToday	boolean	false	Only today's listings
hasPics	boolean	false	Only listings with photos
condition	string		new, like new, excellent, good, fair, salvage
proxyConfiguration	object		Apify proxy settings

Output Schema

Each result contains the listing data plus an intelligence object:

Field	Type	Description
id	string	Craigslist listing ID
title	string	Listing title
price	number	Parsed price (null if not listed)
priceFormatted	string	Display price (e.g. "$250")
url	string	Full listing URL
location	string	Neighborhood/area
postedAt	string	ISO timestamp
description	string	Full listing text
condition	string	Item condition
allImages	array	Image URLs
intelligence	object	See below

Intelligence Metrics

1. Deal Score (dealScore: 0-100)

Percentile-based price ranking within the result set. Cheapest items score highest. Uses title heuristics ("OBO", "firm") when price is missing.

2. Value Category (valueCategory: string)

Human-readable deal label based on dealScore thresholds.

3. Listing Freshness (listingFreshness: 0-100)

How recently the item was posted. Higher = newer.

4. Freshness Label (freshnessLabel: string)

"Just Listed" | "Recent" | "A Few Days Old" | "Stale Listing"

5. Photo Quality Score (photoQualityScore: 0-100)

Based on photo count with bonuses for visual diversity and high-resolution images.

6. Description Quality (descriptionQuality: 0-100)

Evaluates length, word variety, specs/measurements, contact info, with penalties for ALL CAPS and excessive punctuation.

7. Trust Score (trustScore: 0-100)

Composite seller trust indicator. Factors: photos, description detail, contact method, location, spam keywords.

8. Price Per Unit (pricePerUnit: number|null)

Computed when listing mentions "lot of X", "pack of 5", etc.

9. Red Flags (redFlags: string[])

Warning indicators: no photos, short description, suspicious pricing, ALL CAPS, spam keywords, relisting.

10. Opportunity Score (opportunityScore: 0-100)

The main "should I buy?" signal. Weighted composite of deal, freshness, trust, and photo scores with demand signal boost.

11. Opportunity Label (opportunityLabel: string)

"Act Now" | "Worth Checking" | "Maybe" | "Pass" | "Avoid"

12. Estimated Retail Price (categoryEstimatedRetailPrice: number|null)

Best-effort MSRP lookup from 100+ product keyword matches.

13. Savings vs Retail (savingsVsRetail: number|null)

Retail price minus listing price. Positive = savings. Null if retail unknown.

14. Title Sentiment (titleSentiment: string)

"Positive" (mint, like new) | "Negative" (broken, parts only) | "Neutral"

15. Estimated Days on Market (estimatedDaysOnMarket: integer|null)

Days since the listing was posted.

16. Market Demand Signal (marketDemandSignal: string)

"High Demand" | "Motivated Seller" | "Bargain Hunter Target" | "Standard"

Use Cases

Bargain Hunting

Filter results by opportunityScore > 70 to find the best deals quickly.

Market Research

Analyze the distribution of dealScore across a category to understand pricing trends.

Flipping Items

Look for listings where savingsVsRetail > 50 and trustScore > 60 to find profitable flip opportunities.

Monitoring Listings

Track listingFreshness combined with redFlags to spot new listings while avoiding scams.

Pricing

PAY_PER_EVENT: $0.01/run + $0.05/1K listings

FAQ

Q: What locations are supported? Any valid Craigslist subdomain (e.g. sfbay, newyork, chicago, losangeles, seattle, etc.)

Q: How many results can I get? Up to 500 per run. The scraper handles pagination automatically.

Q: Does it handle CAPTCHAs? The scraper detects CAPTCHA pages and logs a warning. Use Apify proxy configuration for better success rates.

Q: Why are some intelligence fields null? Fields like pricePerUnit and savingsVsRetail are only computed when enough data is available (e.g., quantity mentions in title, known retail price match).

Q: How accurate is the retail price estimate? The lookup table covers 100+ popular products. It matches keywords in the title, so accuracy depends on how well the title describes the product.