Superclean Person Names
Pricing
from $0.70 / 1,000 results
Superclean Person Names
Clean messy person names for cold email and CRM. Extracts first names for personalization, fixes ALL CAPS, handles McDonald/O'Brien/van der Berg correctly, strips titles (Dr.) and credentials (PhD). Three styles: first name only, casual, or formal.
Pricing
from $0.70 / 1,000 results
Rating
0.0
(0)
Developer

Superlative
Actor stats
2
Bookmarked
4
Total users
2
Monthly active users
5 minutes ago
Last modified
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Clean messy person names for cold email personalization, CRM systems, and lead lists.
What does Superclean Person Names do?
This Actor uses AI to intelligently clean and normalize person names from lead lists, LinkedIn exports, and CRM exports.
- Fixes ALL CAPS — "JOHN SMITH" becomes "John Smith"
- Extracts first names — "Dr. John Michael Smith Jr., PhD" becomes "John" for cold emails
- Handles special cases — McDonald, O'Brien, van der Berg formatted correctly
- Strips unwanted content — Removes titles, credentials, emails, phone numbers
- Detects non-English — Flags names in CJK, Arabic, Cyrillic for review
Why clean person names?
Your lead lists show the same person different ways:
- "JOHN SMITH"
- "Dr. John Smith, PhD"
- "john smith"
- "Smith, John"
- "MR. JAMES WILSON JR., MBA"
Clean data means better:
- Cold email personalization — "Hi John," instead of "Hi DR. JOHN MICHAEL SMITH JR.,"
- CRM consistency — Proper formatting across all records
- Segmentation — Accurate name-based filtering and deduplication
How to use Superclean Person Names
- Paste your person names into the input field
- Select your output style (First, Casual, or Formal)
- Click Start and download your cleaned results
Input example
{"items": ["JOHN SMITH","dr. mary jane o'brien, phd","McDonald, Ronald","johannes van der berg","MR. JAMES WILSON JR."],"style": "casual"}
Output example
[{"id": 1,"input": "JOHN SMITH","output": "John Smith","confidence": 0.95},{"id": 2,"input": "dr. mary jane o'brien, phd","output": "Mary Jane O'Brien","confidence": 0.92},{"id": 3,"input": "McDonald, Ronald","output": "Ronald McDonald","confidence": 0.90},{"id": 4,"input": "johannes van der berg","output": "Johannes van der Berg","confidence": 0.88},{"id": 5,"input": "MR. JAMES WILSON JR.","output": "James Wilson Jr.","confidence": 0.93}]
Output styles
| Style | Best for | Before | After |
|---|---|---|---|
| First | Cold email | Dr. John Michael Smith Jr. | John |
| Casual | CRM, general | DR. JOHN SMITH JR., PhD | John Smith Jr. |
| Formal | Contracts | dr john smith jr phd | Dr. John Smith Jr., Ph.D. |
First (for cold email)
Just the first name. Perfect for cold email personalization.
- "Dr. John Michael Smith Jr., PhD" → "John"
- "Mary-Jane O'Brien" → "Mary-Jane"
- "van der Berg, Johannes" → "Johannes"
Casual (default)
Full name without titles or credentials. Keeps generational suffixes.
- "DR. JOHN SMITH JR., PhD" → "John Smith Jr."
- "mary-jane o'brien" → "Mary-Jane O'Brien"
- "JOHANNES VAN DER BERG" → "Johannes van der Berg"
Formal
Complete professional formatting with all components.
- "dr john smith jr phd" → "Dr. John Smith Jr., Ph.D."
- "MARY O'BRIEN MD" → "Mary O'Brien, M.D."
- "prof johannes van der berg" → "Prof. Johannes van der Berg"
Use cases
Cold email personalization
Extract first names to personalize your outreach. "Hi John," sounds better than "Hi DR. JOHN MICHAEL SMITH JR.,"
CRM data cleanup
Standardize person names across your HubSpot, Salesforce, or Pipedrive records. Stop seeing the same person formatted 15 different ways.
Lead enrichment
Clean names from Apollo, ZoomInfo, or LinkedIn exports before importing into your outreach tools.
Special capitalization
The Actor correctly handles:
- Scottish/Irish names — McDonald, MacArthur, O'Brien, O'Neill
- Dutch/German names — van der Berg, von Braun (particles lowercase)
- Italian names — da Vinci, di Caprio
- Hyphenated names — Mary-Jane, Jean-Pierre, Saint-Martin
Integrations
Apify API
Call directly via the Apify API for programmatic access.
Clay
Use the Apify integration in Clay to clean person names as part of your enrichment workflow.
Make / Zapier / n8n
Connect via the Apify app to automate person name cleaning in your workflows.
Pricing
| Items | Cost |
|---|---|
| 1,000 | $0.70 |
| 10,000 | $7.00 |
| 100,000 | $70.00 |
AI model costs
This Actor uses the Apify OpenRouter Actor to access AI models. AI token costs are billed to your Apify account at OpenRouter rates. Typical LLM costs are ~$0.05 per 1,000 names using the default openrouter/auto model.
Tips for best results
- Batch your requests — Process names in bulk for efficiency
- Check confidence scores — Items with confidence < 0.7 may need manual review
- Choose the right style — Use "First" for cold email, "Casual" for CRM, "Formal" for contracts
Confidence scores
Each result includes a confidence score from 0 to 1:
- 0.9+ — High confidence, no review needed
- 0.7-0.9 — Moderate confidence, spot check recommended
- < 0.7 — Low confidence, manual review suggested
Non-English names automatically receive confidence 0 and should be reviewed.
More from Superlative
- Superclean Company Names — Clean messy company names for cold emails and CRM.
- Superclean Product Names — Clean product names from e-commerce data.
- Superclean Job Titles — Normalize job titles for lead scoring and personalization.
- Superclean Places — Normalize location data from lead exports.
- Superclean URLs — Clean and normalize URLs from lead data.
- DNS Lookup — Query DNS records for any domain.
- HTTP API — Make HTTP requests from your workflows.
Built by Superlative — Clean data in. Better emails out.