BERT

BERT (Bidirectional Encoder Representations from Transformers) is a language understanding model used by Google to better interpret the context of words in search queries. Its key advantage is bidirectional context: meaning is inferred from surrounding terms rather than isolated keywords. For marketers, this reinforces the importance of intent-focused writing instead of exact-match keyword stuffing. Content that answers real user questions with clear structure and topical depth tends to align better with BERT-driven interpretation. BERT does not require technical "optimization" as a feature toggle; it rewards high-quality language and semantic relevance. Teams should use it as a strategic reminder to write for comprehension, cover related subtopics, and resolve ambiguity that might confuse either users or search engines.