How To Group Keywords Automatically With The Serpstat "Clustering" Tool
Updated and improved tool
Eugenia Pisarenko
Customer Support & Education Specialist at Serpstat
To compose the structure of a site correctly, distribute keywords for certain pages manually, draw up a technical assignment for writing articles to a copywriter, separate requests into commercial and informational — all these takes you a lot of time? In this article, you will learn how our updated "Clustering" tool can help you reduce spent time on these processes.
By the way, the new version of the tool now groups а list of keywords into clusters faster, and you can add up to 50,000 keywords to projects. We have simplified cluster hierarchy and improved report navigation.
Read about the new version of the tool below!
By the way, the new version of the tool now groups а list of keywords into clusters faster, and you can add up to 50,000 keywords to projects. We have simplified cluster hierarchy and improved report navigation.
Read about the new version of the tool below!
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 semantic core;
- 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.
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 semantic core;
- 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:
Here are some problems of such method cases:
1
resulting clusters may either contain keywords without a strong semantic similarity;
2
too many clusters that could have been merged into larger clusters appear;
3
parsing search volume data takes time, additional costs and sources.
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.
1
We don't set a cluster keyword center with the highest search volume.
2
Serpstat considers all keywords analyzing genreal URLs in SERPs.
3
We use a one-level cluster hierarchy.
4
Serpstat checks the connection strength of all analyzed keywords according to your selected settings.
Connection strength — is the number of identical URLs in keywords' top-30 search results. Thus, the highest number of mutual results is 30 URLs.
What keyword clustering methods Serpstat provides?
To group keywords for your needs you may select two major settings: strength and cluster type. The results with the number of clusters and the similarity of their keywords depend on this choice.
Below you can see examples with some pairs of various settings of strength and cluster type that suits different cases.
Below you can see examples with some pairs of various settings of strength and cluster type that suits different cases.
1) There are three types of strength — Weak/Medium/Strong.
- By setting "Weak" parameter, the keywords with minimum 3 mutual URLs in top-30 search results will be combined into a cluster;
- With "Medium" strength, keywords need to have 8 common URLs;
- "Strong" strength sets 12 common URLs in top-30 search results in a single cluster.
2) There are two cluster types to choose from: "Weak" and "Strong".
"Weak" parameter tells the system that a cluster can be created if at least one pair of keywords has common URLs in top-30 search results (depending on the previous Weak/Medium/Strong strength).
- By setting "Weak" parameter, the keywords with minimum 3 mutual URLs in top-30 search results will be combined into a cluster;
- With "Medium" strength, keywords need to have 8 common URLs;
- "Strong" strength sets 12 common URLs in top-30 search results in a single cluster.
2) There are two cluster types to choose from: "Weak" and "Strong".
"Weak" parameter tells the system that a cluster can be created if at least one pair of keywords has common URLs in top-30 search results (depending on the previous Weak/Medium/Strong strength).
"Weak" cluster type
"Strong" one requires all keywords in a cluster to have common URLs in top-30 search results (the requirement for the number of common keywords is defined in the previous step where you selected Weak/Medium/Strong clustering).
"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 and should be removed from the dataset.
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.
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".
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 Keyword Clustering tool?
Let's create a project and launch the keyword clustering.
1. Go to the side menu and open "Clustering and TA" tool.
1. Go to the side menu and open "Clustering and TA" tool.
2. Click on "Add a new project" button.
3. Enter a project name and a domain (if you want to run a text analysis for a particular domain), click "Next".
4. Then fill the form with search engine (Google or Yandex); country, region (optional) and town (for Google optional; for Yandex not optional).
5. Select strength and cluster type and click "Start".
6. Paste the list of keywords or import them from .csv or .txt files and click "Start".
Please note that for 1 keyword you spend 5 credits (you see this information in the calculator of spending credits below).
Please note that for 1 keyword you spend 5 credits (you see this information in the calculator of spending credits below).
Make a cup of coffee and sit back, grouping takes some time :)
7. After a while, you'll get something like this in the results:
In the left block we see the list of clusters.
- the number of clusters in this project is displayed in brackets (1) next to the name of the "Clusters" column;
- the "Clusters" column displays the names of the created clusters (2);
- the "Keywords" column shows the number of keywords in the cluster (3).
- the number of clusters in this project is displayed in brackets (1) next to the name of the "Clusters" column;
- the "Clusters" column displays the names of the created clusters (2);
- the "Keywords" column shows the number of keywords in the cluster (3).
On the right block you see all your keywords grouped into clusters with some additional information:
1. Volume — how often users type this keyword into a search per month.
2. Every keyword has its connection strength. It shows how related to the cluster's subject this keyword is (from 0 to 100%).
3. Homogeneity shows the strength of connection between keywords (from 0 to 100%).
4. URL that ranks for the keywords in the cluster. If you add a domain while creating a project, we will display the URL which suits the cluster's subject the most. If you don't specify the domain, you can add URL manually when launching text analysis.
2. Every keyword has its connection strength. It shows how related to the cluster's subject this keyword is (from 0 to 100%).
3. Homogeneity shows the strength of connection between keywords (from 0 to 100%).
4. URL that ranks for the keywords in the cluster. If you add a domain while creating a project, we will display the URL which suits the cluster's subject the most. If you don't specify the domain, you can add URL manually when launching text analysis.
Let's pass to some additional options when you click on drop-down menu:
1. Click on "Add keywords" to add new keywords to the project (after that you need to click the button "Refresh clustering").
2. If you want to delete some keywords from the cluster, tick them and click on "Delete keywords".
3. The "Move to unsorted" button allows you to move selected keywords to the "Unsorted keywords" directory.
4. If you need to move selected keywords to the other cluster click the "Move keywords to..." button.
5. To delete a cluster, click on the "Delete cluster" button.
2. If you want to delete some keywords from the cluster, tick them and click on "Delete keywords".
3. The "Move to unsorted" button allows you to move selected keywords to the "Unsorted keywords" directory.
4. If you need to move selected keywords to the other cluster click the "Move keywords to..." button.
5. To delete a cluster, click on the "Delete cluster" button.
6. By clicking on "Show metatop" you see the list of major competitors in SERP for keywords from this cluster (top-30). The higher a page's rank in the meta-top, the more relevant it is to the cluster's topic.
7. Change the name of clusters, create new ones, delete and move keywords between clusters. Everything is for your convenience.
That's finally it! Try our new tool ;)
That's finally it! Try our new tool ;)
No additional payments, "Clustering" tool is included to your pricing plan. Learn more about pricing plans and other on the page SEO checking tool.
Video tutorial
To learn about the tool faster, watch this video and start working now!
Don't hesitate to ask, if you have any questions. We'll do our best to answer all of them ;)
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