BERT.

BERT (Bidirectional Encoder Representations from Transformers) is a pre-trained NLP model introduced by Google in 2018. Unlike previous models that read text sequentially (left to right or right to left), BERT reads text bidirectionally—considering the full context of a word based on all surrounding words simultaneously. This enables dramatically better understanding of nuanced language.

BERT as a Ranking Factor

In October 2019, Google announced BERT integration into its search ranking system, describing it as 'one of the biggest leaps forward in the history of Search'. BERT helps Google understand the context of words in queries, particularly for conversational searches, prepositions, and nuanced phrasing that previous systems struggled with.

Writing for BERT

Content optimised for BERT is written for humans, not crawlers. BERT understands natural language so well that keyword stuffing actively hurts comprehension. Writing clear, contextually rich content that thoroughly explains concepts—using natural phrasing, related terms, and real-world examples—aligns with how BERT evaluates relevance.