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Lead Intelligence Scorer

Clean, deduplicate, score, and prepare raw B2B leads from Apify datasets for CRM import and outreach workflows.

This Actor is built for one specific job: take messy output from lead-generation scrapers and turn it into a ranked, explainable, CRM-ready list. It does not scrape websites. It works as a post-processing step after Google Maps, event, supplier, directory, or trade-data scrapers.

What does Lead Intelligence Scorer do?

Lead generation workflows often produce noisy records:

• duplicate companies
• missing emails or phone numbers
• inconsistent company, website, and location fields
• mixed-fit leads in the same dataset
• raw exports that are not ready for a CRM or outreach sequence

This Actor cleans that data and adds a simple lead-prioritization layer.

It outputs:

• normalized company, domain, email, phone, location, and category fields
• deduplication by email, domain, or company + location
• leadScore from 0 to 100
• score band: Excellent, Strong, Moderate, or Weak
• plain-English scoring reasons
• missing fields to enrich next
• suggested next action
• outreach angle
• original source record for traceability

Common use cases

• Clean results from Apify lead scrapers before importing them into a CRM.
• Prioritize a large raw lead list before outreach.
• Remove duplicate companies across multiple scraper runs.
• Find which leads need enrichment before a campaign.
• Chain scraper output into n8n, Make, Zapier, HubSpot, Airtable, or Google Sheets.
• Build a repeatable scrape -> clean -> score -> export lead pipeline.

Input options

Use either:

• records: paste a JSON array of raw lead records.
• sourceDatasetId: select an existing Apify Dataset ID.

You can also describe your ICP in plain language:

{
"records":[
{
"company":"Northstar HVAC Supply",
"website":"https://northstarhvacsupply.example",
"email":"sales@northstarhvacsupply.example",
"phone":"+1 555 010 2210",
"city":"Dallas",
"state":"TX",
"category":"Industrial supplier",
"description":"Commercial HVAC supplier serving contractors and property managers"
}
],
"icpDescription":"Industrial suppliers, HVAC distributors, manufacturers, logistics companies, and B2B service providers with a website and reachable sales contact.",
"mode":"industrial_supplier",
"dedupe":true,
"minimumScore":0
}

Scoring modes

Choose the mode that best matches your dataset:

• generic_b2b: general B2B records
• local_business: local service businesses and appointment-driven companies
• industrial_supplier: manufacturers, distributors, suppliers, logistics, RFQ, wholesale
• event_exhibitor: events, conferences, expos, exhibitors, sponsors

Output example

{
"leadScore":100,
"band":"Excellent",
"companyName":"Acme Industrial Supply",
"domain":"acme-industrial.example",
"email":"sales@acme-industrial.example",
"phone":"+1 555 012 1000",
"location":"Houston, TX",
"category":"Industrial supplier",
"reasons":[
"Lead has enough contact and firmographic data for prioritization.",
"Matches ICP terms: industrial, hvac, wholesale, sales.",
"Matches industrial supplier signals: supplier, industrial, wholesale, distributor.",
"Has a direct contact channel."
],
"missingFields":[],
"suggestedNextAction":"Import to CRM and start priority outreach.",
"outreachAngle":"Industrial/supplier lead. Open with sourcing, RFQ, distribution, or trade-intelligence relevance for Acme Industrial Supply.",
"dedupeKey":"9ff66ab7b2f7ad170115596449e2daa2ff4f4293"
}

What this Actor is not

• It is not a scraper.
• It does not find emails by itself.
• It does not send outreach.
• It does not use paid AI APIs by default.

This makes it cheaper and more stable as a workflow step. Use it after a scraper and before CRM import, enrichment, or outreach.

Recommended workflow

1. Run your preferred lead scraper.
2. Copy the output Dataset ID.
3. Run this Actor with your ICP description.
4. Export the scored dataset as CSV, JSON, or Excel.
5. Import only Excellent and Strong leads into your CRM or outreach workflow.

Why use this Actor?

Many lead scrapers focus on collecting data. This Actor focuses on making collected data usable.

It is useful when you already have leads, but you do not yet know which records are complete, duplicated, relevant, or worth contacting first.