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Entity linking gives multi-location brands semantic clarity, improving local rankings, non-branded visibility, and AI search accuracy.
Search has changed dramatically, including local search. Search engines and AI systems now incorporate semantic understanding to generate citations and results. To gain semantic understanding, they need to know which topics appear in the content and how they relate to one another so that they can identify your areas of authority.
For brands with multiple locations, this shift can create challenges. Search engines often misinterpret place names or the services a location offers, which can lead to the wrong landing page appearing for a near-me query. At the same time, it gives local SEOs a new opportunity to add needed semantic clarity.
To support clarity and semantic understanding, SEOs should adopt an entity SEO approach. The topics, also known as entities, are like keywords with multiple dimensions. When defined within your content and with schema markup, entities can bring clarity to AI and search engines.
In Microsoft’s recent article titled “Optimizing Your Content for Inclusion in AI Search Answers,” Krishna Madhavan, Bing’s Principal Product Manager, stated:
“Schema can label your content as a product, review, FAQ, or event, turning plain text into structured data that machines can interpret with confidence.”
This semantic understanding is what adds clarity to AI.
With more than 47 locations, one of our clients, Brightview Senior Living, needed a way to scale SEO across dozens of markets. Entity linking helped them do exactly that. Their strategy shows what SEOs can start doing today to gain clarity, authority, and better local performance.
In the world of Entity SEO, search engines now look beyond keywords for:
Entities include locations, services, products, people, or anything else with a definable meaning. But identifying an entity is only the first step. Search engines also need to understand the entity’s context, which is where properties in schema markup come in and help disambiguate what the entity actually represents.
When you optimize a page, you describe its main entity. By using the schema.org vocabulary, you can leverage its properties to provide search engines and AI with a structured way to understand the entity.
For example, if you’re describing a location, you’d define the physical location as a LocalBusiness entity, using schema properties to describe the business and its service area, and then define the properties that map to the content on the page to describe it.
Now that you’ve defined the entity using properties, it’s time to add entity linking.
There are two types of entity linking: external entity linking and internal entity linking.
Internal Entity linking is the process of linking to internal entities on your website. External Entity linking is the process of linking entities on your site to their definitions in authoritative knowledge bases such as Wikipedia, Wikidata, or industry-specific glossaries. This is done using schema.org properties such as “sameAs”, “mentions”, “areaServed”, and more. Note that entity linking can use any properties within schema.org.
Today, we’ll focus on external entity linking.
By linking the entities mentioned in your website content to authoritative external sources, you provide search engines with clear, explicit definitions. This reduces ambiguity, improves the relevance of your rankings, and can help your content’s performance in AI summaries and intent-based search experiences.
For organizations looking to optimize for local search, place-based entity linking is particularly impactful.
Brightview Senior Living’s marketing team was responsible for performance across more than 47 community pages, each with its own name, local context, and service mix. Search engines often struggled to interpret these pages correctly, especially when the location name overlapped with a more prominent city elsewhere.
A prime example was Phoenix, Maryland, being confused with Phoenix, Arizona. This kind of misunderstanding can derail visibility for queries such as “assisted living near me” or “assisted living in Phoenix.”
To improve search engines’ understanding of what Brightview offered and where, they needed a future-proof strategy grounded in semantic clarity.
Brightview shifted from keyword-first SEO to entity-first SEO. Their strategy focused on identifying the entities that defined each location and service offering, then linking them to authoritative definitions to eliminate ambiguity.
On each community page, Brightview explicitly defined the location entity and linked it to its authoritative source. For example:
This resolved issues such as the Phoenix, Maryland, confusion by telling search engines exactly which Phoenix the content referred to. It also provided a clear geographic signal for near me and geo-modified queries.
Brightview applied entity linking to core service terms, including assisted living and independent living. These concepts were linked to authoritative sources using “sameAs” and “mentions”.
This helped Brightview show up more consistently for non-branded, high-intent searches like “assisted living communities” or “independent living options,” which are critical touchpoints early in the customer journey.
By linking assisted living to a known entity, search engines recognized Brightview’s content as authoritative on the topic. This moved Brightview beyond brand-dependent queries and into the realm of broader, category-level search visibility.
Entity linking was applied across community pages, blog posts, and informational resources. This built a connected content knowledge graph that reinforced Brightview’s authority across both topics and locations that mattered most to their organization.
The result was a site where search engines could clearly understand what each page was about, what locations it represented, and how those pages related to Brightview’s broader expertise.
By disambiguating locations and services, Brightview made it easier for AI systems to return correct answers when users searched for care options in specific regions.
After implementing entity linking, Brightview saw measurable gains in both local and non-branded visibility.
Non-branded queries often indicate users who have not yet chosen a provider and who are actively evaluating options.
By clearly defining their service entities using schema markup, Brightview achieved:
This shift shows how entity linking helps organizations rank for what they do and where they do it, not just who they are.
With place-based external entity linking in place, Brightview’s community pages performed better for high-intent local searches. Search engines better understood the connection between each community and its service area.
Across community pages, Brightview saw:
Pages that used clear, linked location data were more reliably served for near-me and city-based queries.
As AI Overviews reshape the SERP with zero-click search, many brands have seen their click-through rate drop. Brightview’s CTR remained strong relative to benchmarks. Clear entity definitions helped search engines and AI models surface their content accurately, even as the search landscape shifted.
Ryan Pitcheralle, Brightview’s SEO consultant, noted that the strength of their schema markup implementation was a direct driver of performance. As he put it, their results showed “complete causation, not just correlation. This is why we’ve stayed competitive in clickthrough rate and performance while everyone else is sliding.”
Entity linking is not only a technical tactic. It is a strategic opportunity to clarify what your organization should be known for. Here is how to apply it effectively.
Your website contains many entities, but you do not need to link them all. Focus on the ones that support clarity and strategic differentiation.
For example:
Consistently linking these entities signals to search engines where your expertise lies.
Entity linking is a key part of creating a content knowledge graph that shows search engines the relationships between your locations, offerings, resources, and brand. Your content knowledge graph helps machines infer meaning, understand context, and deliver more accurate results about your organization that can make or break conversions.
Local search hinges on clarity. Search engines need explicit signals about:
Place-based entity linking provides that clarity and increases your chances of ranking for geo-modified and near-me queries.
AI search experiences rely on correctly interpreted entities. When locations, services, and concepts are linked to authoritative sources, AI systems can return more accurate, helpful answers and are more likely to reference your content correctly.
Brightview’s success shows that entity linking is a practical, high-impact way to strengthen local search performance. By clarifying locations, services, and key concepts, you can help search engines and AI systems understand exactly what your content represents.
Entity linking improves semantic accuracy and builds the foundation for long-term authority. For SEO and marketing leaders, it is one of the most actionable ways to prepare for the future of semantic and AI-driven search.
More Resources:
Featured Image: optimarc/Shutterstock
Martha van Berkel is the CEO and co-founder of Schema App, an end-to-end Schema Markup solution provider. She focuses on …
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