Do you have to do keyword research for the website or optimize it? The first thing you should do (and everybody knows it) is to match keywords to pages. Forget about optimization for “keyword strings”; it’s out of date. To go with the times and make an efficient SEO, I suggest implementing a smart approach to keyword research: keyword clustering.
In this article, I’m going to show you how to automate this process. After reading it, you’ll be able to optimize one page for the whole group of keywords.
What is Keyword Clustering?
To start with, let’s figure out what the term “Keyword Clustering” means and where you can use this process.
Semantic keywords (related by meaning to the primary keyword) are necessary to make your content more natural and SEO optimized.
Keyword clustering is a particular practice to segment keywords into groups (clusters) relevant to each page of the website. To say in simple words, it is a grouping of a long keyword list by relevancy. It means that you take relevant keywords and arrange them together into several groups. Keywords in the same cluster are more similar to each other than to those in other groups.
There is no specific base which contains info about the properties of objects keywords describe and the context of their use.That’s why Serpstat keyword clustering algorithm is based on SERP results through comparing the search results for different keywords.
Such clustering will help you to:
- Create a semantic core of the website;
- Understand the topic of the page or the whole domain better;
- Optimize the content for several keywords, instead of the only one;
- Learn subtopics inside the niche;
- Expand the content with related terms and phrases;
- Make a clear structure of the material.
How To Cluster Keywords
The most popular and obvious way to group keywords is to find a common word in the strings and identify each phrase which includes this word. Then we can play with the keywords list in Excel.
For example, you have the website about cryptocurrency. The separate cluster which you can make would consist of all the phrases containing a modifier “bitcoin.”
This method of clustering is outdated and limited as search engines are constantly developing and improving. Now we need to pay attention to related concepts even without the same terms to describe them.
A great modern way of clustering is using specific tools. Serpstat is one of them and it goes beyond word matching. It analyzes Google search engine results, finds similar URLs ranking for queries, and makes conclusions related to the quantity of results overlap for two SERPs. Use the tool to discover more new connections and concepts of your topic.
Serpstat Keyword Clustering Tool
Below is the process of using Serpstat Keyword Clustering Tool.
To group keywords, go to Tools > Keyword Clustering and Text Analytics.
Here you should create a project, add its name, website (if necessary), and the list of keywords. You can do it manually or import from *csv or *txt file. Then you will be able to choose search engine, country, region and a city (if your business is regional).
After this process you’ll get the next table:
And here I suggest you’ll need some help and explanations.
To talk about linkage strength:
Weak – keywords must have at least 3 common URLs in top-30 search results;
Medium -5 common URLs;
Strong – at least 7 common URLs in top-30 search results have to be in the cluster.
Type Of Grouping:
Soft -a group can be created if at least 1 keyword pair have 3 or 7 common URLs;
Hard – all cluster keywords must have 3 or 7 common URLs.
When you choose these parametres, you should pay attention to the semantic similarity of the objects. Point Strong + Hard (or Soft) if they are related closely. And if you have various products, choose Weak + Soft, and you’ll get a lot of small groups.
When you choose this points, you should wait for a little and then you’ll get the clusters.
At this report, the Strength means how close a keyword is to the topic of the cluster (from 0 to 1).
Also, you can manage the given groups manually (delete them, shift words, etc.).
Text Analytics As An Essential Addition To Serpstat
Serpstat text analytics gives recommendations on how to improve your on-page SEO: what keywords Title, H1, Body should include.
Text analytics analyzes the content on the landing page, the list of keywords from a cluster and a set of pages from the Top 10 search results for keywords from the list.
This feature is helpful while creating a semantic core and creating a task for the copywriters as well.
As a summary
Keyword clustering is a useful method for SEO specialists as it helps them to do a keyword research for the domain and separate URLs, conduct SEO, create tasks for copywriters and write content for the website.
Clustering by a tool takes less time and resources compared to manual. One of the best services with such feature is Serpstat. It is clear and easy to manage. The one thing you should know is the meaning of linkage strength and types of grouping. This knowledge will help you to get the most appropriate and exact clusters to your website.