The landscape of search, particularly local search, has undergone a significant transformation. Modern search engines and AI systems increasingly rely on semantic understanding to generate relevant results and citations. To achieve this, they must identify the topics (or entities) within content and understand their relationships, thereby recognizing areas of authority. For brands operating across multiple locations, this evolution presents both challenges and opportunities. Search engines frequently misinterpret place names or the specific services a location offers, potentially leading users to incorrect landing pages for "near me" queries. However, this shift also empowers local SEO professionals to introduce crucial semantic clarity. To foster this clarity and semantic understanding, SEO strategies should embrace an entity SEO approach. Entities, essentially multi-dimensional keywords, become invaluable when clearly defined within content and supported by schema markup. This structured data helps AI and search engines interpret information with greater precision. As Krishna Madhavan, Bing’s Principal Product Manager, noted in Microsoft’s article "Optimizing Your Content for Inclusion in AI Search Answers":

"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 fundamental to enhancing AI clarity. Brightview Senior Living, a client with over 47 locations, faced the challenge of scaling its SEO efforts across numerous markets. Entity linking proved to be the key to achieving this, demonstrating a strategy that other SEOs can adopt today to improve clarity, build authority, and boost local performance.

Why Entity Linking is Crucial for Local SEO Today

In the realm of Entity SEO, search engines now delve beyond mere keywords to analyze:
  • What entities are mentioned on a page.
  • How those entities relate to a user's search queries.
  • Whether the content offers meaningful context and clarity.
Entities encompass locations, services, products, people, or any concept with a definable meaning. However, merely identifying an entity is insufficient. Search engines also require an understanding of the entity's context, which is where properties within schema markup become essential for disambiguation. When optimizing a page, you describe its primary entity. By utilizing the schema.org vocabulary, you can leverage its properties to provide search engines and AI with a structured framework for understanding the entity. For instance, to describe a physical location, you would define it as a LocalBusiness entity, using schema properties to detail the business, its service area, and how these map to the content on the page. Once an entity is defined using properties, the next step is to implement entity linking. There are two primary types of entity linking: external and internal. Internal entity linking involves connecting to other entities within your own website. External entity linking, which is our focus here, involves linking entities on your site to their definitions in authoritative knowledge bases such as Wikipedia, Wikidata, or specialized industry glossaries. This is achieved using schema.org properties like `sameAs`, `mentions`, and `areaServed`, among others. By linking the entities in your website content to credible external sources, you provide search engines with explicit, unambiguous definitions. This process reduces uncertainty, enhances the relevance of your rankings, and can significantly improve your content's performance in AI summaries and intent-based search experiences. For organizations aiming to optimize for local search, place-based entity linking is particularly impactful.

Brightview's Challenge: Scaling Hyperlocal SEO Across 47+ Communities

Brightview Senior Living’s marketing team faced the complex task of managing SEO performance for over 47 community pages. Each page had a unique name, local context, and service mix. Search engines frequently struggled to accurately interpret these pages, especially when a location name coincided with a more prominent city elsewhere. A common issue, for example, was Phoenix, Maryland, being confused with Phoenix, Arizona. Such misunderstandings can severely hinder visibility for critical queries like "assisted living near me" or "assisted living in Phoenix." To improve search engine comprehension of Brightview's offerings and locations, a future-proof strategy rooted in semantic clarity was essential.

The Solution: Place-Based and Topical Entity Linking at Scale

Brightview transitioned from a keyword-first to an entity-first SEO approach. Their strategy centered on identifying the specific entities that defined each location and service offering, then linking these to authoritative definitions to eliminate ambiguity.

1. Disambiguating Place Names

On every community page, Brightview explicitly defined the location entity and linked it to its authoritative source. This involved:
  • Using `mentions` within the schema markup to pinpoint the specific place referenced on the community page.
  • Employing `areaServed` on community pages to clarify the geographic region the location serves.
  • Utilizing `sameAs` to link each location entity to authoritative sources like Wikipedia, Wikidata, and Google’s Knowledge Graph, effectively disambiguating places with similar or identical names.
This approach successfully resolved issues like the Phoenix, Maryland, confusion by explicitly informing search engines which Phoenix the content referred to. It also provided a clear geographic signal for "near me" and geo-modified queries.

2. Mapping Key Services as Entities

Brightview extended entity linking to its core service terms, including "assisted living" and "independent living." These concepts were linked to authoritative sources using `sameAs` and `mentions`. This strategy significantly improved Brightview's consistent appearance for non-branded, high-intent searches such as "assisted living communities" or "independent living options," which are crucial touchpoints early in the customer journey. By linking "assisted living" to a recognized entity, search engines acknowledged Brightview’s content as authoritative on the topic, moving the brand beyond reliance on branded queries into broader, category-level search visibility.

3. Scaling Entity Linking Across All Content Types

Entity linking was systematically applied across community pages, blog posts, and informational resources. This effort constructed a connected content knowledge graph that reinforced Brightview’s authority across the topics and locations most vital to their organization. The outcome was a website where search engines could clearly comprehend the purpose of each page, the locations it represented, and how these pages contributed to Brightview’s overall expertise. By disambiguating locations and services, Brightview made it easier for AI systems to deliver accurate answers when users searched for care options in specific regions.

The Result: Stronger Local Visibility and More Accurate Search Interpretation

Following the implementation of entity linking, Brightview observed significant gains in both local and non-branded visibility.

Stronger Non-Branded Search Performance

Non-branded queries typically originate from users who are still evaluating options and have not yet committed to a specific provider. By clearly defining their service entities using schema markup, Brightview achieved:
  • 25% increase in clicks for non-branded queries featuring the "assisted living" entity.
  • 30% increase in impressions for those same queries.
This demonstrates how entity linking enables organizations to rank for *what they do* and *where they do it*, rather than solely for *who they are*.

Higher Discoverability for Community Pages

With place-based external entity linking in place, Brightview’s community pages performed better for high-intent local searches. Search engines gained a clearer understanding of the connection between each community and its service area. Across community pages, Brightview saw:
  • 16% year-over-year increase in clicks (despite industry-wide declines).
  • 26% year-over-year increase in impressions.
Pages with clear, linked location data were more reliably served for "near me" and city-based queries.

Stable CTR Despite Industry Declines

As AI Overviews continue to reshape the Search Engine Results Page (SERP), leading to an increase in zero-click searches, many brands have experienced a drop in their click-through rates (CTR). Brightview’s CTR, however, remained robust relative to industry benchmarks. The precise entity definitions helped search engines and AI models accurately surface their content, even amidst shifts in the search landscape. Ryan Pitcheralle, Brightview’s SEO consultant, emphasized that the strength of their schema markup implementation was a direct driver of this performance. He stated that 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."

How to Use Entity Linking Strategically

Entity linking is more than just a technical SEO tactic; it represents a strategic opportunity to clarify your organization's areas of expertise. Here’s how to apply it effectively:

1. Identify the Entities That Define Your Authority

While your website contains numerous entities, not all require linking. Focus on those that enhance clarity and strategic differentiation. For example:
  • Locations you aim to rank for.
  • Core service offerings.
  • Product categories.
  • Regulated terms or industry-specific definitions.
  • Topics on which you seek to establish authority.
Consistently linking these key entities signals your expertise to search engines.

2. Build a Connected Content Knowledge Graph

Entity linking is a vital component in creating a content knowledge graph. This graph illustrates to search engines the relationships between your locations, offerings, resources, and brand. A well-structured content knowledge graph helps machines infer meaning, understand context, and deliver more accurate results about your organization, which can be critical for conversions.

3. Prioritize Place-Based Entity Linking for Multiple Locations

Local search success heavily relies on clarity. Search engines require explicit signals regarding:
  • Which specific location your page refers to.
  • What services are available at that location.
  • Which geographic region that page serves.
Place-based entity linking provides this clarity, significantly increasing your chances of ranking for geo-modified and "near me" queries.

4. Prepare for AI Search

AI search experiences are highly dependent on correctly interpreted entities. When locations, services, and concepts are linked to authoritative sources, AI systems can generate more accurate and helpful answers, and are more likely to reference your content correctly.

Entity Linking: A Clear Path to Local SEO Accuracy

Brightview’s success story unequivocally demonstrates that entity linking is a practical and high-impact method for bolstering local search performance. By clarifying locations, services, and key concepts, organizations can help search engines and AI systems precisely understand their content. Entity linking not only improves semantic accuracy but also lays the groundwork for long-term authority. For SEO and marketing leaders, it stands as one of the most actionable strategies to prepare for the future of semantic and AI-driven search. More Resources: