Crexi Property Details Scraper

Turn a list of Crexi property ids into one flat, spreadsheet-ready row per listing. You get asking price, cap rate, NOI, lease terms, tenants, full address with coordinates, investment bullets, and the listing narrative, all as ready-to-use columns instead of nested JSON. Ids are fetched in parallel, so a batch of 50 properties finishes in seconds.

Both id formats work and can be mixed in a single run:

• 2340253: the numeric id from a Crexi listing URL
• crexi_2340253: the property_id returned by the Crexi Property Listings actor
• crexi_2340253_1: a multi-location row id (folded back to the base asset automatically)

Duplicates collapse to a single fetch, so you can paste unfiltered id lists straight in.

Input parameters

Field	Type	Default	Description
propertyIds	list of strings	required	Property ids, one per line. Up to 1,000 per run.
maxConcurrency	integer	5	Parallel requests (max 20). Lower this if you hit rate limits.
requestTimeoutSecs	integer	30	Timeout per request, in seconds.

Sample inputs

One property (smoke test)

{
    "propertyIds": ["2340253"]
}

Batch of numeric ids from Crexi URLs

{
    "propertyIds": [
        "2340253",
        "1984210",
        "2011884",
        "2202441"
    ]
}

Mixed id formats in one run (plain, prefixed, multi-location)

{
    "propertyIds": [
        "2340253",
        "crexi_1000002",
        "crexi_1234567_1"
    ]
}

Chained from the Crexi Property Listings actor

Feed its property_id column straight in:

{
    "propertyIds": [
        "crexi_2340253",
        "crexi_2340254",
        "crexi_2340255",
        "crexi_2340256",
        "crexi_2340257"
    ],
    "maxConcurrency": 10
}

Large batch with tuned parallelism and longer timeout

{
    "propertyIds": [
        "crexi_2340253", "crexi_1984210", "crexi_2011884", "crexi_2202441",
        "crexi_2100034", "crexi_2100035", "crexi_2100036", "crexi_2100037"
    ],
    "maxConcurrency": 15,
    "requestTimeoutSecs": 60
}

What this actor returns

Each record is a single flat row with 80+ columns, grouped into four families.

Identity and location

Field	Example
property_id / crexi_asset_id	crexi_2340253 / 2340253
name	Dutch Bros Ground Lease
status	Active
address, city, county, state_code, zip	2930 Sperry Ave, Patterson, Stanislaus County, CA, 95363
geo_latitude / geo_longitude	37.4645 / -121.1751
listing_url	direct link to the Crexi listing
hero_image_url	primary photo URL

Deal terms in two flavors. Display strings live under display_* and typed numeric values under metric_*, so spreadsheets get readable text and pipelines get sortable numbers:

Display field	Example	Numeric field	Example
display_asking_price	$1,534,000	metric_asking_price	1534000.0
display_cap_rate	4.50%	metric_cap_rate	4.5
display_noi	$69,000	metric_net_operating_income	69000.0
display_price_per_sqft	$1,614.74	metric_price_per_sq_ft	1614.74
display_lease_term	15.1 years	metric_lease_term	15.1
display_lot_size_acres	0.5	metric_lot_size	0.5

Plus lease type, tenancy, tenant list, rent bumps, ground lease flag, lease commencement and expiration dates, investment type, year built, and square footage in both forms.

Marketing text and listing flags. investment_bullets and listing_narrative arrive as clean plain text (HTML stripped). Boolean signals include flag_opportunity_zone, flag_has_om, flag_has_flyer, flag_has_virtual_tour, flag_is_sold, and flag_is_paused.

Broker of record. The lead brokerage is flattened into broker_name, broker_type, broker_office, and broker_email.

Sample output

{
    "property_id": "crexi_2340253",
    "crexi_asset_id": "2340253",
    "name": "Dutch Bros Ground Lease",
    "status": "Active",
    "address": "2930 Sperry Ave",
    "city": "Patterson",
    "state_code": "CA",
    "zip": "95363",
    "geo_latitude": 37.4645,
    "geo_longitude": -121.1751,
    "metric_asking_price": 1534000.0,
    "metric_cap_rate": 4.5,
    "metric_net_operating_income": 69000.0,
    "display_lease_type": "Absolute NNN",
    "display_lease_term": "15.1 years",
    "tenant_names": "Starbucks, Dutch Bros. Coffee",
    "display_rent_bumps": "10% Every 5 Years",
    "investment_bullets": "Prime Retail Location: High-visibility and easily accessible location...",
    "broker_name": "Jane Doe",
    "broker_office": "Marcus & Millichap",
    "hero_image_url": "https://images.crexi.com/assets/...",
    "listing_url": "https://www.crexi.com/properties/2340253/california-dutch-bros-ground-lease-grocery-outlet-outparcel"
}

Use cases

• Deal underwriting: pull cap rate, NOI, lease term, and rent bumps for a shortlist into one spreadsheet
• Pipeline enrichment: run the Crexi Property Listings actor for a region, feed its property_id column here for full lease-level detail
• Tenant research: extract tenant names and lease structures across many net-lease listings at once
• Comp building: collect price per square foot, year built, and lot size for a submarket
• Change monitoring: re-run the same id list on a schedule and diff status, metric_asking_price, and last_updated_on
• Broker outreach: export broker_name, broker_office, and broker_email for a targeted list

Notes

• Failed ids (removed listings, timeouts, blocked responses) are logged and skipped without aborting the run. The final status message lists which ids failed.
• Listings only carry the fields the broker published. A property without a lease section has no lease columns; those cells simply stay empty for that row.
• Use display_* columns for reports and screenshots, metric_* columns for filtering, sorting, and math.

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