Clubhouse Email Scraper

Clubhouse Email Scraper

Clubhouse Email Scraper — Public Contact Emails from Clubhouse Profiles

The Clubhouse Email Scraper collects publicly indexed contact emails from Clubhouse profiles and returns them as structured, exportable data.

Read this first — expected volume. Clubhouse indexes relatively few public profile pages, so expect lower volume than mainstream networks. This is a property of the platform, not a fault in the Actor. Plan your run sizes and expectations accordingly.

With that stated plainly, the Clubhouse Email Scraper is still useful for a specific reason: the accounts Google has indexed skew toward founders, room hosts, coaches, investors and community builders who deliberately published a contact address.

The Clubhouse Email Scraper searches clubhouse.com and joinclubhouse.com through Google, filters for the email domains you choose, and returns account names, display names, profile URLs and the bio snippet each address came from.

It is a Clubhouse email extractor for founder outreach, host booking, community research and targeted lead generation — a precision tool rather than a volume tool.

Important: this Clubhouse Email Scraper never logs into Clubhouse, never uses the Clubhouse API, and never opens the app or website. Every record comes from publicly indexed Google search results.

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Key Features of the Clubhouse Email Scraper

Every feature listed is genuine crawler behaviour.

Feature	What it means in practice
Dual-domain site: search	The Clubhouse Email Scraper queries both clubhouse.com and the legacy joinclubhouse.com
Query expansion	Each keyword × domain pair runs as base, quoted, intitle: and one variant per query modifier
Domain-filtered extraction	Only addresses ending in your customDomains list are collected
Global deduplication	Each email is written once per run, across every query and page
Obfuscation-aware parser	Handles name [at] domain [dot] com, name (at) domain, name @ domain.com, domain .com, zero-width characters and the full-width ＠
Junk filter	Rejects placeholders such as email@, yourname@, test@, xxx@ and single-character locals
Boundary-correct matching	@gmail.com never matches inside @gmail.company or @gmail.com.br
Soft-wrap repair	Drops a hit that is only the tail of another address in the same block
Structural HTML parsing	Finds the <h3> title then the smallest surrounding block — independent of Google's CSS class names
Whole-page fallback parser	A Google markup change degrades to "emails without account metadata" rather than "no emails"
Concurrency	An asyncio worker pool runs queries in parallel with a shared stop signal on maxEmails
Retry logic	Up to 3 attempts per page, exponential backoff, a fresh proxy session per request
Block detection	CAPTCHA, "unusual traffic" and consent pages are detected and retried, not counted as empty
Blocked-query requeue	Blocked or failed queries get one more attempt at the end of the run
Resumable state	Key-value-store checkpoints keyed by an input hash, flushed on PERSIST_STATE, MIGRATING and ABORTING
Streaming dataset writes	Each lead is pushed to the Apify dataset the moment it is extracted
Run summary	Pages fetched, blocked pages, retries and emails per page are logged

Because Clubhouse yields fewer indexed pages, query expansion and generous maxPagesPerQuery matter more here than on a large network.

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How the Clubhouse Email Scraper Works

The Clubhouse Email Scraper pipeline is six steps long and fully transparent. There is no browser, no JavaScript rendering, no authentication and no cookies.

1. Read input. Keywords, optional location, email domains and run limits are loaded.

2. Build search queries. Google queries use the site: operator across both Clubhouse domains, for example site:clubhouse.com founder "@gmail.com" contact.

3. Fetch result pages. Requests go out asynchronously with aiohttp through the Apify GOOGLE_SERP proxy, with proxy rotation and retry logic on each attempt.

4. Parse each result block. The Clubhouse Email Scraper locates the <h3> heading, walks up to the tightest enclosing block, and reads title, site label and snippet.

5. Extract and normalise emails. A domain-filtered regex pulls candidate addresses; normalisation, obfuscation handling and the junk filter clean the rest.

6. Deduplicate and push. Unique addresses stream into the dataset immediately, so you can export while the run is still going.

Base queries execute before expanded variants, so the earliest rows the Clubhouse Email Scraper writes are usually the most relevant.

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What Data Does the Clubhouse Email Scraper Extract?

Each dataset item is one unique email address described by 14 structured fields.

Alongside the address you get the account label Google printed, a parsed display name, the handle where Clubhouse exposes one, a canonical profile URL and the bio snippet the address came from.

Provenance is included: the keyword and the exact Google query that produced the lead, plus a UTC timestamp.

On a low-volume platform that provenance is especially useful — it tells you quickly which keywords are worth keeping and which return nothing.

The Clubhouse Email Scraper collects nothing beyond these fields — no room history, no follower graph, no club membership, no private data.

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Clubhouse Email Scraper Input Schema

Every field below is taken verbatim from the Clubhouse Email Scraper input schema.

Field	Type	Default	Description
keywords	array (required)	["founder", "host"]	Search terms describing the Clubhouse accounts you want (niche, job title, industry)
location	string	""	Optional location phrase added to every query
customDomains	array	["@gmail.com", "@yahoo.com"]	Only emails on these domains are collected; leading @ optional
maxEmails	integer (1–10000)	20	Stop once this many unique emails have been collected
countryCode	string	""	Two-letter country code for the search proxy (US, GB, DE…)
expandQueries	boolean	true	Search each keyword × domain pair with several phrasings
queryModifiers	array	["email", "contact", "inquiries", "hire", "work with me"]	Extra words combined with each keyword when expansion is on
maxPagesPerQuery	integer (1–50)	30	Page cap per query
maxConcurrency	integer (1–20)	5	How many queries run in parallel

JSON input example

{
  "keywords": ["startup founder", "podcast host", "business coach"],
  "location": "Dubai",
  "customDomains": ["@gmail.com", "@outlook.com"],
  "maxEmails": 100,
  "countryCode": "AE",
  "expandQueries": true,
  "queryModifiers": ["email", "contact", "inquiries", "hire", "work with me"],
  "maxPagesPerQuery": 30,
  "maxConcurrency": 5
}

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Clubhouse Email Scraper Output Schema

Every dataset item produced by the Clubhouse Email Scraper carries all 14 fields.

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 (handle or display name)
fullName	Display name parsed from a profile-style title; empty for post captions
username	URL-safe handle when Clubhouse 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 snippet, cleaned of labels and engagement counters
email	Lower-cased email address
emailDomain	The matched domain (e.g. @gmail.com)
possiblyTruncated	true when Google's snippet ellipsis touched the email — verify before sending
foundAt	ISO 8601 UTC timestamp

JSON output example

{
  "network": "Clubhouse",
  "keyword": "startup founder",
  "query": "site:clubhouse.com startup founder \"@gmail.com\" contact",
  "title": "Rana Habib (@ranahabib) on Clubhouse",
  "accountName": "@ranahabib",
  "fullName": "Rana Habib",
  "username": "ranahabib",
  "profileUrl": "https://www.clubhouse.com/@ranahabib",
  "url": "https://www.clubhouse.com/@ranahabib",
  "description": "Founder, fintech. Hosts a weekly room on early-stage fundraising. Dubai. Contact: rana.habib.build@gmail.com",
  "email": "rana.habib.build@gmail.com",
  "emailDomain": "@gmail.com",
  "possiblyTruncated": false,
  "foundAt": "2026-08-31T16:41:29Z"
}

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How to Use the Clubhouse Email Scraper

Step 1 — open the Actor. Launch the Clubhouse Email Scraper from the Apify Store.

Step 2 — set realistic expectations. Given the low index coverage, treat a Clubhouse run as a supplementary source, not a primary list-building channel.

Step 3 — use broad role keywords. founder, investor, host, coach and community manager work better here than narrow niche phrases, simply because there is less indexed content to match.

Step 4 — keep expandQueries on and maxPagesPerQuery high. On a thin index, the extra phrasings are where most of the yield comes from.

Step 5 — run and export. Take the Clubhouse Email Scraper dataset as JSON, CSV or XLSX, or pull it via the Apify API.

Because volume is limited, most teams run the Clubhouse Email Scraper alongside a higher-yield sibling such as the LinkedIn Email Scraper for B2B contacts or the X Email Scraper, where much of the original Clubhouse crowd is still active.

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Use Cases for the Clubhouse Email Scraper

Use case	How the Clubhouse Email Scraper helps
Founder outreach	Reach early-stage founders who published a contact address
Room and panel booking	Find hosts and speakers for an audio event
Podcast guest sourcing	Identify people already comfortable with live audio formats
Coaching and consulting sales	Contact coaches and advisors listing enquiry addresses
Investor and angel research	Surface investors with public contact details
Community manager recruiting	Find people running recurring rooms and clubs
Regional market research	Study how founders in a given city describe themselves
Event and conference invitations	Build a speaker shortlist from public bios
Newsletter and audience growth	Reach hosts whose topic overlaps with yours
CRM enrichment	Attach Clubhouse handles and profile URLs to existing records

Every one of these works best as a supplement. The Clubhouse Email Scraper delivers a small, well-qualified list rather than a large one.

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Why Choose This Clubhouse Email Scraper

It is realistic. The Clubhouse Email Scraper tells you up front that Clubhouse indexes relatively few public profile pages, so expect lower volume than mainstream networks.

It covers both domains. Legacy joinclubhouse.com pages are still indexed and are searched alongside clubhouse.com.

It is honest about its source. Google's public index only. No API, no login, no private data.

It is resilient. Structural parsing plus a whole-page fallback keeps the crawler producing data through Google layout changes.

It is resumable and precise. Input-hashed checkpoints, domain filtering, boundary-correct matching, obfuscation handling and a junk filter.

It has siblings. The same engine powers the Discord Email Scraper and Telegram Email Scraper, both far higher-yield for community-driven outreach.

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Limitations

Read these before you run. They are real, and the first one is the most important.

• Low index coverage. Clubhouse indexes relatively few public profile pages, so expect lower volume than mainstream networks. A run that returns a handful of leads is normal for this platform.
• Only publicly indexed emails. If an address is not in Google's index, the Clubhouse Email Scraper cannot find it. Private data is never accessed.
• Google's ~300-result cap. A single query returns roughly 300 results at most. Query expansion exists to work around this — keep expandQueries on.
• possiblyTruncated. A true value means Google's snippet ellipsis may have clipped the address. Verify those rows before sending.
• Apify GOOGLE_SERP proxy required. The Clubhouse Email Scraper cannot run without Apify proxy credentials.
• Free-plan cap. Free Apify plans are limited to 100 emails per run; paid plans are uncapped.
• username and profileUrl availability. Populated only when Google's result exposes a handle. Some rows will carry accountName and fullName with an empty username and profileUrl — a Google limitation, not a defect.
• No guaranteed volume. Yield varies with keywords, domains and location, and is structurally lower on Clubhouse than on larger networks.

The Clubhouse Email Scraper is independent and not affiliated with, endorsed by or officially supported by Clubhouse.

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Related Actors

Several of these are considerably higher-yield than Clubhouse and are worth running in parallel.

Actor	What it collects
Clubhouse Email and Phone Number Scraper	Emails and phone numbers from Clubhouse
Clubhouse Phone Number Scraper	Public phone numbers from Clubhouse
Behance Email Scraper	Public contact emails from Behance
Bigo Live Email Scraper	Public contact emails from Bigo Live
Bluesky Email Scraper	Public contact emails from Bluesky
Bumble Email Scraper	Public contact emails from Bumble
Dailymotion Email Scraper	Public contact emails from Dailymotion
DeviantArt Email Scraper	Public contact emails from DeviantArt
Discord Email Scraper	Public contact emails from Discord
Dribbble Email Scraper	Public contact emails from Dribbble
Facebook Email Scraper	Public contact emails from Facebook
Goodreads Email Scraper	Public contact emails from Goodreads
Hinge Email Scraper	Public contact emails from Hinge
Instagram Email Scraper	Public contact emails from Instagram
KakaoTalk Email Scraper	Public contact emails from KakaoTalk
Kick Email Scraper	Public contact emails from Kick
Lemon8 Email Scraper	Public contact emails from Lemon8
Likee Email Scraper	Public contact emails from Likee
LINE Email Scraper	Public contact emails from LINE
LinkedIn Email Scraper	Public contact emails from LinkedIn
Mastodon Email Scraper	Public contact emails from Mastodon
Medium Email Scraper	Public contact emails from Medium
Mixcloud Email Scraper	Public contact emails from Mixcloud
Patreon Email Scraper	Public contact emails from Patreon
Pinterest Email Scraper	Public contact emails from Pinterest
Quora Email Scraper	Public contact emails from Quora
Reddit Email Scraper	Public contact emails from Reddit
Rumble Email Scraper	Public contact emails from Rumble
Snapchat Email Scraper	Public contact emails from Snapchat
SoundCloud Email Scraper	Public contact emails from SoundCloud
Substack Email Scraper	Public contact emails from Substack
Telegram Email Scraper	Public contact emails from Telegram
Threads Email Scraper	Public contact emails from Threads
TikTok Email Scraper	Public contact emails from TikTok
Tinder Email Scraper	Public contact emails from Tinder
Tumblr Email Scraper	Public contact emails from Tumblr
Twitch Email Scraper	Public contact emails from Twitch
Vimeo Email Scraper	Public contact emails from Vimeo
VK Email Scraper	Public contact emails from VK
WeChat Email Scraper	Public contact emails from WeChat
Weibo Email Scraper	Public contact emails from Weibo
X Email Scraper	Public contact emails from X

Clubhouse Email Scraper Example Run

A fintech accelerator wants to invite regional founders to an application cycle.

They run the Clubhouse Email Scraper with keywords: ["fintech founder", "startup host"], location: "Dubai", customDomains: ["@gmail.com", "@outlook.com"] and maxEmails: 100.

Because Clubhouse indexes relatively few public profile pages, the run finishes with a modest dataset rather than hundreds of rows — the expected outcome on this platform.

They drop rows flagged possiblyTruncated, review each description snippet by hand, and add the qualified contacts to a shortlist. On a small list, manual review is entirely practical.

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Clubhouse Email Scraper FAQ

Why does the Clubhouse Email Scraper return fewer results than other scrapers?

Because Clubhouse indexes relatively few public profile pages, so expect lower volume than mainstream networks. It is a platform characteristic, not a bug.

Does the Clubhouse Email Scraper log into Clubhouse?

No. It never logs in, never uses the Clubhouse API, and never opens the app or website. All data comes from publicly indexed Google search results.

Which domains does it search?

Both clubhouse.com and the legacy joinclubhouse.com, which still has indexed pages.

Where do the emails come from?

From Google result titles, site labels and snippets — profile bios where the account holder published a contact address themselves.

Do I need an Apify proxy?

Yes. The Clubhouse Email Scraper requires the Apify GOOGLE_SERP proxy and cannot run without Apify proxy credentials.

How many emails can I collect per run?

Free Apify plans are capped at 100 emails per run; paid plans are uncapped. In practice, Clubhouse's thin index is the binding constraint long before your plan is.

How can I get more results?

Keep expandQueries on, keep maxPagesPerQuery high, broaden your keywords, and add more email domains. Beyond that, the index is the ceiling.

Why is username empty on some rows?

Google did not expose a handle in that result. Those rows still include accountName, fullName and the bio snippet. It is a Google limitation, not a scraper defect.

What does possiblyTruncated: true mean?

Google's snippet ellipsis touched the address, so it may be incomplete. Verify those rows before sending.

Does the Clubhouse Email Scraper deduplicate?

Yes, globally. Each address appears once per run regardless of how many queries surfaced it.

What happens if a run is interrupted?

State is checkpointed in the key-value store, keyed by a hash of your input, and flushed on PERSIST_STATE, MIGRATING and ABORTING. Restarting resumes.

Is this affiliated with Clubhouse?

No. The Clubhouse Email Scraper is independent and is not affiliated with, endorsed by or officially supported by Clubhouse.

How should I use the results responsibly?

Follow GDPR, CAN-SPAM and local law. Keep outreach relevant and personal — which is easy here, because the lists are small.

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Support

Questions, bug reports or a custom build request? Email neurodata.apify@gmail.com with your run ID so the Clubhouse Email Scraper logs can be reviewed.