This month Google made improvements to the consumer search experience. Google made some big changes to its search engine around this same time last year to improve the relevancy of search results. These Google search algorithm changes were aimed at better understanding language, which is the foundation of how people search. These changes build upon what Google launched in 2018 when they introduced and open-sourced a neural network-based technique for natural language processing (NLP) pre-training called Bidirectional Encoder Representations from Transformers, which is more commonly known as BERT. In 2019 it was implemented in Google Search and was used in about 10% of searches. As of this year, BERT powers almost every single English based query done on Google Search.
What does this change mean for businesses? More than you’d think, as these Google algorithm changes improve your consumer’s ability to find you while performing a Google search. The BERT improvement helps correct user spelling errors, which is helpful if your business uses terms that are frequently misspelled or have multiple spelling variations. As many as one in ten searches are misspelled, so this may be impacting your potential consumer’s experience trying to find your business.
Google has also implemented a feature enabling more relevant language to display from the page being displayed within the search result, this feature is called passages. With the new passage capabilities, Google can understand that a specific passage within a page is a lot more relevant to a specific search than a broader page on that topic and they will display the relevant passage within the results.
This contextualization and enhanced focus on how consumers use language to try to find relevant information helps businesses who focus on generating quality content on their websites. It means that you don’t have to worry as much about trying to capture all of the spelling variations or semantic variations in your business or industry, you can prioritize generating meaningful content.