LoopNet Scraper for Commercial Real Estate Listings

Extract public LoopNet commercial real estate listings from a location search, a LoopNet search URL, or selected listing pages. Each dataset row represents one validated property listing with canonical identity, price, property type, size, location, image, provenance, and optional building and broker details.

Best fit for this Actor

Choose this Actor for LoopNet sale and lease research, commercial property sourcing, market comparisons, and broker-enriched listing datasets. Use location and property filters for discovery, or provide listing URLs when your workflow starts from a selected property set.

Focused standalone workflow

This Actor is designed as a focused standalone workflow for LoopNet commercial property discovery and listing-detail enrichment.

A practical acquisition scenario

A commercial real estate analyst starts with a city, listing type, and property category. The Actor collects canonical listing records with price, size, address, and property type; the analyst then enables detail enrichment for shortlisted listings and exports broker, cap-rate, building-size, and year-built fields into an acquisition worksheet.

Quick start input

{
  "location": "Austin, TX",
  "listingType": "for-sale",
  "propertyType": "Office",
  "maxResults": 10,
  "enrichDetails": true
}

You can also place LoopNet search pages in searchUrls or canonical property pages in startUrls.

What data you receive

Field	Meaning
listingId, url, name	Canonical listing identity and title
propertyType, propertySubtype, availability	Property classification and public status
price, priceText, currency, isAuction	Public pricing presentation
sizeValue, sizeUnit, buildingSize, lotSize	Property size fields
street, city, state, zip	Listing location
yearBuilt, capRate	Enriched property details when displayed
brokerName, brokerCompany	Public broker fields when displayed
sourceUrl, scrapedAt	Provenance and collection time

{
  "listingId": 40482433,
  "url": "https://www.loopnet.com/Listing/701-E-Franklin-St-Endicott-NY/40482433/",
  "name": "Commercial Property",
  "propertyType": "Office",
  "priceText": "$1,250,000",
  "currency": "USD",
  "city": "Endicott",
  "state": "NY",
  "sourceUrl": "https://www.loopnet.com/search/example/",
  "scrapedAt": "<ISO-8601 collection time>"
}

Run through the Apify API

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~loopnet-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"location":"Austin, TX","listingType":"for-sale","propertyType":"Office","maxResults":10}'

Read the default dataset for listing rows and the default key-value store for OUTPUT and RUN_SUMMARY.

Use with AI agents through Apify MCP

Example prompt:

Find public LoopNet office listings for sale in Austin. Return canonical URL, price, property type, size, address, broker fields, source URL, and collection time. Read the dataset and summarize the shortlisted properties with source provenance.

Give the agent a location, listing type, property type, and focused result scope. Ask it to retain source URLs, read the dataset after completion, and report the Apify cost with the outcome.

Pricing

This Actor uses Pay per event plus Apify platform usage. Listing records and optional detail enrichment use the events configured for the Actor. Open the live Pricing tab for current billing details and use maxResults or Apify run cost controls to keep each research pass focused.

Best results

Provide a specific location and property type for discovery, or canonical listing URLs for detail-first research. Enable enrichment after the broad listing fields identify the properties that support a deeper review.

Builder's note

I built the search parser around structured listing data first and canonical listing links as a second source because LoopNet can present the same useful property identity through different page structures. Keeping sourceUrl and scrapedAt on each row makes those observations easier to audit later.

Responsible use

Collect public listing data you are authorized to access and follow applicable laws, LoopNet terms, and your organization's real estate data policies.