CommercialCafe Email Scraper

CommercialCafe Email Scraper for office and commercial listing contacts

The CommercialCafe Email Scraper collects publicly indexed contact emails that appear on commercialcafe.com pages in Google's index. You give it keywords, an optional location and a list of email domains; it returns a deduplicated dataset of leads. It is a supplementary source in this category, and this page tells you that up front rather than at the bottom.

Yield note, stated plainly: CommercialCafe indexes market-report and listing pages rather than broker profiles, so expect low volume and few resolvable handles. In a measured live run the CommercialCafe Email Scraper parsed 3 result blocks, identified 0 named broker records and returned 1 unique email. That is the honest baseline. Do not plan a campaign around this Actor alone.

Where the CommercialCafe Email Scraper earns its place is as a merge-in source. CommercialCafe sits inside the Yardi listing network, so its indexed pages lean toward office, coworking and market-report content that other commercial marketplaces do not carry. Run it alongside a strong sibling such as the LoopNet Email Scraper, deduplicate on email, and treat whatever it adds as incremental coverage.

What the CommercialCafe Email Scraper actually does

The CommercialCafe Email Scraper builds Google queries with the site: operator against commercialcafe.com, fetches result pages through the Apify GOOGLE_SERP proxy using aiohttp, and parses each block structurally. It locates the <h3> title, walks up to the smallest surrounding block, and runs a domain-filtered regular expression over that block's text. Parsing is structural rather than CSS-class based, so a Google markup change degrades the run instead of breaking it.

It does not log into CommercialCafe, does not use any CommercialCafe API and never opens the site in a browser. There is no JavaScript rendering, no authentication and no cookies anywhere in the pipeline. Every field comes from titles, snippets and site labels that Google already publishes.

Commercial brokers and leasing teams publish contact addresses deliberately, because vacancy costs money and inbound enquiries are the point. The CommercialCafe Email Scraper only reads what those professionals already chose to make public.

Key features of the CommercialCafe Email Scraper

The engineering below is identical across this Actor family; what differs is how much CommercialCafe's indexed footprint gives it to work with.

Feature	What it does
Query expansion	Each keyword x domain pair runs as a base query, a quoted query, an intitle: query and one variant per modifier, base queries first.
Global deduplication	An address found by many queries is written to the dataset once.
Email normalisation	Handles name [at] domain [dot] com, name (at) domain, name @ domain.com, domain .com, zero-width characters and the full-width ＠ sign.
Junk filter	Rejects placeholders such as email@, yourname@, test@, xxx@ and single-character local parts.
Boundary-correct matching	@gmail.com will not match inside @gmail.company or @gmail.com.br.
Soft-wrap repair	Drops a hit that is only the tail of another email in the same result block.
Concurrency control	An asyncio worker pool with a shared stop signal on maxEmails.
Retries and block detection	Three attempts per page with exponential backoff, a fresh proxy session per request, and CAPTCHA or consent pages retried rather than counted as empty.
Failed-query requeue	Blocked or failed queries are retried once at the end of the run.
Resumable state	Key-value store state keyed by an input hash, saved on PERSIST_STATE, MIGRATING and ABORTING.
Whole-page fallback parser	A layout change degrades to emails without account details rather than to nothing.
Run summary	Pages fetched, blocked pages, retries and emails per page are logged.

How the CommercialCafe Email Scraper works

A CommercialCafe Email Scraper run starts by reading the input and hashing it into a resumable state key. The query set is then built by multiplying keywords by email domains and, when expandQueries is on, by query modifiers. A representative query looks like site:commercialcafe.com "office space" "@gmail.com" "Austin".

The CommercialCafe Email Scraper fetches result pages concurrently through the Apify GOOGLE_SERP proxy and parses them block by block. Emails are extracted, normalised, filtered by domain and deduplicated globally before each lead is pushed to the dataset immediately. Because CommercialCafe returns few blocks, a CommercialCafe Email Scraper run usually finishes well before it reaches maxEmails.

That early finish is expected behaviour, not a failure. The stop signal on maxEmails is shared across all workers; free Apify plans are capped at 100 emails per run and paid plans are uncapped.

CommercialCafe Email Scraper input fields

Field	Type	Default	Meaning
keywords	array (required)	["commercial broker", "office space"]	Search terms describing the accounts you want
location	string	""	Optional location phrase added to every query
customDomains	array	["@gmail.com","@yahoo.com"]	Only emails on these domains are kept; the @ is optional
maxEmails	integer 1-10000	20	Stop after this many unique emails
countryCode	string	""	Two-letter country for the search proxy (US, GB, DE...)
expandQueries	boolean	true	Search each keyword x domain pair in several phrasings
queryModifiers	array	["email","contact","listing agent","inquiries","broker"]	Extra words combined with each keyword when expansion is on
maxPagesPerQuery	integer 1-50	30	Page cap per query
maxConcurrency	integer 1-20	5	Parallel queries

Only keywords is required, so the CommercialCafe Email Scraper runs on defaults out of the box. Given the small indexed footprint, keep expandQueries on and widen customDomains before you do anything else.

Location targeting in the CommercialCafe Email Scraper

location is the most valuable input here, but its role is different than on a high-yield platform. On CommercialCafe it works less as a filter and more as a way to reach different corners of a thin index. Running the CommercialCafe Email Scraper across several metros and merging is usually better than one national sweep.

Metro phrases are the right starting point, because CommercialCafe's market-report pages are organised by metro office market: "Austin", "Chicago", "Charlotte", "Denver". Those report pages are exactly the content this platform indexes best, so metro phrasing matches the grain of the source.

County phrases are worth trying for industrial and flex product: "Travis County", "DuPage County", "Mecklenburg County". Expect thinner returns than metro phrasing gives you, because county language is rarer in office market copy.

State phrases suit anyone with a statewide remit, such as a regional lender or a facilities contractor: "Texas", "Illinois", "North Carolina". Pair a state-level location with countryCode: "US" so the search proxy resolves to the right index. Submarket phrases such as "downtown Austin" or "the Loop" sometimes surface a leasing contact that a metro query buries, and cost nothing to try.

Example input JSON

{
  "keywords": ["office space", "coworking space", "commercial broker"],
  "location": "Austin",
  "customDomains": ["@gmail.com", "@yahoo.com", "@outlook.com", "@hotmail.com"],
  "maxEmails": 100,
  "countryCode": "US",
  "expandQueries": true,
  "queryModifiers": ["email", "contact", "listing agent", "inquiries", "broker"],
  "maxPagesPerQuery": 30,
  "maxConcurrency": 5
}

CommercialCafe Email Scraper output fields

Every dataset item written by the CommercialCafe Email Scraper carries all fourteen fields below, even when several of them are empty.

Field	Meaning
network	Platform name
keyword	The keyword that produced the lead
query	The exact Google query used
title	Raw result title
accountName	Account label Google prints
fullName	Display name parsed from a profile-style title; empty for non-profile results
username	URL-safe handle when CommercialCafe exposes one; otherwise null
profileUrl	Canonical account URL when a handle is known; otherwise empty
url	Direct platform link when exposed, else the profile URL
description	Bio or snippet text, cleaned of labels and counters
email	Lower-cased email address
emailDomain	The matched domain, for example @gmail.com
possiblyTruncated	true when Google's snippet ellipsis touched the email
foundAt	ISO 8601 UTC timestamp

Because CommercialCafe indexes market-report and listing pages rather than broker profiles, most rows will have username: null and an empty profileUrl. The example below shows that honestly rather than dressing it up.

Example output JSON

[
  {
    "network": "CommercialCafe",
    "keyword": "office space",
    "query": "site:commercialcafe.com \"office space\" contact \"@gmail.com\" \"Austin\"",
    "title": "Austin Office Market Report - Q1 | CommercialCafe",
    "accountName": "CommercialCafe Austin Office Market",
    "fullName": "",
    "username": null,
    "profileUrl": "",
    "url": "https://www.commercialcafe.com/office-market-report/austin",
    "description": "Austin office availability and asking rents. Leasing enquiries: austin.office.leasing@gmail.com",
    "email": "austin.office.leasing@gmail.com",
    "emailDomain": "@gmail.com",
    "possiblyTruncated": false,
    "foundAt": "2026-03-13T10:41:05Z"
  },
  {
    "network": "CommercialCafe",
    "keyword": "commercial broker",
    "query": "site:commercialcafe.com \"commercial broker\" \"@yahoo.com\" \"Austin\"",
    "title": "Commercial Broker - Congress Ave Office Listing | CommercialCafe",
    "accountName": "Congress Ave Office Listing",
    "fullName": "",
    "username": null,
    "profileUrl": "",
    "url": "https://www.commercialcafe.com/commercial-real-estate/us/tx/austin/",
    "description": "Sublease available, downtown Austin. Broker contact: congress.leasing.team@yahoo.com",
    "email": "congress.leasing.team@yahoo.com",
    "emailDomain": "@yahoo.com",
    "possiblyTruncated": true,
    "foundAt": "2026-03-13T10:41:44Z"
  }
]

Use cases for the CommercialCafe Email Scraper

Read this table with the yield note in mind: these are realistic supplementary uses, not primary channels.

Audience	How they use the CommercialCafe Email Scraper
Office market researchers	Pick up leasing and report contacts attached to metro office market pages.
Coworking and flex operators	Find leasing contacts on office and coworking listing pages in a target metro.
Facilities and building services suppliers	Reach the leasing side of buildings advertising availability.
CRE technology vendors	Add a small number of incremental contacts to a list built from stronger sources.
Lenders and debt brokers	Use as a coverage top-up when a metro is thin on the larger marketplaces.
Title and appraisal firms	Cross-check a market list for contacts the bigger portals missed.
Property marketing agencies	Identify listings whose marketing pages are thin and pitch accordingly.
Data teams building a market map	Merge on email with other Actors to widen coverage of a metro.

The CommercialCafe Email Scraper is a top-up, not a pipeline. If you need a primary commercial source, start with the Showcase Email Scraper or the Crexi Email Scraper instead.

CommercialCafe Email Scraper examples

A coworking operator expanding into Austin runs the CommercialCafe Email Scraper with keywords set to ["coworking space", "office space"] and location "Austin". They set maxEmails to 100 knowing the run will very likely finish well short of it. Whatever it returns goes into the same sheet as their LoopNet and Showcase results, deduplicated on email.

A facilities services firm covering Illinois widens customDomains to ["@gmail.com","@yahoo.com","@outlook.com","@hotmail.com"]. Widening domains is the highest-return adjustment on a thin source, because every additional consumer mailbox domain is a genuinely new chance at a match. They then run the CommercialCafe Email Scraper across "Chicago", "Naperville" and "Rockford" separately.

A data team building a national office-market contact map schedules the CommercialCafe Email Scraper monthly. Individual runs are small, but the dataset accumulates and the index does change over time. They deduplicate on email between runs and keep foundAt to track when each contact first appeared.

Responsible use of scraped commercial contacts

Everything the CommercialCafe Email Scraper returns was already published on a public web page and indexed by Google. That does not make every downstream use lawful, and knowing which rules apply to you is your responsibility. What follows is practical guidance, not legal advice.

Under CAN-SPAM in the United States, commercial email must avoid deceptive headers and subject lines, identify itself as an advertisement where required, include a valid physical postal address, and honour opt-out requests promptly. Under the GDPR and UK GDPR, a named individual's business address is still personal data, so you need a lawful basis, a genuine legitimate-interest assessment where you rely on one, transparency about the source, and a working route to object or erase. ePrivacy rules and several EU member states add consent requirements for electronic marketing that go beyond the GDPR baseline.

Operational habits matter as much as the statute when you work with CommercialCafe Email Scraper output. Given how often CommercialCafe rows are team or listing inboxes rather than named individuals, be especially careful that your message is relevant to whoever actually reads it. Hold possiblyTruncated rows out of a first send, keep a suppression list across runs, and retain query and foundAt as provenance.

Limitations of the CommercialCafe Email Scraper

CommercialCafe indexes market-report and listing pages rather than broker profiles, so expect low volume and few resolvable handles. In a measured live run the CommercialCafe Email Scraper parsed 3 blocks, identified 0 named brokers and returned 1 unique email. That is the leading limitation and it will not be engineered away, because the constraint is what Google has indexed.

The CommercialCafe Email Scraper only finds accounts whose email is publicly visible in Google's index. A leasing contact behind a form or inside an image will never appear, however many pages you fetch.

Google caps a single query at roughly 300 results, which is why query expansion exists. On a thin source the cap is rarely the binding constraint, but leaving expandQueries on still maximises the number of distinct pages the Actor sees.

username and profileUrl are only populated when CommercialCafe exposes a handle in the Google result. Here that is uncommon, so most rows carry accountName with an empty username and profileUrl. That is a Google limitation, not a bug.

possiblyTruncated: true means Google's snippet ellipsis touched the address and it may be incomplete. The CommercialCafe Email Scraper requires the Apify GOOGLE_SERP proxy and cannot run without Apify proxy credentials. Free Apify plans stop at 100 emails per run, and results vary with keywords, domains and location, so no volume is guaranteed.

CommercialCafe Email Scraper FAQ

How many results should I expect from the CommercialCafe Email Scraper?

Very few. CommercialCafe indexes market-report and listing pages rather than broker profiles, so expect low volume and few resolvable handles. A measured live run parsed 3 blocks, identified 0 named brokers and returned 1 unique email.

Then why would I run the CommercialCafe Email Scraper at all?

As a merge-in source. It reaches Yardi-network office and market-report pages that other commercial marketplaces do not carry. A handful of incremental contacts per metro is a fair expectation.

Does the CommercialCafe Email Scraper log into CommercialCafe?

No. It never logs in, never calls an API and never opens the site in a browser. Every field comes from publicly indexed Google search results.

Is this an official CommercialCafe or Yardi tool?

No. It is an independent Apify Actor and is not affiliated with, supported by or endorsed by CommercialCafe or Yardi.

Why is username null on almost every row?

Because CommercialCafe's indexed pages are reports and listings, not broker profiles with handles. Google prints no handle for those pages, so there is nothing to build a canonical profile URL from.

Which email domains should I use with the CommercialCafe Email Scraper?

Widen beyond the defaults immediately: add @outlook.com and @hotmail.com to @gmail.com and @yahoo.com. On a thin source, domain breadth is the single highest-return setting.

Can I improve yield with better keywords?

Somewhat. Favour terms that match report and listing language, such as "office space", "sublease" or "coworking space", over profile-style terms. Broker-profile phrasing performs poorly here for the reason stated in the yield note.

What does possiblyTruncated mean?

Google's snippet cut the text with an ellipsis close enough to the address that it may be incomplete. Verify those rows before sending.

Does a CommercialCafe Email Scraper run resume if interrupted?

Yes. State lives in the key-value store keyed by an input hash, with saves on PERSIST_STATE, MIGRATING and ABORTING.

Do I need my own proxy?

No, but Apify proxy credentials are required, because the CommercialCafe Email Scraper uses the Apify GOOGLE_SERP proxy.

Why does my CommercialCafe Email Scraper run finish so quickly?

It ran out of indexed pages before it ran out of email budget. That is the expected behaviour for this platform, not an error.

What should I pair it with?

Run the CommercialCafe Email Scraper alongside the CommercialSearch Email Scraper and a high-yield source, then deduplicate on email.

Related Actors

Actor	What it collects
CommercialCafe Email and Phone Number Scraper	Emails and phone numbers from CommercialCafe
CommercialCafe Phone Number Scraper	Public phone numbers from CommercialCafe
Apartment List Email Scraper	Public contact emails from Apartment List
ApartmentFinder Email Scraper	Public contact emails from ApartmentFinder
Apartments.com Email Scraper	Public contact emails from Apartments.com
Century 21 Agent Email Scraper	Public contact emails from Century 21
Coldwell Banker Agent Email Scraper	Public contact emails from Coldwell Banker
CommercialSearch Email Scraper	Public contact emails from CommercialSearch
Compass Agent Email Scraper	Public contact emails from Compass
Crexi Email Scraper	Public contact emails from Crexi
Domain Agents Email Scraper	Public contact emails from Domain
Homes & Land Email Scraper	Public contact emails from Homes & Land
Homes.com Email Scraper	Public contact emails from Homes.com
HotPads Email Scraper	Public contact emails from HotPads
Keller Williams Agent Email Scraper	Public contact emails from Keller Williams
Land And Farm Email Scraper	Public contact emails from Land And Farm
Land.com Email Scraper	Public contact emails from Land.com
LandWatch Email Scraper	Public contact emails from LandWatch
LoopNet Email Scraper	Public contact emails from LoopNet
OnTheMarket Email Scraper	Public contact emails from OnTheMarket
RealEstate.com.au Agents Email Scraper	Public contact emails from realestate.com.au
Realtor.ca Email Scraper	Public contact emails from Realtor.ca
Realtor.com Rentals Email Scraper	Public contact emails from Realtor.com
Redfin Rentals Email Scraper	Public contact emails from Redfin
RE/MAX Agent Email Scraper	Public contact emails from RE/MAX
Rent.com Email Scraper	Public contact emails from Rent.com
RentCafe Email Scraper	Public contact emails from RentCafe
Zillow Rentals Email Scraper	Public contact emails from Zillow
Zumper Email Scraper	Public contact emails from Zumper
Apartment List Email and Phone Number Scraper	Emails and phone numbers from Apartment List
ApartmentFinder Email and Phone Number Scraper	Emails and phone numbers from ApartmentFinder
Apartments.com Email and Phone Number Scraper	Emails and phone numbers from Apartments.com
Century 21 Email and Phone Number Scraper	Emails and phone numbers from Century 21
Coldwell Banker Email and Phone Number Scraper	Emails and phone numbers from Coldwell Banker
CommercialSearch Email and Phone Number Scraper	Emails and phone numbers from CommercialSearch
Compass Email and Phone Number Scraper	Emails and phone numbers from Compass
Crexi Email and Phone Number Scraper	Emails and phone numbers from Crexi
Domain Email and Phone Number Scraper	Emails and phone numbers from Domain
Homes & Land Email and Phone Number Scraper	Emails and phone numbers from Homes & Land
Homes.com Email and Phone Number Scraper	Emails and phone numbers from Homes.com
Keller Williams Email and Phone Number Scraper	Emails and phone numbers from Keller Williams
Land And Farm Email and Phone Number Scraper	Emails and phone numbers from Land And Farm

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