Word Count Doesn’t Matter for SEO in 2025. Here’s What to Do Instead.
For years, SEOs have repeated the same advice:
“Write longer content.”
“Google prefers in-depth pages.”
“Aim for 2,000+ words.”
But when our technology partner looked at the data, the truth became impossible to ignore:
Content length doesn’t matter for SEO in 2025.
Here’s what they found after digging into 1 million pages, and how it reshapes how we think about content quality.
The Results
Text-length factors dropped to zero
Term usage surged in importance
However, why does the length of the text itself, in isolation from CS, maintains a high correlation.
At first, it seemed like term usage and text length might still be linked—longer pages naturally include more terms. So they dug deeper.
They filtered the data to include only pages that used at least 50% of suggested terms, something surprising happened:
Text length stopped mattering entirely. In fact, there was a slight preference for shorter, more focused content.
Re-evaluate
Based on observations on AI research, Google isn’t evaluating content the way it used to. With LLMs parsing pages using enormous context windows—think 1 million+ tokens—it no longer relies on word count as a shortcut for quality.
It evaluates meaning, relevance, and topical completeness.
If your content says everything it needs to in 700 words, that’s enough. If it takes 2,000 words to be useful, go for it. But stop writing more just because you think you have to.
Get Started
What to do instead of chasing word count
If you’re still writing long content just for the sake of it—stop.
- Don’t chase word count
- Don’t fluff your pages
- Don’t assume longer = better
Instead, focus on writing complete, relevant, and helpful content.
Use the right terms. Cover the topic deeply. Be useful.
Google doesn’t reward length anymore. It rewards coverage.
If coverage—not length—is what really moves the needle, then you need to use our investment in technology, tools built to help you optimise for exactly that.
Scaning top-performing SERPs, AI Overviews, and trusted LLMs like ChatGPT and Perplexity to uncover context-rich facts, subtopics, and relationships your content might be missing.
Then it suggests (and automatically inserts) high-context additions directly into your article, so you can strengthen topical coverage in seconds, without manual research.
Let’s say you’re writing about “beard grooming tips.” Dropping in isolated terms like “beard conditioner” or “split ends” won’t move the needle. But tie them together with context, like “Use a beard conditioner to soften beard hair and reduce split ends”, and suddenly your content becomes more meaningful.
Your Guide to Visibility in the AI Era
