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Keyword research has changed a lot in the past few years. Instead of targeting a single keyword string, we now create reader-centric content that answers search queries.
Yet understanding how people search remains important. Knowing what they type in the search box and how often can help understand their needs.
But it’s not easy.
Google has stated that 15% of daily searches are “new” — i.e., queries it has never encountered. Hence people search in different and often unpredictable ways, using hundreds or thousands of word combinations for the same thing.
As a result, keyword lists are often cluttered and seemingly endless. Making sense of those lists — containing the same or slightly altered phrases — is very challenging.
“Keyword clustering” can help.
Keyword clustering is not new. It’s a technique for grouping keywords by a common modifier, a word or phrase that extends the seed term.
For example, if “ecommerce platform” is the seed keyword, “best” could be a modifier, producing the following keyword cluster.
- best ecommerce platform for wholesale
- best ecommerce platform for customization
- best ecommerce platform for handmade items
- best ecommerce platform in us
- best multi-store ecommerce platform
- how to choose the best ecommerce platform
- best multilingual ecommerce platform
Clustering remains useful because it helps discover low-volume keywords, which are easy to overlook but potentially important to your shoppers.
How to Cluster
There are several ways of clustering your keywords.
A free method is to use the conditioning formatting feature in a spreadsheet to color-code keywords sharing the same modifier. The most popular modifiers are easily located by spotting repeated colors. The process, while helpful, risks overlapping the colors when one keyword contains two or more common modifiers.
A free method of keyword clustering is to use the conditioning formatting feature in a spreadsheet to color-code keywords sharing the same modifier.
Semrush offers a better way. It identifies the most common modifiers and shows the keyword groups and subgroups containing each one. Run Semrush’s “Keyword Magic Tool” and click modifiers in the left panel. Each will open more groups and show how many keywords are included in them.
Clicking the modifier will open the list to the right of keywords containing it. For example, the group in the screenshot below in the feedback section contains both “free” and “software.” Fifty-four keywords include “free.”
Semrush’s “Keyword Magic Tool” identifies the most common modifiers and shows the keyword groups and subgroups containing each one.
Keyword Magic Tool is included in every Semrush plan, starting at $119 per month.
The tool is beneficial in understanding all kinds of searching patterns of your target audience. But it misses many phrases with the same intent but slightly different modifiers.
For example, a page targeting “easy photo editing software” would benefit from knowing how people express that need in the search box, including closely related phrases, such as:
- easiest photo editing software
- photo editing software for beginners
- simple photo editing software
And that’s where search-intent-based keyword clustering makes sense.
SE Ranking offers a keyword clustering feature inside its Keyword Suggestion Tool that groups keywords based on the number of overlapping URLs ranking for those terms in Google. Set the number of overlaps from two to nine. The more URLs overlap for two separate search queries, the closer those queries relate to each other.
SE Ranking’s Keyword Suggestion Tool groups keywords based on the number of overlapping URLs ranking for those terms in Google.
SE Ranking uses this signal to identify keyword clusters, i.e., closely related keywords that should be included in one group. This keyword grouper is included in all plans, starting at $40 a month, but is charged separately at $0.004 per keyword.
Clusters for SEO
There’s no single strategy for using keyword clusters in search engine optimization. All keyword groups should be manually reviewed and treated differently.
- Content ideas. One cluster may include keywords of helpful content ideas, wherein each keyword within the group is used to create a standalone page, such as the “best ecommerce platform” example. All pages within this topic cluster are interlinked, with a parent-pillar page referencing each in that group. In our example above, the parent page could be titled “best ecommerce platforms,” with each subpage targeting a keyword (and search intent) within that group.
- Single-page optimization. Another keyword group could optimize a single page. When the search intent is practically the same, there’s no need to create multiple pages targeting each keyword. Instead, create a single page that would mention other modifiers. For example, a single page could target “easy photo editing software” and other keyword options, such as “for beginners.”
- Better insights. Finally, some groups exist solely to understand how people search, such as knowing how folks query for free photo editing software. Semrush allows the exclusions of certain clusters from keyword research lists to remove clutter. That’s another way to use clusters: unclutter lists to identify important keyword phrases and modifiers more easily.
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