How to Group Keywords Automatically with the Keyword Clustering Tool

What is keyword clustering?

Keyword clustering is the process of grouping keywords in such a way that keywords in the same group (or cluster) are relevant to a particular website page.
Let's say you have a list of keywords: iphone 6s, iphone 7, bmx, mountain bike, road bikes and macbook. Here is what you'll get after clusterization the following clusters: {iphone 6s, iphone 7}; {bmx, mountain bike, road bikes}; {macbook}.

Why do you need keyword clustering?

• grouping of the related keywords;
• automatic analysis of a keyword pool;
• collecting the right keywords for specific pages;
• keywords distribution across pages for a site's SEO structure;
• searching for website keywords that fall outside all obtained groups.

How other keyword clustering tools work?

The most fundamental drawback of the majority of existing keyword clustering tools is that the clusters are formed based on the cluster's center — the keyword with the highest search volume. They find similar keywords which share SERPs results with it.

Here are some problems of such method cases:

How our keyword clustering tool works?

The aim of grouping keywords in Serpstat is to get clusters with the most semantically related keywords and not lose any of the keywords.

What keyword clustering methods Serpstat provides?

To group keywords for your needs you may select two major settings: strength and cluster type. The number of clusters and the keywords similarity depend on this choice.

Strength

There are three types of strength — Weak/Medium/Strong.

Cluster type

After clustering is finished, some keywords can fall into the "Unsorted keywords" directory. These are keywords that have no semantic similarity to the topic of the analyzed keyword set.

An alternative solution here is to create separate pages for these keywords or move them to one of the created clusters if you consider they belong there.

What clustering method to choose?

You can choose any pairing of the settings according to your needs. The decision should be based on the semantic similarity of the objects from your dataset.

If keywords are initially closely related, for example, sneakers of different brands, you should choose "Strong"+"Strong" or "Strong"+"Weak" so that only the closest synonyms are combined into a cluster. As a result, you'll get lots of clusters to use for separate pages or specific categories.

In the case of various products and services, for example, you are collecting keywords for a multi-product store or medical center with a full range of health-care services, it's worth selecting "Weak"+"Weak".

How to use the "Keyword Clustering" tool?

After the keyword clustering is done, the project will look like this:

Now, let's look through all the indicators and figure out what it all means.

Project navigation

In the left block, we see a list of clusters.

On the right block, you see all keywords within a selected cluster with additional information:

Tip: if you see that some keywords are irrelevant to the cluster or you would like to add more keywords to the specific cluster, move them around — use "Operations".

You'll also use buttons at the top:

Video tutorial

You may have a better perception of what keyword clustering is and how it works by watching the video.

How are credits spent?

Number of keywords * 5 = the number of Tools credits spent when creating or updating a project.

Example: 300 keywords * 5 = 1,500 credits spent.

Credits are not spent when you change Strength and Cluster type only.

Check how many credits you have left in My account.

Use cases

Keyword clustering may be used for different goals by different specialists: SEO specialists, blog editors, content writers, marketing analysts.

Based on formed clusters, you can:

• Create or improve a website structure.
• Create new landing pages.
• Create new website sections.
• Create new filters for e-commerce websites.
• Plan future blog content.
• Optimize product listings.
• Optimize titles and descriptions.
• Optimize contextual advertising.
• Analyze an industry, a niche, or a specific competitor.