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$25.00/month + usage

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Twitter(X) Profile Bio ICP Classifier - Bio Keywords Extractor

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Developed by

LeadGen Labs

Classify Twitter (X) profiles by using bio keyword extraction. This tool scrapes public Twitter bios and intelligently extracts relevant keywords to help you sort users into Ideal Customer Profile (ICP) categories — like Founders, SaaS Marketers, Investors, Coaches, or Crypto Traders.

0.0 (0)

Pricing

$25.00/month + usage

Total users

Monthly users

Runs succeeded

>99%

Last modified

2 days ago

Automation

Lead generation

Social media

Classify Twitter (X) profiles by analyzing their bios using keyword matching. This tool is built to help you segment, analyze, or filter users based on what they write in their bios — such as roles, interests, industries, or intent. This tool complements:

Twitter(X) Community Members Profile Extractor

Twitter(X) Profile Details Scraper

Introduction

The Twitter(X) Profile Bio ICP Classifier - Bio Keywords Extractor is a powerful tool that:

Parses bios from Twitter/X profiles
Matches them against customizable keyword groups (e.g., SaaS, Developers, Investors)
Outputs structured results showing which keywords were matched per profile

Perfect for audience segmentation, influencer research, marketing intelligence, and building ideal customer profiles (ICPs).

Use Cases

Audience Segmentation: Segment users into categories like SaaS Founders, Developers, Investors, etc.
Lead Qualification: Identify potential leads or partners based on bio content.
Marketing Intelligence: Understand how people in your niche describe themselves.
Community Management: Filter and tag members of a Twitter community based on their roles.

How to Use

Provide a dataset: The dataset must be a URL that returns Twitter profile data in JSON format, with fields like name, bio, followers_count, following_count, and profile_url.
Define your keywords: Supply a dictionary where each label/category maps to a list of keywords.
Run the classifier: The tool will scan each profile bio, match it against the keyword groups, and assign matched keywords. Profiles with no matches will be labeled as "Unclassified".

Input Sample

{
  "dataset_url": "https://api.apify.com/v2/datasets/fdcBNhlmShbG0dwNh/items?clean=true&format=json",
  "keywords": {
    "SaaS": [
      "saas",
      "startup",
      "founder",
      "bootstrap"
    ],
    "Marketing": [
      "seo",
      "growth",
      "marketing",
      "branding"
    ],
    "Investors": [
      "vc",
      "angel",
      "investor",
      "portfolio"
    ],
    "Developers": [
      "developer",
      "engineer",
      "fullstack",
      "frontend",
      "backend"
    ]
  }
}

Output Sample

{
  "name": "Spencer Walden",
  "bio": "I build things: \nhttps://t.co/wv1GBRyvZu\nhttps://t.co/LYXzFm8V8d\nhttps://t.co/tHrNJtV4Yv\nhttps://t.co/6rMGzMmD5w\n\nBuilding software to help founders @AntlerGlobal\n\n#buildinpublic #adhd",
  "followers_count": 795,
  "following_count": 378,
  "profile_url": "https://x.com/Swaldy",
  "matched_keywords": [
    "founder"
  ]
}

{
  "name": "Yash Desai 🚀 Shipr.Dev",
  "bio": "Founder @ShiprDev | Simplifying SaaS Development",
  "followers_count": 2201,
  "following_count": 2139,
  "profile_url": "https://x.com/yhdesai",
  "matched_keywords": [
    "saas",
    "founder"
  ]
}

Feature Requests?

Raise an Issue on the actor page for feature request or contact me directly for custom solution(check my profile page)

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