Google has enhanced its algorithm in a major way by releasing its latest natural language processing (NLP) iteration known as BERT. BERT is short for Bidirectional Encoder Representations from Transformers, and is an upgrade intended to enhance how Google interprets searches; whether queries be spoken or manually typed into a search bar. 

This update will have the biggest impact pertaining to search since the release of RankBrain; as it will affect around ten percent of all search queries, according to information collected from Search Engine Land.

What makes this update unique is that it is specifically designed to process not only the proposed question itself, but the context of the question. 

Here's an example of how BERT will enhance the quality of the results users receive. 

Example Search: A Californian driving from California to New York in 2019

  • Top Search Result Before Update: "What you need to know when driving from California to New York."
  • Top Search Result After Update: "What is the best driving route from California to New York in 2019"

The key difference between these search results is that, before the update, the algorithm couldn't understand the importance of the word "to," and its connection to the other words in the query. This lapse in understanding prevented the algorithm from truly understanding the intent behind the user's question, which affected the quality of their search results. With the implementation of BERT, Google's algorithm can detect this distinction and understand how important words like "to" are to a user's question, which will allow for better results. 

How Will BERT Affect SEO?

While the implementation of BERT is a major stepping stone pertaining to the advancement of NLP (natural language processing), the impact it will have on SEO is minimal. The purpose of BERT is to better understand conversational queries that are written and spoken in longer form, as opposed to the short-tail queries that tend to rank highest amongst those who utilize SEO keyword tracking tools.

Related: Choosing Keywords for SEO Friendly Content

Terms

  • NLP – NLP, or natural language processing, exists in the fields of computer science, linguistics, information engineering, and artificial intelligence. It focuses on relationships between human languages and computers. The purpose of natural language processing is to program computers to examine large amounts of natural language information.
  • Short-Tail Queries – Short-tail keywords are less specific key phrases that contain one word (e.g., homes). Shorter keywords rank better due to their higher search volume. To clarify, people are more likely to search "homes" than "build modern homes larger."
  • Long-Tail Queries – Long-tail queries are keywords that are longer (e.g., "build modern homes larger) and much more specific than traditional, high-ranking, short-tail key phrases. The length of long-tail keywords tends to negatively affect it's level of traffic, while also resulting in heightened conversion value due to their heightened specificity.

Should I Optimize My Content for BERT?

The short answer is no. Your content should still focus on creating the best possible material for your intended audience. The end goal for Google, concerning its algorithm, is to fully grasp all languages and all the nuances embedded within in order to provide users with the most relevant results. 

So, no need to conduct a complete overhaul of your SEO marketing strategy. The current update most likely won't impact your marketing efforts.

For business professionals looking to enhance your understanding of BERT, or to see if the update will affect your marketing, get in touch with the digital marketing experts at Ironmark today. We have extensive experience in all things marketing, and it would be our pleasure to help guide you through this new update.

LET'S TALK DIGITAL (MARKETING!)

Written by Reid Broendel

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