BERT algorithm is considered one of Google’s most important algorithms and affects up to 10% of search queries. The term BERT (Bidirectional Encoder Representations from Transformers) is a technique that is applied to Natural Language Processing (NLP) to give Google a better understanding of what search queries contain and the right results to process for users.

BERT is an open-sourced neural network-based technique that Google uses to process words in search queries based on their relationship with other words in the same query. Before the roll-out of BERT, Google was only able to process queries based on the meaning of individual words.

So, Google uses BERT to understand not just the words in a query but the contextual meaning derived from all the words together. This means, even when words are spelled alike, BERT can use the context to understand which of the meanings of that word is applicable to users’ search queries. With BERT, users are able to get matching results for their search queries.

How BERT Affects SEO

With the BERT algorithm now helping Google get a deeper understanding of what users want, and a more contextual understanding of what is found in blog posts, it is expected that some blog posts that Google finds highly relevant to users will rank higher while a number of posts that do not give a clear understanding of what it contains may lose their rankings.

This update will also help Google focus on what people are looking for in specific niches. This means ranking for keywords will assume some importance for web pages. Where it was previously difficult for Google to understand some long-tail keywords, it will easily consider and understand them within their context of use.

BERT will also impact on voice searches and featured snippets as Google will be enabled to answer queries relating to voice searches more accurately.