Google RankBrain & BERT: How AI is Reshaping SEO and Digital Marketing Strategies

Understanding the intricacies of search engine algorithms is paramount for those looking to optimise their online presence. Among the various updates and components that Google has introduced to its search algorithm, RankBrain stands out as a significant advancement, followed by BERT.

Confirmed by Google on October 26th, 2015, RankBrain utilises machine learning to process and interpret the billions of searches that Google handles every day.

This article delves into RankBrain and BERT, implications for SEO, and how digital marketers can adapt to this evolving landscape.

What is Google RankBrain?

RankBrain is a machine learning-based search engine algorithm component that helps Google understand the intent behind queries and deliver more relevant search results. Before RankBrain, Google relied on its basic algorithm to decide which results to show for a query. However, with the introduction of RankBrain, Google can now interpret queries more effectively by considering factors such as the searcher’s location, personalisation, and the specific words used in the query.

The significance of RankBrain lies in its ability to learn and improve over time. By analysing vast amounts of data, it teaches itself to make connections and identify patterns that help it better understand searcher intent. This capability sets RankBrain apart from previous updates and is a leap forward in the quest for a more intuitive and responsive search engine.

Understanding RankBrain’s Role in Search

Consider the complexity of interpreting a search query like “Olympics location.” The searcher’s intent could range from wanting to know the location of the upcoming Olympics, seeking directions to the Olympic venue, or even looking for historical information about the first Olympics. Before RankBrain, Google might have struggled to discern the true intent behind such a multifaceted query, often relying on simplistic signals like content quality or the number of links.

However, RankBrain excels in these scenarios. It uses machine learning to infer the most likely intent behind a query and adjust search results accordingly. For example, if the majority of people searching for “Olympics location” are interested in the next Games, RankBrain will prioritise showing that information, possibly through a Google answer box. This adaptability ensures that users are more likely to find what they are looking for, even with ambiguous or complex queries.

The Impact of RankBrain on SEO

RankBrain’s introduction has necessitated a shift in SEO strategies. Traditional approaches that focused heavily on keywords and link-building are no longer sufficient. Digital marketers must now consider the context and intent behind searches. This evolution aligns with Google’s overarching goal to provide users with the most relevant and useful information.

1. Different Ranking Signals for Different Queries: SEO strategies must be tailored to the type of content and the user’s intent. For urgent information, such as news about a hurricane, freshness might be more important than the number of links. Conversely, for historical or educational content, depth and authority might carry more weight.
2. Reputation Based on Signals: Websites need to establish a reputation for delivering content that meets specific needs, whether that’s providing quick answers, in-depth analysis, or fresh updates. RankBrain has created an environment where a website’s reputation can be built on its ability to satisfy particular user intents.
3. Comprehensive Content Over Single-Keyword Pages: The strategy of creating multiple pages for keyword variants is outdated. Instead, SEO now favours comprehensive content that addresses entire concepts in a natural and engaging manner, reflecting the way people actually search and speak.

Adapting to RankBrain in Digital Marketing Strategies

For digital marketers, adapting to RankBrain means focusing on quality content that addresses the searcher’s intent. It’s about understanding the nuances of how your audience searches for information and tailoring your content to meet those needs. This could involve:

• Conducting in-depth keyword research to understand the language and questions your audience uses.
• Creating comprehensive content that answers those questions in a detailed and authoritative manner.
• Ensuring your website is user-friendly and provides a good experience, as user engagement metrics can influence rankings.
• Staying updated with SEO best practices, as the algorithms and what they prioritise can change over time.

The Introduction of BERT

Google introduced BERT (Bidirectional Encoder Representations from Transformers) in 2019. This leap in natural language processing technology marked a significant shift in how search engines interpret the context and nuances of search queries.

BERT’s integration into Google’s search algorithm underscores a broader movement towards AI-driven SEO, where understanding the intent behind users’ searches becomes as crucial as the keywords themselves.

Understanding BERT’s Impact on Search

BERT represents a paradigm shift in natural language understanding. By focusing on the context in which words appear, BERT goes beyond the limitations of traditional keyword matching. It comprehends the subtleties of language, such as how the presence or absence of small function words like “for” and “to” can alter the meaning of a query.

This capability enables Google to grasp the intent behind a search query with unprecedented accuracy.

Consider the query “can you get medicine for someone pharmacy.” Before BERT, search engines might focus on keywords like “medicine” and “pharmacy,” potentially overlooking the critical context provided by “for someone.” BERT, however, recognizes the importance of these connecting words, understanding that the searcher is inquiring about the possibility of picking up medication on behalf of another person. This nuanced understanding allows Google to return results that are more closely aligned with the searcher’s intent.

BERT’s Contributions to SEO

BERT’s influence on SEO is profound, affecting both the ranking and retrieval aspects of search. By enhancing Google’s ability to understand natural language, BERT ensures that even the most complex or ambiguously worded queries yield relevant results. For digital marketers and SEO professionals, this means that:

• Content must be naturally written and contextually rich: With BERT, the focus shifts towards creating content that answers questions and provides value in a natural, conversational tone. Keyword stuffing becomes even less effective, as BERT seeks content that genuinely addresses the nuances of user queries.
• Long-tail keywords gain importance: BERT’s ability to parse the nuances of language makes long-tail keywords — which often more closely resemble natural speech patterns — more crucial than ever. These keywords can capture the specific intent behind searches, aligning content more closely with user needs.
• User-focused content is key: The ultimate goal of BERT is to connect users with the information they seek. Therefore, understanding your audience and the types of questions they are asking is essential. Content should be designed to comprehensively answer these questions, considering the various ways someone might phrase them.

The Collaborative Nature of BERT in Google Search

While BERT has significantly advanced Google’s language understanding capabilities, it does not work in isolation. It’s part of a complex ecosystem of algorithms and systems that work in concert to deliver the most relevant and high-quality search results. This collaborative approach ensures that no single system, including BERT, dictates the entirety of search outcomes. Instead, it contributes to a nuanced understanding of queries, enhancing the overall quality of search results.

The Future of RankBrain, BERT and Digital Marketing

As machine learning technology continues to evolve, so too will RankBrain and BERT, and its impact on search. Digital marketers must stay agile, continuously learning and adapting to these changes.

The focus should always be on providing value to the user, as this aligns with Google’s objectives and thus, is favoured by its algorithms.

RankBrain and BERT represents a significant step forward in the evolution of search engines, moving towards a more intuitive and user-focused experience. For digital marketers, this underscores the importance of creating high-quality, relevant content that meets the needs of their audience.

As the digital landscape continues to change, those who can effectively adapt to these advancements will thrive, ensuring their content is not only seen but also valued by their target audience.

In the realm of digital marketing, understanding and adapting to the nuances of search engine algorithms like RankBrain and BERT is not just beneficial; it’s essential for success!