Lead List Deduplicator & Normalizer - CRM-Ready Leads, Not Messy Dumps

Turn messy scraped B2B lead lists into canonical, CRM-ready company and contact records, not duplicate-filled dumps.

This Actor takes inline JSON records or an Apify dataset ID, normalizes common lead fields, groups duplicates, and outputs one canonical row per lead/company cluster with confidence scores, match reasons, source row IDs, and warnings.

Use it after Google Maps scrapers, directory scrapers, website contact scrapers, exhibitor-list scrapers, Apollo-style lead exports, or any workflow where several sources produce overlapping leads.

Launch Pricing

Launch pricing is currently $0.05 per 1,000 cleaned rows.

The launch version supports up to 5,000 input records per run. Larger datasets can be processed in batches while high-volume matching is optimized.

Quick Preview

Messy input	Clean output
Acme Inc, ACME LLC, https://www.acme.com, sales@acme.com	one canonical acme.com cluster
duplicate domains, emails, phones, or similar company names	clusterId, clusterSize, mergeConfidence, matchReasons
records from multiple Apify datasets or CSV/JSON imports	CRM-ready rows with normalized company, domain, email, and phone

Why Use This Actor

• Merge overlapping exports from multiple scrapers.
• Remove duplicate companies, domains, emails, and phone numbers before CRM import.
• Normalize company names, domains, emails, and phones.
• Keep source row IDs so every merge is auditable.
• Get confidence scores and match reasons instead of a black-box cleanup.
• Use deterministic rules first, so costs stay predictable.
• No browser, proxies, or external enrichment APIs.

Common Use Cases

• Merge lead lists from several Apify scrapers.
• Clean a CSV before importing it into HubSpot, Pipedrive, Salesforce, Clay, Instantly, Smartlead, or Airtable.
• Remove duplicate outreach targets before spending credits on email verification or enrichment.
• Create a canonical company list from multiple scraped directories.
• Audit which rows were merged and why.

Input Example

{
  "dedupMode": "balanced",
  "records": [
    {
      "id": "1",
      "company": "Acme Inc",
      "website": "https://www.acme.com",
      "email": "sales@acme.com"
    },
    {
      "id": "2",
      "companyName": "ACME LLC",
      "domain": "acme.com",
      "phone": "(415) 555-2671"
    }
  ]
}

You can also provide an Apify datasetId instead of inline records.

If no input is provided, the Actor runs with sample records so you can test the output immediately.

Output Example

{
  "recordType": "canonicalLead",
  "clusterId": "cluster_0001",
  "clusterSize": 2,
  "mergeDecision": "merged",
  "mergeConfidence": 0.9,
  "matchReasons": ["same_domain", "similar_company"],
  "sourceRowIds": ["1", "2"],
  "canonicalCompanyName": "Acme Inc",
  "normalizedCompanyName": "acme",
  "normalizedDomain": "acme.com",
  "normalizedEmail": "sales@acme.com",
  "normalizedPhone": "4155552671",
  "warnings": []
}

Deduplication Modes

Mode	Best for	Behavior
conservative	Avoiding false merges	Requires exact email, phone, or domain match
balanced	Most lead lists	Uses exact email/phone/domain plus strong company-name similarity
aggressive	Very messy lists	Uses looser company-name matching; review warnings before importing

Dataset Views

View	Best for
Canonical	CRM-ready rows after deduplication
Duplicate clusters	Auditing source rows, match reasons, and confidence

Output Fields

Field	Meaning
clusterId	Stable cluster identifier for the canonical row
clusterSize	Number of source rows merged into the canonical row
mergeDecision	unique, merged, or ambiguous
mergeConfidence	Confidence score from 0 to 1
matchReasons	Why records matched, such as same_email, same_domain, or similar_company
sourceRowIds	Original row IDs or indexes used in the merge
normalizedDomain	Clean domain value such as acme.com
warnings	Flags such as low_confidence_merge or missing_domain_or_email

Limits and Caveats

• This MVP uses deterministic rules and fuzzy string similarity, not paid LLM adjudication.
• Review ambiguous rows before importing them into a CRM.
• Email/phone/domain normalization is conservative and may not cover every country-specific format.
• The Actor does not scrape or enrich missing contact data; it cleans the records you provide.
• It does not verify email deliverability or MX records in the first version.
• Current runs are capped at 5,000 input records while the deduplication engine is optimized for larger files.

Pricing

This Actor is designed for pay-per-row pricing. You pay for cleaned output rows plus Apify platform usage.

Because it does not launch a browser or call external enrichment APIs, runs should stay inexpensive for bulk cleanup.