🔨 AuctionTime Scraper

Pull structured records from Auctiontime — clean fields ready as CSV, JSON, JSONL, Excel, or XML for downstream pipelines.

Collect equipment auction listings from AuctionTime.com including excavators, tractors, trucks, trailers, and farm machinery. Perfect for equipment dealers monitoring prices, procurement teams sourcing inventory, and market analysts tracking equipment values. Get an auctiontime scraper without coding, download auction data as CSV or Excel, and monitor competitor equipment listings with bid prices and auction dates all included.

The AuctionTime Scraper collects heavy equipment auction listings with complete bid information and equipment specifications, up to 12 data fields per item, with no authentication required.

✨ What Does It Do

• 🖼️ Image URL - Browse equipment photos directly from your data without visiting the site
• 📝 Title - Full equipment description including year, manufacturer, and model for quick identification
• 🏭 Manufacturer - Equipment brand such as Caterpillar, John Deere, or Komatsu to filter by preferred brands
• 🔧 Model - Specific equipment model for inventory matching and comparison
• 📅 Year - Manufacturing year to assess equipment age and depreciation
• 💰 Current Bid - Live bid amount to track price trends across auctions
• 📊 Bid Count - Number of bids placed to gauge auction competitiveness
• 🕐 Auction End Date - When the auction closes to plan your bidding strategy
• 🌍 Location - City and state formatted for regional equipment sourcing
• 🔗 Listing URL - Direct link to the auction page for detailed inspection and bidding
• 📍 Scraped At - Timestamp of data collection for tracking freshness
• ⚠️ Error - Any collection issues for troubleshooting failed listings

📋 Data Fields

Each listing record includes the following fields (verified from live output):

Field	Description
title	Equipment listing title, e.g. "(4) KARRIER ST205/75R15 TRAILER TIRES"
manufacturer / model / year	Make, model, and manufacturing year
category	Equipment category, e.g. "Tires", "Shredder/Mower"
condition	Condition, e.g. "Used", "New"
currentBid / currentBidFormatted	Current bid amount (number and formatted, e.g. "$12,500")
minimumBid / buyNowPrice / bidCount	Minimum bid, buy-now price, and number of bids
currency	Currency code, e.g. "USD"
auctionStatus / auctionStartDate / auctionEndDate	Auction status and timing
lotNumber / reserveStatus / isOnlineBidding	Lot number, reserve status, online-bidding flag
locationFormatted / city / state / country / postalCode	Location details
latitude / longitude / googleMapsUrl	Geographic coordinates and map link
sellerName / sellerContact / sellerPhone / sellerWebsite / sellerLocation	Seller / auction house details
description / serialNumber / stockNumber / hours / mileage	Item description and specs
imageUrl / images / imageCount / videoCount	Primary image, all image URLs, media counts
specifications	Key/value map of additional equipment specs
listingUrl	Direct link to the auction listing page
listingId / externalId	Internal and external identifiers
scrapedAt	ISO timestamp of collection

🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the AuctionTime Scraper page on the Apify Store.
3. 🎯 Set input. Configure the input fields in the form (or paste a JSON), then set maxItems.
4. 🚀 Run it. Click Start and let the Actor collect your data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

⚠️ Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by AuctionTime.com or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.

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💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.

🆘 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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