Superclean Places

Clean messy location data from lead exports, CRM records, and web scraping.

What does Superclean Places do?

This Actor normalizes location strings into consistent, standardized formats.

• Standardizes abbreviations — "NYC" becomes "New York", "Calif" becomes "CA"
• Fixes casing — "NEW YORK, NY" becomes "New York, NY"
• Parses combined fields — "San Francisco, California, USA" extracts city, state, country
• Normalizes countries — "USA", "United States", "America" all become "US"
• Handles Canadian provinces — "Ontario" becomes "ON", "British Columbia" becomes "BC"

Why clean location data?

Your lead data comes from many sources with inconsistent formats:

• "San Francisco, CA"
• "san francisco california"
• "SF, Calif., USA"
• "SAN FRANCISCO, CALIFORNIA, UNITED STATES"

Clean data means better:

• Segmentation — Group leads by metro area or region
• Routing — Assign leads to the right sales territory
• Personalization — Reference locations correctly in outreach
• Deduplication — Match records across different sources

How to use Superclean Places

1. Paste your location strings into the input field
2. Select your output style (Short, Long, or Components)
3. Click Start and download your cleaned results

Input example

{
  "items": [
    "San Francisco, CA",
    "NYC",
    "new york city, new york, usa",
    "LA, California",
    "London, UK",
    "toronto ontario canada"
  ],
  "style": "short"
}

Output example

[
  {
    "id": 1,
    "input": "San Francisco, CA",
    "output": "San Francisco, CA",
    "city": "San Francisco",
    "stateOrProvince": "CA",
    "country": "US",
    "confidence": 0.85
  },
  {
    "id": 2,
    "input": "NYC",
    "output": "New York",
    "city": "New York",
    "stateOrProvince": null,
    "country": null,
    "confidence": 0.65
  },
  {
    "id": 3,
    "input": "new york city, new york, usa",
    "output": "New York, NY",
    "city": "New York",
    "stateOrProvince": "NY",
    "country": "US",
    "confidence": 0.85
  }
]

Output styles

Style	Best for	Example Input	Example Output
Short	CRM fields, compact display	San Francisco, California	San Francisco, CA
Long	Full formatting, letters	SF, CA	San Francisco, California, United States
Components	Programmatic use, parsing	NYC, NY	{"city":"New York","state":"NY","country":"US"}

Short (default)

Uses standard abbreviations. Omits country when it can be inferred from state.

• "San Francisco, California, USA" → "San Francisco, CA"
• "Toronto, Ontario, Canada" → "Toronto, ON"
• "London, United Kingdom" → "London, GB"

Long

Uses full names for all components.

• "SF, CA" → "San Francisco, California, United States"
• "NYC" → "New York"
• "Toronto, ON" → "Toronto, Ontario, Canada"

Components

Returns structured JSON with each component parsed separately. Useful for programmatic processing.

What gets cleaned

City abbreviations

• NYC, N.Y.C. → New York
• LA, L.A. → Los Angeles
• SF, S.F. → San Francisco
• Philly → Philadelphia
• Vegas → Las Vegas

State variations

• California, Calif, Calif., Cal → CA
• Massachusetts, Mass, Mass. → MA
• Texas, Tex, Tex. → TX
• Pennsylvania, Penn, Penna → PA

Country variations

• USA, U.S.A., United States, America → US
• UK, U.K., United Kingdom, Britain, England → GB
• Canada, Can → CA

Casing

• ALL CAPS → Title Case
• all lowercase → Title Case

Pricing

Items	Cost
1,000	$0.50
10,000	$5.00
100,000	$50.00

This Actor uses rule-based normalization with no external API calls, keeping costs low.

Limitations

• Focuses on US, Canada, and major international locations
• Does not validate addresses against postal databases
• Does not geocode or return coordinates
• For full address validation, consider integrating with Smarty or similar services

Confidence scores

Each result includes a confidence score from 0 to 1:

• 0.8+ — High confidence, recognized location with state/country
• 0.6-0.8 — Moderate confidence, partial match or city-only
• < 0.6 — Low confidence, manual review suggested

Confidence is based on how many components (city, state, country) were successfully parsed.

Tips for best results

• Include state when possible — "Portland, OR" is clearer than just "Portland"
• Check confidence scores — Items with confidence < 0.6 may need manual review
• Use Components style — When you need to work with city/state/country separately

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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 Person Names — Clean person names for cold email personalization.
• Superclean Job Titles — Normalize job titles for lead scoring and personalization.
• 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.