Skill Store 33

Finding Real Estate Professionals On Twitter

Finds real estate agents, brokers, property investors, and real estate professionals on Twitter/X…

by apidojo-io · Apache-2.0

The skill

Finds real estate agents, brokers, property investors, and real estate professionals on Twitter/X using apidojo's Twitter User Scraper on Apify. Triggers when the user asks to: find real estate agents on Twitter, discover property professionals on X for outreach, build a list of realtors active on Twitter, find real estate investors or brokers on X, prospect real estate professionals via their Twitter bios, identify mortgage brokers or property managers on Twitter, or compile a real estate professional contact list from Twitter. Returns username, bio, follower count, verification status, location, and website per user. Ideal for PropTech SaaS vendors, mortgage product teams, and B2B service providers targeting real estate professionals.

Finding Real Estate Professionals On Twitter

Inputs

Parameter Type Required Default Notes
startUrls array Optional [] Twitter profile or tweet URLs
twitterHandles array Optional [] Twitter usernames (without @)
twitterUserIds array Optional [] Twitter user IDs
getFollowers boolean Optional false Extract follower lists
getFollowing boolean Optional false Extract following lists
getRetweeters boolean Optional false Extract retweeters of a tweet URL
includeUnavailableUsers boolean Optional false Include unavailable/suspended users
maxItems number Optional Unlimited Maximum users to return
customMapFunction string Optional — JavaScript function to transform each output object

How to Run

Using run_actor.js (recommended)

# Quick answer (table)
node scripts/run_actor.js --actor "apidojo~twitter-user-scraper" --input '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}'

# Save as CSV
node scripts/run_actor.js --actor "apidojo~twitter-user-scraper" --input '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}' --output results.csv --format csv

# Save as JSON
node scripts/run_actor.js --actor "apidojo~twitter-user-scraper" --input '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}' --output results.json --format json

REST API fallback

curl -X POST "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["realtor", "real estate agent"], "maxItems": 100}'

If Apify MCP is available: Use the Apify MCP call_actor tool with actor apidojo~twitter-user-scraper and the input above.

Scoring & Ranking

Score each user by:

  • followers → normalized 0-1 (cap at 50K), weight 0.30
  • bio_match_score (contains: realtor, broker, real estate, property, agent, MLS) → 0 or 1, weight 0.40
  • has_website → 0 or 1, weight 0.30
score = 0.30 * min(followers / 50000, 1.0) + 0.40 * int(bio_match) + 0.30 * int(has_website)

Classification

Score Tier Label
≥ 0.70 A PRIME_OUTREACH
0.40–0.69 B HOT_CANDIDATE
< 0.40 C LOW_PRIORITY

Edge Cases

  • Generic bio keywords: "house" or "home" match too broadly. Use "realtor", "real estate agent", "MLS".
  • Personal accounts mixed in: Filter by followers > 200 and has website link.
  • Bot accounts: Unusually high following-to-follower ratio — filter out.
  • Keyword not in bio: Twitter user search matches bio text — results may vary if bio is non-standard.
  • International agents: Use country-specific terms (e.g., "estate agent" for UK).

Use this skill

Connect your agent to the Skill Store MCP server and ask for it by ref: apidojo-io/finding-real-estate-professionals-on-twitter-47783560373.

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Details

Publisher
apidojo-io
Category
Business › Sales & CRM
License
Apache-2.0
Updated
2026-05-14

References

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