Equipment Auction Comps — Heavy Machinery Price Monitor avatar

Equipment Auction Comps — Heavy Machinery Price Monitor

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from $1.00 / 1,000 results

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Equipment Auction Comps — Heavy Machinery Price Monitor

Equipment Auction Comps — Heavy Machinery Price Monitor

Track used construction and agricultural equipment listings across auctions and marketplaces in one schema, with first_seen so you can see what is newly listed and what has moved.

Pricing

from $1.00 / 1,000 results

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Developer

alaudin burki

alaudin burki

Maintained by Community

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1

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5 days ago

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Equipment Auction & Used-Listing Comps — Heavy Machinery Price Monitor

Track used construction and agricultural equipment across marketplaces in one schema, and get the comparison a dealer actually wants: for each make and model, how many are listed right now and at what asking prices — plus firstSeenAt, so you can see what is newly listed and what has moved.

What you get

Rows — one per machine

FieldDescription
idStable id, mascus:hi6l5rbp
makeManufacturer, resolved from a known-makes list — john deere, not john
modelModel with the machine-type words stripped — 314e lcr
titleReadable name, cat 314e lcr
categoryThe category it was found under, e.g. crawler-excavators
typeWordsThe machine-type words found in the slug, e.g. tracked excavator
priceAsking price if the index exposes one, else null — never guessed
urlDirect link to the listing
isNewtrue when onlyNewSinceLastRun is on and this id was not seen before
firstSeenAtWhen this listing first appeared — carried across runs
scrapedAtThis run's timestamp

A second dataset, comps — one row per make + model

FieldDescription
machinecat 314e lcr
listingsHow many are listed right now
priceLow / priceHighThe asking-price range, when prices are exposed
pricesSeenHow many listings actually carried a price
categories, sourcesWhere they came from
sampleUrlOne listing to look at

Sample output

{
"id": "mascus:hi6l5rbp",
"make": "cat",
"model": "314e lcr",
"title": "cat 314e lcr",
"category": "crawler-excavators",
"typeWords": "tracked excavator",
"price": null,
"url": "https://www.mascus.com/construction/crawler-excavators/cat-314e-lcr-tracked-excavator/hi6l5rbp.html",
"isNew": null,
"firstSeenAt": "2026-10-17T18:04:11.201Z",
"scrapedAt": "2026-10-17T18:04:11.201Z"
}
{ "machine": "cat 930h", "make": "cat", "model": "930h", "listings": 3,
"categories": "wheel-loaders", "sources": "mascus", "pricesSeen": 0 }

Default input

Runs with zero editing: three categories, Mascus, up to 1,000 listings, comps on. First run returns everything; turn on Only new since last run after that to get only what changed.

Limitations — stated plainly, because a surprise costs you a review

  • One source today: Mascus. Its robots.txt is permissive and its listing URLs are a stable contract. It is the only source that answered.
  • Ritchie Bros, MachineryTrader, AuctionTime and TractorHouse all return HTTP 403 to a plain request. They are not scraped here — faking them would give you silently empty rows. Covering them needs the platform's proxy or a browser session.
  • Asking prices only, and only where the index exposes them. Mascus's category pages do not publish a price, so price is usually null. Sold prices at auction live on individual lot pages and are not collected. Do not read priceLow as a market value when pricesSeen is 0.
  • Make and model are parsed from the URL slug against a known-makes list. An unfamiliar brand is split at the first word, so a new manufacturer can appear as a two-word make.
  • This is not an appraisal tool. It reports what is listed and what is asked — never what a machine is worth.

Pricing

Pay per result — you are charged for the rows you receive, not for the run. Leave Max listings low while you are testing.

Notes on how it behaves

  • Every URL comes from the listing slug, never from generated CSS class names — Mascus's classes are hashed and change on deploy, and a parser built on them breaks silently.
  • Zero listings across every category is treated as a failure, not an empty result, so a layout change surfaces as an error instead of a blank CSV.
  • comps is a separate named dataset, not extra rows in the main one.