Clean Categories in Local Business Data

✓ Tested Works with CSV, Excel, Google Sheets → JSON-LD Schema

By dataclean.to team · 2026-02-05

Local business directories, chambers of commerce, and city data portals manage listings where business types, neighborhood assignments, and service categories are labeled inconsistently. "Coffee Shop", "Cafe", "Café", "Coffee House", and "Coffeeshop" all describe the same business type. dataclean.to normalizes these labels so local directories are browseable and business census data is accurate.

The Problem

Local business data is collected from registrations, permit applications, Google Business Profile exports, and user submissions. Each source uses different terminology for business type and service area. Without standardization, directory browse pages show fragmented categories, local economic reports by industry are unreliable, and business search returns incomplete results. Schema.org LocalBusiness type for structured local business data

How to Fix It

Upload your local business data

Export your business directory, chamber membership list, or city permit database to CSV. Include columns for business type, industry, neighborhood, service area, or any categorical classifications.

Select category columns

dataclean.to identifies categorical columns in your local business data. Choose business type, industry, neighborhood, and service type columns for normalization.

Review business type clusters

The tool groups similar entries. "Hair Salon", "Beauty Salon", "Hairdresser", "Hair Stylist", and "Salon" would be clustered with a suggested standard label.

Standardize neighborhood and service labels

Normalize neighborhood names ("Downtown", "Centre City", "CBD", "City Center") and service descriptions ("Dine-In", "Dine In", "Sit-Down", "In-House Dining") to consistent terms.

Export cleaned business data

Download the standardized CSV for import into your directory platform, economic development reports, or local search application.

Frequently Asked Questions

Can it handle businesses with multiple categories?

Yes. Businesses assigned multiple categories in a single field have each category normalized individually. A listing tagged as "Restaurant, Bar, Live Music" would have each label cleaned to standard terms.

Does it work with Google Business Profile categories?

Google Business Profile category exports contain freeform and structured category names. The text labels can be normalized, and you can map them to your directory's own taxonomy.

Can I clean both business type and neighborhood data?

Business types and geographic categories are processed independently. Both can be normalized in the same upload, each with its own grouping logic.

Example: Input → Output

name	address	city	phone	website
City Plumbing Co	789 Elm St	Denver CO	(720) 555-0200	cityplumbing.com
city plumbing co	789 elm st	denver	co	(720)555-0200	www.cityplumbing.com

Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.

{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "City Plumbing Co",
  "address": {"@type": "PostalAddress", "streetAddress": "789 Elm St", "addressLocality": "Denver", "addressRegion": "CO"},
  "telephone": "+17205550200",
  "url": "https://cityplumbing.com"
}

💡 How it works: LocalBusiness schema helps your listing appear in Google Maps and local search with structured contact info.

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