Superclean Job Titles

Transform messy job titles into clean, consistent formats for CRM systems, HR databases, and analytics.

What does Superclean Job Titles do?

This Actor uses AI to intelligently normalize job titles from lead lists, LinkedIn exports, and HR systems.

• Standardizes abbreviations — "Sr. Software Eng." becomes "Senior Software Engineer"
• Removes vanity titles — "Code Ninja", "Growth Hacker", "DevOps Guru" cleaned up
• Strips department tags — "Engineer - Platform Team" becomes "Engineer"
• Fixes ALL CAPS — "MARKETING MANAGER" becomes "Marketing Manager"
• Handles international variations — "Programme Manager" becomes "Program Manager"

Why clean job titles?

Your CRM shows the same role 15 different ways:

• "Sr. Software Eng."
• "Senior Software Engineer"
• "Software Engineer, Senior"
• "Sr Software Developer"
• "Snr. SWE"

Clean data means better:

• Lead scoring and routing — Properly identify decision-makers
• Analytics and reporting — Accurate role-based segmentation
• Personalization in outreach — "Hi Sarah, as a Senior Engineer..." instead of "Hi Sarah, as a Sr. Software Eng. - Platform Team..."

How to use Superclean Job Titles

1. Paste your job titles into the input field
2. Select your output style (Standardized, Abbreviated, or Simple)
3. Click Start and download your cleaned results

Input example

{
  "items": [
    "Sr. Software Eng.",
    "VP of Engineering",
    "junior developer",
    "MARKETING MANAGER - EAST COAST TEAM",
    "Full Stack Ninja"
  ],
  "style": "standardized"
}

Output example

[
  {
    "id": 1,
    "input": "Sr. Software Eng.",
    "output": "Senior Software Engineer",
    "confidence": 0.95
  },
  {
    "id": 2,
    "input": "VP of Engineering",
    "output": "Vice President of Engineering",
    "confidence": 0.92
  },
  {
    "id": 3,
    "input": "junior developer",
    "output": "Junior Developer",
    "confidence": 0.98
  },
  {
    "id": 4,
    "input": "MARKETING MANAGER - EAST COAST TEAM",
    "output": "Marketing Manager",
    "confidence": 0.90
  },
  {
    "id": 5,
    "input": "Full Stack Ninja",
    "output": "Full Stack Developer",
    "confidence": 0.88
  }
]

Output styles

Style	Best for	Before	After
Standardized	CRM, LinkedIn, HR systems	Sr. Software Eng.	Senior Software Engineer
Abbreviated	Spreadsheets, reports	Senior Software Engineer	Sr. Software Eng.
Simple	Analytics, categorization	VP of Engineering	Engineering

Standardized (default)

Full, professional job titles. Expands all abbreviations and uses industry-standard naming.

• "Sr. Software Eng." → "Senior Software Engineer"
• "VP, Product" → "VP of Product"
• "Mktg Mgr" → "Marketing Manager"

Abbreviated

Compact titles that fit in spreadsheet columns and constrained displays.

• "Senior Software Engineer" → "Sr. Software Eng."
• "Vice President of Engineering" → "VP Eng."
• "Chief Technology Officer" → "CTO"

Simple

Core job function only. Strips all seniority and level indicators. Perfect for role-based analytics and categorization.

• "Senior Software Engineer" → "Software Engineer"
• "VP of Engineering" → "Engineering"
• "Lead Product Designer" → "Product Designer"

Use cases

CRM data cleanup

Standardize job titles across your HubSpot, Salesforce, or Pipedrive records. Stop seeing the same role 15 different ways.

Lead enrichment

Clean job titles from Apollo, ZoomInfo, or LinkedIn exports before importing into your outreach tools.

HR system standardization

Normalize employee titles for reporting, org charts, and compensation analysis.

Analytics and segmentation

Use "Simple" style to categorize leads by function (Engineering, Sales, Marketing) regardless of seniority level.

Integrations

Apify API

Call directly via the Apify API for programmatic access.

Clay

Use the Apify integration in Clay to clean job titles as part of your enrichment workflow.

Make / Zapier / n8n

Connect via the Apify app to automate job title 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 job titles using the default openrouter/auto model.

Tips for best results

• Batch your requests — Process titles in bulk for efficiency
• Check confidence scores — Items with confidence < 0.7 may need manual review
• Choose the right style — Use "Standardized" for CRM, "Abbreviated" for spreadsheets, "Simple" for analytics

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 titles automatically receive confidence 0 and should be reviewed.

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Built by Superlative — Clean data in. Better emails out.