Free online word counter

Real-time counting

This counter lets you measure the number of characters and words instantly.

As you type, the counter updates in real time.

Frequency analysis

Beyond measuring words and characters, this tool calculates word, bigram and trigram frequency.

Word frequency is especially useful for writers and bloggers looking to avoid repetitions.

The tool analyzes each word, bigram and trigram in real time.

For SEO use, aim for a natural distribution of semantic vocabulary.

Understanding n-grams: unigrams, bigrams and trigrams

An n-gram is a sequence of "n" consecutive words extracted from a text. It's one of the fundamental tools of natural language processing (NLP) used by Google, spell-checkers, recommendation engines and generative AI. Analyzing n-grams means examining not just isolated words, but the relationships between them.

In SEO, n-grams help identify recurring key expressions in a piece of content, spot the formulations Google associates with a query, and analyze how your competitors structure their semantic field. Our tool automatically computes the 3 most useful levels: unigrams (1 word), bigrams (2 words) and trigrams (3 words).

Unigrams (word frequency)

A unigram is simply an isolated word. The "Word frequency" section of this tool lists unigrams ranked by occurrence. It's the most basic form of text analysis — useful to quickly see the dominant words of a text.

In SEO writing, unigram analysis quickly reveals whether your main keyword is sufficiently present, or conversely if it's drowned out by generic terms like "thing", "way", "which". A good text balances rich vocabulary and marked presence of the target keyword.

Bigrams (2-word sequences)

A bigram is a pair of words that appear side by side in a text. Unlike unigrams which isolate words, bigrams capture natural language associations: "dark chocolate", "electric car", "machine learning", "content marketing"… These associations often carry the real meaning of a piece of content.

Search engines like Google have used bigrams extensively since the Hummingbird Update (2013) and especially BERT (2019). Modern queries contain 2-3 words on average, and understanding their co-occurrence lets Google grasp the intent behind ambiguous queries.

SEO value of bigrams : Identify the key expressions Google associates with your topic. If "running shoes" appears 8 times in a Google top 10 but only 2 times in your text, that's a clear signal to strengthen. Bigrams also help detect semantic variations ("sports shoes" vs "running shoes") that enrich your semantic field without repeating.

Trigrams (3-word sequences)

A trigram is a sequence of 3 consecutive words. It's the analysis level closest to the long-tail queries users actually type: "best italian restaurant", "how to make money", "nike air force review". Trigrams reveal the exact phrasing of your content or your competitors'.

By analyzing trigrams from a top 10 SERP, you discover the recurring phrasings Google deems relevant for a query. Particularly useful for B2B writing, product comparisons, tutorials and evergreen content.

SEO value of trigrams : Spot high-potential long-tail expressions. If 7 articles in the top 10 contain "how to choose shoes", that's a sub-topic to address explicitly in your article. Trigrams also help detect keyword stuffing: the same 3-word sequence appearing 10 times in a 500-word text is a signal of over-optimization.

Why analyze the n-grams of your texts?

N-gram analysis goes well beyond simple counting. Here are the 5 most impactful use cases for content creators and SEOs:

• Semantic optimization — Verify your text covers the key expressions Google expects for your target query, without over- or under-optimization.
• Competitive analysis — Compare bigrams and trigrams from the top 5 Google results for your keyword: identify treated angles, recurring expressions, questions asked.
• Repetition detection — Identify phrasings you unconsciously reuse ("it is important to", "in this article we will") that weigh down reading.
• Editorial consistency — Verify vocabulary stays consistent across long articles (3000+ words) — a tired writer may drift from one term to another.
• AI content detection — Raw AI-generated texts (without editing) often feature stereotyped n-grams ("it is crucial to", "moreover", "however, it should be noted"). Spotting these patterns helps humanize a text.

How to interpret the results?

Here's a 4-step method to get the most out of n-gram analysis:

1. First look at unigrams to validate main keyword presence and spot overrepresented filler words.
2. Examine bigrams to ensure your target expressions appear at least 3-5 times in a 1000-word article.
3. Analyze trigrams to detect repetitive phrasings (more than 2 occurrences) and replace them with variants.
4. Compare your article's n-grams with the top 3 Google results — gaps reveal enrichment opportunities.

N-grams or keyword density: what's the difference?

Keyword density measures the frequency of a single given keyword in a text, as a percentage. N-gram analysis goes further: it reveals all recurring sequences, including ones you hadn't anticipated. It's a broader, more exploratory analysis.

In practice, both analyses complement each other: use density to validate a specific keyword, and n-grams to explore the overall semantic field and spot opportunities or drift.

Conclusion

This counter does more than measure: it helps you optimize your text so every word counts.

Frequently asked questions