By Shad Super in Questions —

How Does Incorporating BERT Into On-Page SEO Affect Content Strategy and Google's Understanding of Page Relevance?

Summary

Incorporating BERT (Bidirectional Encoder Representations from Transformers) into on-page SEO enhances content strategy by prioritizing natural language understanding and user intent. This shift enables Google to better comprehend context and semantics, rewarding content that aligns with user queries in a conversational and precise manner. Adapting to BERT requires focusing on high-quality, contextually relevant content rather than relying solely on keywords.

Understanding BERT's Impact on SEO

What is BERT?

BERT, developed by Google, is a machine learning model designed to understand the nuances of human language, including context, intent, and semantic relationships between words in a sentence. Instead of analyzing individual keywords, BERT processes entire sentences bidirectionally to grasp meaning more effectively. For example, BERT can better understand the difference in meaning between "bank" in "river bank" versus "savings bank."

Introduced in 2019, BERT powers Google's search algorithms, particularly by improving the relevance of search results for complex or conversational queries. As of today, BERT is used in almost all English-language searches [Google Blog, 2019].

How BERT Changes Google's Understanding of Content

  • Focus on Context: BERT can analyze sentences holistically, allowing Google to better understand the role of prepositions, conjunctions, and other context-dependent terms. This reduces the emphasis on individual keywords and increases the importance of semantic relevance.
  • User Intent Recognition: Queries that involve natural language, conversational tones, or long-tail search terms are better processed with BERT. For instance, in the query "how to catch a fish without a rod," BERT identifies that the intent isn't about using a rod but alternatives to it.
  • Improved Passage Ranking: Google's integration of BERT extends to passage indexing, where relevant sections of a webpage can rank even if the broader page doesn’t directly target the query [Google Search Central Blog, 2020].

Implications for On-Page SEO

Content Strategy Adjustments

With BERT prioritizing user intent and context, the conventional approach of keyword stuffing is no longer effective. Instead, content creators must focus on delivering value through comprehensive, reader-focused content. Below are specific strategies:

1. Write for Humans First

Create content that answers questions directly and provides value to users. For example, instead of forcing keywords like "best dog grooming tools," write naturally: "What are the best tools for grooming your dog?" Focus on solving user problems with clear, conversational phrasing [Moz, 2019].

2. Long-Tail Keywords and Natural Phrasing

Incorporate long-tail keywords that mimic how users ask questions. For instance, instead of targeting "SEO tools," optimize for user-intent-driven phrases like "what are the best free SEO tools for beginners?" This aligns with the conversational queries BERT processes best [Search Engine Land, 2019].

3. Content Depth and Context

Ensure your page covers topics comprehensively. BERT rewards pages that fully explore a subject, using subheadings, bullet points, and examples to address all facets of a query. For example, if writing about "how to start a garden," include sections on soil preparation, seed selection, watering schedules, and pest control.

BERT's ability to identify the most relevant passages makes it crucial to structure content for featured snippets. Use concise, answer-focused paragraphs and include lists, tables, and step-by-step instructions tailored to common queries [Search Engine Journal, 2019].

Technical SEO Considerations

While BERT primarily emphasizes content, technical SEO plays a supporting role in ensuring Google can access and interpret your pages effectively:

  • Structured Data: Use schema markup to clarify the content and enhance the chances of appearing in rich results.
  • Mobile Optimization: Ensure content is mobile-friendly, as many conversational queries originate from voice or mobile searches.
  • Fast Page Speed: Optimize load times to ensure users (and search engines) can access content quickly [Web.dev, 2023].

Examples of BERT in Action

Example 1: "Can you get medicine for someone pharmacy?"

Before BERT, Google might have focused on keywords like "medicine" and "pharmacy," returning results for general pharmacy services. Post-BERT, Google understands the intent is about whether someone can pick up a prescription on behalf of another person.

Example 2: "Brazil traveler to USA needs a visa."

BERT helps Google understand the query's nuanced meaning: Does a Brazilian traveling to the USA need a visa? Results are more aligned with the specific intent rather than offering general travel advice.

Conclusion

BERT has revolutionized how content strategy and on-page SEO should be approached, emphasizing user intent, contextual relevance, and natural language. To succeed, focus on creating high-quality, comprehensive content designed for human readers. While keywords still matter, their importance has shifted from simple placement to semantic alignment. By optimizing for BERT, you not only align with Google’s algorithms but also enhance user satisfaction and engagement.

References