Local Business Schema is a type of structured data markup used to help search engines understand key information about a local business. It provides explicit details such as business name, address, phone number, opening hours, and service area in a machine readable format. This markup helps search engines interpret business data accurately rather than inferring it from page content alone.
By implementing Local Business Schema, businesses improve the consistency and reliability of their online information. This is especially important for local search, where accuracy of location and contact details directly affects visibility. The schema supports search engines in matching businesses to relevant local queries.
Local Business Schema does not guarantee enhanced results, but it strengthens eligibility for rich features. It improves clarity, reduces ambiguity, and supports trust signals that influence local rankings and user confidence.
Advanced
Local Business Schema is implemented using structured data formats such as JSON LD and must align precisely with on page content. Inconsistencies between schema data and visible information can reduce effectiveness or trigger trust issues. Validation and maintenance are critical as business details change.
Advanced implementations may include additional properties such as price range, accepted payments, geo coordinates, same as links, and business attributes. Correct use supports enhanced local understanding, improves data aggregation across platforms, and reinforces entity recognition within search systems.
Relevance
- Improves accuracy of local business information.
- Supports local search visibility and trust.
- Reinforces consistency across search platforms.
- Enhances eligibility for rich search features.
- Strengthens entity recognition signals.
Applications
- Physical retail stores.
- Service area businesses.
- Professional service providers.
- Hospitality and food venues.
- Multi location business websites.
Metrics
- Local search impressions and clicks.
- Accuracy of business data in search results.
- Rich result eligibility indicators.
- Click through rate on local listings.
- Local ranking stability over time.
Issues
- Incorrect data causes trust loss.
- Inconsistencies weaken schema effectiveness.
- Outdated hours or addresses mislead users.
- Missing properties reduce clarity.
- Lack of validation introduces errors.
Example
A local trades business added structured markup to its contact page with accurate address and service details. Search engines displayed clearer local information, click through rates increased, and incorrect third party listings were reduced over time.