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Create LocalBusiness Schema from Auto Repair Shop Data

✓ Tested Works with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-05

Auto repair shops need LocalBusiness schema markup with AutomotiveBusiness or AutoRepair subtypes to appear in local search results, Google Maps, and knowledge panels. Converting shop information from spreadsheets into JSON-LD format enables structured representation of addresses, hours, services, payment methods, and ratings for local search visibility.

The Problem

Auto repair businesses maintain location information across directories without implementing unified LocalBusiness schema markup, limiting knowledge graph inclusion and local search features. Multi-location operations need consistent schema across franchise or chain shops. Manual schema creation for business hours, service areas, payment methods, and aggregate ratings is complex. AutoRepair - Schema.org

How to Fix It

1
Gather Location Business Data
Create spreadsheet with shop name, address (street, city, state, zip), telephone, email, url, latitude, longitude, openingHours (weekly schedule), priceRange ($-$$$$), paymentAccepted, image (shop photo), and logo URLs. Include service specializations.
2
Upload Shop Location Data
Import your auto repair location spreadsheet. The platform detects address components, phone number formats, geographic coordinates, day/time patterns for hours, and URL formats for website and social profiles.
3
Map to LocalBusiness Schema
Assign columns to LocalBusiness properties with @type AutoRepair: name, address (PostalAddress), telephone, geo (GeoCoordinates), url, openingHoursSpecification, priceRange, paymentAccepted, image, logo, aggregateRating, and areaServed. Include sameAs for verification.
4
Generate LocalBusiness JSON-LD
Export validated LocalBusiness schema for each shop location. The system creates nested address and geo coordinate objects, properly formatted opening hours specifications, and complete business identity markup.
5
Implement on Location Pages
Add LocalBusiness schema to homepage (single location) or individual location pages (multi-shop). Test markup with Google Rich Results Test for local business feature eligibility. Monitor for knowledge panel and map display.

Frequently Asked Questions

What is the difference between LocalBusiness and AutomotiveBusiness?
LocalBusiness is the parent type for any business with physical location. AutomotiveBusiness (subtype) specifies automotive industry services. AutoRepair (subtype of AutomotiveBusiness) is most specific for repair shops. Use the most specific applicable type: AutoRepair for repair-only, AutomotiveBusiness for shops with sales.
How do I represent multiple shop locations?
Create separate LocalBusiness schema instances for each location with unique addresses, phone numbers, and hours. Use Organization schema at corporate level with department or location properties referencing individual LocalBusiness objects. Alternatively, create location-specific pages each with own LocalBusiness markup.
What openingHours format does Google require?
Use openingHoursSpecification with dayOfWeek (Monday, Tuesday), opens (09:00), and closes (17:00) in 24-hour format. Create separate specification objects for days with different hours. Include validFrom and validThrough for seasonal hours. This enables Google to display accurate operating hours.

Example: Input → Output

nameskupricebrandrating
Wireless Headphones ProWHP-001$89.99SoundTech4.5
wireless headphones proWHP00189.99soundtech4.5/5

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

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Wireless Headphones Pro",
  "sku": "WHP-001",
  "offers": {"@type": "Offer", "price": "89.99", "priceCurrency": "USD"},
  "brand": {"@type": "Brand", "name": "SoundTech"},
  "aggregateRating": {"@type": "AggregateRating", "ratingValue": "4.5"}
}
💡 How it works: Product schema enables rich results with price, availability, and star ratings in Google Shopping.

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