10 queries, BERT aims to allow Google to more fully understand user intent through augmenting the company’s already significant Natural Language Processing capabilities. As Google states about search language understanding via BERT:
“BERT models can therefore consider
the full context of a word by looking at the words that come phone number library before and after it—particularly useful for understanding the intent behind search queries. By applying BERT models to both ranking and featured snippets in Search, we’re able to do a much better job helping you find useful information.”
In effect, what this means is that through BERT, Google has become more effective in its ability to interpret complex, long-tail queries and semantic context, returning increasingly relevant results based on the intent of the search.
Naturally, given that this update impacts
Google’s understanding of searches as opposed to how pages are up-to-date, high-quality business data. ranked, retailers are attempting to establish ways to optimize their ecommerce business for voice search, standard long-tail queries and other types of searches that BERT will impact.
Optimizing ecommerce Under BERT
While most Google updates come with a set of tactics that be numbers merchants can employ to help raise their rankings in the SERPs, Google has openly acknowledged that no such strategies exist for BERT.
