Twitter/X Leads Scraper — turn searches and hashtags into contactable author profiles

Turn X/Twitter into a lead list you can actually email. Give this actor search terms, hashtags, or @handles and get back one row per unique author — not a noisy tweet timeline — with their name, bio, follower count, verified status, website, an email found in the bio or on their linked site, an email_status flag, and a 0–100 lead score that sorts the best leads first. Built for B2B cold email, creator and founder outreach, agencies, and recruiters who want contactable people, not raw tweets. Pay-per-result — you're charged only for the leads delivered after your filters — and no X/Twitter login or API key is needed.

What it does

• Searches X/Twitter for your terms, hashtags, and handles — tweets are fetched through the apidojo/tweet-scraper data provider, so you never supply credentials.
• Collapses tweets into unique authors: a two-pass roll-up dedupes every matching tweet down to one row per author handle, and averages likes + retweets + replies across each author's collected tweets into an engagement_rate (when the underlying data carries engagement counts).
• Finds emails from two sources: it scans each author's bio text for inline emails, and (with enrichEmails on) visits their bio-link website — home, /contact, /contact-us, and /about — to extract real emails plus LinkedIn/Facebook/Twitter links. Link-in-bio pages (Linktree, Beacons, etc.) are resolved one hop further, but only to domains matching the author's own name or handle, so a sponsor's email never contaminates your list.
• Filters before you pay: min/max follower bands, verified-only, has-website, has-email.
• Scores every lead 0–100 — email +40, website +15, follower-band fit up to +15, verified +5, engagement up to +20 — and sorts best-first.
• Dedupes by handle, website domain, and email, and optionally writes an AI cold-opener per lead using your own OpenAI or Anthropic key (used once per run, never stored).

Use cases

• Niche founder outreach — search "ai founder" or "shopify agency" and get the people tweeting about your space, with emails.
• Hashtag communities — turn #buildinpublic into a CSV of contactable indie builders for a launch campaign.
• Creator partnerships — filter to 5k–500k followers to find mid-tier creators with real engagement, then pitch collaborations.
• Recruiting — find engineers or designers active in a technical hashtag and reach them off-platform by email.
• CRM enrichment — feed a list of known @handles and get back emails, websites, and social links for your existing contacts.

Input

Provide at least one of searchTerms, hashtags, or handles.

Field	Type	Default	Description
searchTerms	array	["ai founder", "saas indie hacker"]	Keywords/phrases to search X/Twitter for. Matching tweets are collapsed to their authors.
hashtags	array	["buildinpublic"]	Hashtags (with or without #); treated as extra search terms.
handles	array	—	Specific @handles or profile URLs to pull tweets from, one per line.
maxItems	integer	200	How many tweets to fetch before rolling up to unique authors. More tweets = more authors discovered.
minFollowers	integer	0	Keep only authors with at least this many followers (0 = off).
maxFollowers	integer	0	Keep only authors with at most this many followers (0 = no cap).
onlyVerified	boolean	false	Keep only verified profiles.
onlyWithWebsite	boolean	false	Drop authors with no bio link.
onlyWithEmail	boolean	false	Drop authors where no email could be found.
enrichEmails	boolean	true	Visit each author's bio-link website to extract emails and socials.
writeOpeners	boolean	false	Generate a personalized one-sentence AI opener per lead (needs your key below).
llmProvider	string	"openai"	openai or anthropic.
llmApiKey	string	—	Your own OpenAI/Anthropic API key. Used only for openers; never stored.
llmModel	string	—	Optional model override (defaults: gpt-4o-mini / claude-haiku-4-5).

{
  "searchTerms": ["ai founder", "saas indie hacker"],
  "hashtags": ["buildinpublic"],
  "maxItems": 200,
  "minFollowers": 1000,
  "onlyWithEmail": true,
  "enrichEmails": true
}

Output

One dataset row per unique author, sorted best lead first. Export to CSV, JSON, or Excel from the Output tab.

{
  "handle": "somefounder",
  "name": "Some Founder",
  "bio": "Building an AI tool for agencies. Ex-Google. hello@somestartup.com",
  "email": "hello@somestartup.com",
  "website": "https://somestartup.com",
  "followers": 24800,
  "verified": true,
  "engagement_rate": 1.8,
  "tweets_seen": 3,
  "profile_url": "https://x.com/somefounder",
  "email_status": "found",
  "lead_score": 90
}

When enrichment finds more, rows also carry extra_emails (up to 5 additional addresses) and any linkedin / facebook / twitter links found on the author's site. With writeOpeners on, each lead gets an icebreaker field.

Pricing

This actor uses Apify pay-per-event pricing: a fraction of a cent per result — see the Pricing tab for the exact rate. You're charged only for the author leads delivered after dedup and your filters — with onlyWithEmail on, authors without an email cost you nothing. No subscription, no charge for empty runs, and the free Apify plan is enough to try it on a real search before spending anything.

Tips / FAQ

Why authors instead of tweets? Search results are tweets, but for outreach you need people. Every matching tweet is rolled up to its author, so the dataset is a deduped list of contactable profiles — tweets_seen tells you how often each author matched.

Will every author have an email? No. X shows public emails for very few accounts; most emails come from bios and linked websites. Authors with no email show email_status: "missing" — use onlyWithEmail to keep (and pay for) only contactable leads.

Is maxItems the number of leads? No — it's the number of tweets scanned before the author roll-up. 200 tweets might yield anywhere from a handful to ~150 unique authors depending on the query.

Why is engagement_rate sometimes null? It's computed from like/retweet/reply counts averaged across the author's collected tweets; when the underlying data doesn't include those counts, the field stays null and the lead score simply skips that component.

Where does the data come from, and what if the source is down? Tweets come via an upstream data provider (apidojo/tweet-scraper). On a transient upstream outage the run ends gracefully with a "temporarily unavailable — please retry" message and you're charged nothing.

Is this legal? It reads public profile and tweet data only. Use the leads for legitimate outreach and follow X's terms plus anti-spam laws (CAN-SPAM, GDPR).

Related actors

• LinkedIn Leads Scraper — the same scored-leads approach for LinkedIn profiles
• Bulk Email Verifier — verify every email before you launch a campaign
• Email Pattern Finder — guess-and-verify work emails when the bio has none

Support: found a bug or need a feature? Open an Issue on this actor's Issues tab — typical response within 1 business day.