Local Schema Markup: Structured Data for Local Search

Anyone operating a local business in Austria is found almost exclusively via Google. The market leader holds81.87% market share among search engines(as of May 2026), followed by Bing with 9.01% and DuckDuckGo with 2.75%. With8.69 million internet users and a penetration of 95.3%organic and local search decisively determines whether a practice, trade business, or restaurant gains customers.

For Google and increasingly AI systems to reliably capture the key data of a local business, plain text alone is insufficient. Local Schema Markup delivers this data in machine-readable form. Despite its high utility, adoption is low: According to Web Almanac 2024,LocalBusiness markup appears on only 3.97% of mobile pagesmaking it the third most common JSON-LD type but far from standard practice. Therein lies a real differentiation opportunity. This article shows how LocalBusiness Schema is structured, how to implement it correctly for an Austrian business, and which errors are the most common causes of missing rich results.

Why Local Schema Markup matters for local visibility

Structured data are code annotations that explicitly describe a page's content rather than merely displaying it. Google recommends the JSON-LD format, a data object embedded in a<script>tag. Web Almanac 2024 confirms the trend:JSON-LD has grown from 34% in 2022 to 41% of all pages in 2024and is considered Google's preferred and fastest-growing format.

For local businesses, LocalBusiness Schema serves three functions. It makes location, opening hours, and contact data clearly evaluable, it can enable rich results such as star ratings in search, and it provides AI systems like Google AI Overviews or Perplexity with structured facts for their answers. Unlike a Google Business Profile that you maintain on a platform, the markup belongs to your own website and strengthens its authority as the primary data source.

Managing expectations is important: Schema is not a direct ranking factor. It does not improve position but rather comprehensibility and presentation. Value emerges indirectly through better data quality, higher click-through rates via rich results, and consistent signals to search and AI systems.

LocalBusiness Schema in relation to Organization and WebSite

Three Schema types are frequently confused.Organization:describes the company as a legal or business entity without mandatory local reference. It suits brands and supra-regional firms.WebSite:describes the website itself, for instance for the sitelinks search box.LocalBusiness:is a specialization of Organization and Place and describes a business with a physical location and local service area. Only LocalBusiness carries address, geo-coordinates, and opening hours as core properties.

Choosing the right sub-type is crucial. Google explicitly recommendsusing the most specific LocalBusiness sub-type, such as Restaurant, DaySpa, or HealthClub. Schema.org defines an extensive hierarchy:Dentistfor a dental practice,Plumberfor a plumber,Restaurantfor gastronomy,LegalServicefor a law firm. If no suitable sub-type exists, use the general typeLocalBusiness. An incorrect or overly general type wastes context that specialized sub-types provide through additional properties such asservesCuisineormenu.

Mandatory and recommended properties in detail

Google specifies twomandatory properties in its documentation: name and address of type PostalAddress. Without these two fields, the markup is invalid. All other properties are recommended and significantly increase utility.

• name:the exact business name, identical to Google Business Profile and citations.
• address (PostalAddress):structured address withstreetAddress,postalCode,addressLocality(city),addressRegion(state), andaddressCountry(for AustriaAT).
• geo (GeoCoordinates): latitudeandlongitudeas decimal degrees. Precise coordinates improve mapping in Maps, especially for ambiguous addresses.
• telephone:the telephone number in international format with country code, for Austria starting with+43.
• openingHoursSpecification:machine-readable opening hours withdayOfWeek,opens, andclosesin 24-hour format.
• priceRange:the price level, for example as a symbol (€€) or range.
• areaServed:the service area, especially useful for businesses without walk-in customers that travel to clients.
• url, image, sameAs:website, photo, and links to profiles such as Google Business Profile, Facebook, or business directories.

JSON-LD step by step: Example for a Vienna business

The following example shows valid markup for a fictional dental practice in Vienna. Note the Austria-specific formatting:addressCountryset toAT, telephone number in+43format, and decimal point (not comma) for geo-coordinates.

```html
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Dentist",
"@id": "https://www.zahnarzt-beispiel.at/#praxis",
"name": "Zahnarztpraxis Dr. Beispiel",
"image": "https://www.zahnarzt-beispiel.at/praxis.jpg",
"url": "https://www.zahnarzt-beispiel.at",
"telephone": "+43 1 5550123",
"priceRange": "€€",
"address": {
"@type": "PostalAddress",
"streetAddress": "Mariahilfer Straße 100",
"postalCode": "1070",
"addressLocality": "Wien",
"addressRegion": "Wien",
"addressCountry": "AT"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": 48.198765,
"longitude": 16.345678
},
"openingHoursSpecification": [
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday"],
"opens": "08:00",
"closes": "17:00"
},
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": "Friday",
"opens": "08:00",
"closes": "13:00"
}
],
"sameAs": [
"https://www.google.com/maps/place/?q=place_id:BEISPIEL",
"https://www.facebook.com/zahnarztbeispiel"
]
}
</script>
```

Place the block in the<head>or<body>of the respective page, ideally on the homepage or contact page with complete location data. The@idattribute with a unique URL is important once you link multiple entities or represent multiple locations. Every piece of information provided must also be visible on the page.

NAP consistency: Schema, Google Business Profile, and citations

NAP stands for Name, Address, Phone. These three data points must be identical across all sources: in LocalBusiness Schema, in Google Business Profile, and in local citations such as herold.at, firmenabc.at, or business directories. Inconsistencies, such as "Str." versus "Straße" or different telephone formats, weaken the search engine's trust in the data and can impair local visibility.

The Schema is the machine-readable confirmation of what appears in the Google Business Profile and citations. ThesameAsproperty explicitly links your website to these external profiles and helps search engines recognize the entries as the same entity. Therefore maintain a single authoritative NAP spelling and adopt it unchanged everywhere. Consistency across multiple platforms is relevant because consumers check multiple sources anyway: According to an international US survey,77% of consumers use at least two review platforms in their researchand 41% even three or more.

AggregateRating and Review markup for local businesses

Reviews are a strong lever in the local context. According to BrightLocal's international US study,81% of consumers read reviews of local businesses via Google, and 75% read online reviews "always" or "regularly." WithAggregateRatingmarkup, you can specify the average rating and count, which can enable stars as rich results in search results.

Google's guidelines are strict here. Self-serving reviews, meaning reviews that a business embeds about itself on its own site, are not permitted for star rich results on LocalBusiness. Only mark reviews that are actually and visibly present on the page and come from end customers. Fabricated or aggregated values without visible evidence violate the guidelines and can lead to manual actions. TheratingValue,reviewCount, andbestRatingmust exactly match the data displayed on the page.

Multi-location, Service-Area-Businesses, and @id linking

Businesses with multiple locations require a separate LocalBusiness object per branch with its own address, geo-coordinates, and@id. Create a dedicated landing page for each location and place the appropriate markup there. Via the@id, locations can be consistently referenced and linked to a parentOrganizationobject describing the parent company.

• Multiple branches:per location a separate URL, separate@id, and separate LocalBusiness object with location-specific data.
• Service-Area-Business:Businesses without a public location, such as mobile tradespeople, omit the visible address and instead defineareaServedwith the served cities or regions.
• @id as anchor:A unique@idper entity prevents search engines from merging multiple locations into one entity and allows clean links between Organization and individual branches.

Validation and troubleshooting

Published markup must be tested. Three tools complement each other.

• Rich Results Test:Google's test shows whether the markup can produce a rich result and which properties are missing or incorrect. It is the first point of contact for LocalBusiness.
• Schema Markup Validator (schema.org):This validator checks syntactic and structural correctness according to the Schema.org specification, independent of Google rich results.
• URL Inspection in Search Console:It shows how Google actually renders the live page and which structured data was detected. This reveals whether the markup arrives in the crawled state, for instance with client-side rendered JavaScript.

Treat warnings and errors separately. Errors prevent rich results and must be fixed; warnings concern missing recommended properties and should be supplemented but are not blocking.

Local Schema Markup in the context of AI-Search and AEO

Structured data gains importance with the rise of AI-powered search. Google AI Overviews, ChatGPT, and Perplexity preferentially draw facts from clearly structured, unambiguously attributed sources. LocalBusiness Schema delivers exactly that: machine-readable statements about location, opening hours, and services that an AI system can directly incorporate into an answer.

For Answer Engine Optimization (AEO), this means: Consistent, visible, and Schema-confirmed data increase the likelihood that a local business is correctly mentioned in AI answers. The markup does not replace good content, but it reduces ambiguity. When address, telephone number, and opening hours match in both visible text and JSON-LD, the risk decreases that an AI system uses outdated or incorrect data from third-party sources. Given the low prevalence of LocalBusiness markup, clean implementation is a realistic advantage over competitors.

Common errors in Local Schema Markup

• Incorrect or overly general sub-type: LocalBusinessinstead ofDentistorRestaurantwastes specific context and additional properties.
• Inconsistent NAP data:Discrepancies between Schema, Google Business Profile, and citations weaken the search engine's trust.
• Markup without visible page content:Data in JSON-LD that does not appear on the page violates Google's guidelines and can be ignored or penalized.
• Self-serving review markup:Own reviews embedded on one's own site are not permitted for star rich results on LocalBusiness.
• Incorrect formats:Telephone numbers without+43, opening hours not in 24-hour format, or geo-coordinates with comma instead of period lead to errors.
• Multiple locations in one object:Branches without their own@idand own page merge and lose their individual visibility.

Measuring success: Rich results, impressions, and CTR

You measure the success of Local Schema Markup primarily in Google Search Console. The rich results enhancements report shows valid elements, warnings, and errors for structured data and reports as soon as Google detects the markup.

• Track rich result status:Monitor the number of valid elements in the enhancements report and fix reported errors promptly.
• Observe impressions:Rising impressions for local queries after implementation suggest better capture. Filter the performance report by Austria and by place names.
• Compare CTR:If stars or enhanced snippets appear, the click-through rate of affected pages should rise measurably. Compare CTR before and after markup for the same queries.
• Check indexing:Verify via URL Inspection whether Google actually reads the markup on the live page.

Note that rich results are not guaranteed. Google decides based on query and quality whether to display an enhanced snippet. Therefore evaluate success via the combination of detected markup, impressions, and CTR, not a single metric.

Further reading

Local Schema Markup is a technical foundation that only realizes its value in combination with consistent data. Start with the most specific LocalBusiness sub-type, fill the mandatory fieldsnameandaddressplus the most important recommended properties, and keep NAP identical across website, Google Business Profile, and citations. Validate the result with the Rich Results Test and URL Inspection and monitor the impact in Search Console. Since only a small fraction of pages use LocalBusiness markup, clean implementation is a concrete and achievable advantage for Austrian businesses in traditional and AI-powered search.