Türk SEM · SEO Tool
Keyword Clustering
Enter a seed keyword. See which keywords one page can cover and which ones need a page of their own, based on measured search result overlap.
Cluster tightness
Balanced: the threshold sits at the middle of the measured tie distribution. Visitors get 5 queries a day, members get 25.
Why clustering is the first step of a content plan
If you build two pages for two keywords that serve the same need, those two pages compete with each other. Google has already decided which queries represent the same need, and you can see that decision in the search results. If two queries return the same pages, they are one page. Clustering does not guess that decision, it measures it.
How we measure it
A candidate list is expanded from your seed using Google suggestions. For each candidate we then read, from our own data source, how many pages rank for both that keyword and its neighbor. That number is a tie strength. Clusters are built with the centroid method: the highest-volume keyword becomes the center, and only keywords tied to the center above the threshold join it. Every member therefore has direct evidence with the center, which stops unrelated keywords from chaining into the same cluster.
The limits, stated plainly
Our data source is strong on head and mid tail and weak on long tail: for rarely searched terms it may return neither volume nor ties. That is why we write "no data" rather than zero, and why we do not label unclustered keywords as "needs its own page". Overlap is a strong signal but not a sufficient one. Before you publish a cluster, check by eye that its keywords really do share one intent.