What is the BERT algorithm update and why did it matter?
BERT is the natural language system Google introduced in 2019 to help it understand what a search query actually means. BERT stands for Bidirectional Encoder Representations from Transformers, and it changed the way Google reads words in context, particularly the small connecting words like "for", "to" and "without" that older keyword-matching systems tended to ignore. At launch Google said the change affected roughly one in ten searches.
Why Google introduced BERT
Before BERT, Google matched the words in a query to the words on a page. That worked well for simple searches, but it struggled with longer, conversational questions where the relationship between words matters. Consider a query like "can you get medicine for someone pharmacy". A keyword matcher can easily misread which word the search is about, because "for" carries the meaning. BERT reads a sentence in both directions at once, which lets Google weigh the context around each word instead of treating the query as a bag of keywords. The result was that pages which answered the question naturally started to perform better than pages which repeated an exact keyword phrase in awkward ways.
What BERT changed in practice
For anyone running a website, the practical lesson is simple: write for a reader, not for a search engine.
- Answer the question directly, in the first paragraph where possible.
- Use the words and phrases a customer would actually type, connecting words included.
- Write in natural sentences instead of forcing the keyword phrase in repeatedly.
- Structure the page with headings and short paragraphs so the answer is easy to find.
Google now understands the concept behind a query, not just the literal phrase, so content written the way people speak is exactly what it rewards. Our guide to the Helpful Content Update covers the same idea from the content side.
Was BERT a penalty?
No. BERT was an improvement to Google's understanding of language, not a punishment for websites. There was no manual action to fix and no disavow file to upload. Sites that lost visibility afterwards were usually relying on exact-match phrasing rather than genuinely useful content, but nothing about BERT needs recovering from in the way a link penalty does.
Where BERT fits now
BERT was one step in a longer move towards understanding rather than matching. The systems that followed it, including the language models behind Google's AI Overviews, build on the same idea: read the full query, understand the intent, and match it to content that genuinely answers the question. It is still worth understanding because it marks the point where natural, well-structured content began to beat keyword-stuffed pages.
How to check your site is writing for understanding
Read your key pages out loud and ask whether they answer the questions a customer would type. If a page reads naturally and answers the query directly, it is already in the right shape for the way Google now understands searches. The free SEO report flags the on-page issues that still hold pages back, and SEO plans start at GBP 980 a month with progress reported through the client dashboard.
See how Google understands your site at https://victory.digital/search-engine-optimisation
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