AI semantic method
Groups by meaning with a language model — handles synonyms, paraphrases and multilingual lists. 20 runs/day on Pro.
The free Google SEO method is preselected. For true meaning-based grouping, switch to the AI semantic methods on Pro.
7 benzersiz algoritma: Jaccard, BM25, PMI-semantik, Ward-hiyerarşi, DBSCAN, Levenshtein
💡 Desteklenen her format: frekanslı veya frekanssız, herhangi bir ayırıcı (sekme, noktalı virgül, boşluk vb.)
Google gibi arama amacı ve varlıklara göre gruplandırır
Arama amacı kümeleme
Daha az = kümede daha fazla anahtar kelime
Daha fazla = daha az nihai küme
From a raw keyword list to a page plan in a few minutes.
Lists with synonyms, paraphrases and mixed wording work best.
Semantic and Google SEO modes are free; AI semantic methods add language-model understanding on Pro.
“Cheap flights” and “low cost airfare” end up in the same cluster.
Use each group as a page or a section in your content plan.
Language-model understanding on top of classic similarity.
Groups by meaning with a language model — handles synonyms, paraphrases and multilingual lists. 20 runs/day on Pro.
Semantic grouping tuned to how search engines treat intent and page coverage.
Vector-similarity grouping in your browser on the Free plan.
100 AI runs per day on Agency for large client portfolios.
Choose AgencyWhat changes in your workflow once grouping is automated.
Queries with different wording but the same need end up on one page.
Avoid writing two articles that answer the same question.
Semantic grouping copes with mixed-language and transliterated lists.
Related groups form clear hubs and supporting pages.
Built for people who turn keyword research into pages.
Build topical maps that mirror how people search.
Plan topic clusters and pillar pages.
Group keywords in many languages consistently.
Anahtar kelime kümeleme ücretsizdir ve kayıt gerektirmez. Ücretli planlar limitleri kaldırır ve AI semantik yöntemlerini, Content Analyzer'ı, The Force'u, SERP kümelemeyi ve toplu raporları etkinleştirir.
Başlamak için
$0/mo
Temel kümeleme, kayıt gerekmez
SEO uzmanları için
$29/mo
Günlük SEO çalışmaları için eksiksiz araç seti
Ajanslar ve ekipler için
$89/mo
Müşteri projeleri için yüksek hacimler ve toplu raporlama
Büyük şirketler için
Özel
Özel limitler, SLA ve entegrasyonlar
30-day money-back guarantee · Cancel anytime
Günlük kullanım limitleri her 24 saatte bir, aylık SERP ve Ahrefs hacimleri ise her ay sıfırlanır. Planınızı istediğiniz zaman değiştirebilir veya iptal edebilirsiniz.
Semantic grouping puts "how to remove coffee stains" and "getting coffee out of carpet" in the same cluster, because they express the same need. Word-matching methods leave them apart. For informational content — where searchers phrase the same question a dozen ways — that difference decides whether a page covers a topic or a fragment of one.
A word-matching method needs shared tokens. Real search behaviour does not cooperate: people use synonyms, regional wording, abbreviations, brand names in place of categories, and questions phrased as statements. Every one of those variants is demand for the same page.
Semantic grouping compares the underlying meaning of queries, so those variants converge. In practice, semantic runs on informational sets produce noticeably fewer orphan keywords — single-keyword clusters that should have joined a group.
Meaning-based grouping can over-merge product keywords. "iPhone 15 128GB" and "iPhone 15 256GB" mean nearly the same thing semantically and belong on different pages commercially. Catalogue and SKU keyword sets are better served by lexical or specialised e-commerce modes that respect attribute differences.
On paid plans, semantic runs are supported by a language model that evaluates whether queries express the same underlying task, then labels each resulting cluster with a human-readable topic name. The output is easier to hand to a writer than a numbered group.
Because model-assisted runs cost compute, they are limited to 500 keywords per run. The recommended pattern is to cluster the full list with a standard method first, then re-run the ambiguous or high-value sections with AI assistance.
Two habits keep quality high. First, read the largest cluster in every run — over-merging always shows up there first. Second, sort clusters by total search volume and check the top ten manually, because those decide most of your traffic.
Anything commercially critical should then be confirmed against live search results before you commit it to the content plan.
Run a semantic pass over your most valuable keyword sections and get writer-ready topic labels.
Try semantic groupingFor informational content, usually yes. For product and category keywords where small attribute differences matter, lexical or catalogue-specific methods are safer.
Yes, including non-Latin scripts and right-to-left languages. Keep one language per run for the cleanest results.
Model-assisted runs consume compute per keyword. The limit keeps runs fast and pricing predictable; standard methods handle the full per-run limit of your plan (up to 50,000 keywords on Agency).
Yes. Cluster labels are editable before export, and merges or splits you make by hand are preserved.
The Free plan clusters up to 500 keywords per run, 5 runs per day with a free verified account. Without signing up you can try one preview run of up to 100 keywords. AI semantic methods, SERP clustering and bulk Content Analyzer reports are part of the paid plans.
Pro processes up to 15,000 keywords per run and Agency up to 50,000. Both include AI semantic methods, Content Analyzer, The Force, SERP clustering and bulk Content Analyzer reports with plan-specific monthly volumes.
Yes. Paid plans can be cancelled at any time, and every subscription comes with a 30-day money-back guarantee as described in our Refund Policy.
Paste a list above and get clusters in seconds on the Free plan. Upgrade only when you need bigger runs or AI methods.