Keyword Research has been made easy to carry out because of amazing tools like ahrefs and semrush.
But segmenting these keywords to determine what pages need writing can be tiresome and time-consuming.
Many SEOs fail when carrying out their content roadmaps because:
One web page can rank for multiple keywords, but too many SEOs create pages targeting multiple intents
Old school SEOs create one page per single keyword and this causes competing pages for the same keywords
Finding the right balance to meet the searchers intent behind the query will create you amazing content roadmaps.
Understanding the one page for one corpus is critical to your SEO tactics.
Are you still carrying out the keyword clustering manually or using an advanced AI tool to do the heavy lifting?
What Is Keyword Clustering?
Keyword clustering is segmenting keywords into clusters relevant to the search intent.
SEO specialists cluster phrases after keyword research is carried out into small groups.
The small groups of keywords are what determines the pages you need writing on your website.
“Using a Keyword Clustering Tool will gain you a significant advantage over your competition and optimize your on-site page architecture to align with what Google wants to see”
You are removing the guesswork on whether some keywords needs to be on its own page or added to an existing. The keyword clustering utilises the SERPs to determine this answer and means you are following what Google wants to see on your pages.
To achieve higher rankings in the SERPs you need to create topical articles around the whole topic of your site.
Use SERP Overlapping to find phrases with similar search results helps to create a list of topics and phrases that should be included in an article.
That’s called keyword similarity, and it refers to the number of the same results in the SERP.
This research technique allows us to diagnose users’ intentions and to discover great content ideas.
There is an awesome side-effect, too — we narrow the number of relevant threads and keep proper relevancy to the main keyword and topic.
Goodbye Single Keyword Research to welcome the New Era of Topical Optimisation
The on-point list of long-tail keywords is another outcome of this kind of approach.
The appearance of phrases with many words in the content allows ranking not only for the main keyword but a wide range of relevant, converting, and attractive long-tail terms.
You can rank for more keywords with the same amount of content!
Best Keyword Clustering Tools
Keyword clustering can be a fully automated process performed by keyword clustering tools.
From our research here are the best keyword clustering tools:
Keyword clustering is based on the search results that a search engine shows for a certain search query.
Some tools like keyword cupid base their results on the top 100 with a weighting system applied.
The general algorithm of keyword clustering includes four steps that a tool completes to cluster keywords:
The tool takes keywords one by one from the list and sends them as search queries to the search engine. It scans the search results, pulls the ten first search listings, and matches them to each keyword from the list.
If a search engine returns the same search listings for two different keywords and the number of these listings is enough to trigger clustering, two keywords will be grouped together (clustered).
A minimum number of matches in the search results that trigger keyword clustering is called the clustering level. The clustering level is customizable, and most tools allow changing it in the settings prior to the keyword clustering.
If a tool finds no matching URLs on the first page of the search results, these keywords are sent into a separate group.
Apart from the clustering level, there are also different types of keyword clustering that affect the way all keywords within one group are linked to each other.
The type of keyword clustering can be set prior to the clustering also.
Keyword Clustering Level Settings
As clustering levels is customisable then what is the best level to set in the settings?
The keyword clustering tools allow changing it in the settings prior to the keyword clustering.
The clustering level affects the number of groups and keywords in the group after clustering.
Higher Clustering Levels
The higher clustering level (7-10 matching results) produces more pages to write with fewer keywords in every group.
This happens due to a minimum chance to have 7-10 matching documents on the search results page.
It would need to include almost all pages in the SERPs for both searches which is unusual.
Having higher clustering levels can yield incorrect groupings and you could end up writing two pages on a very similar topic causing content cannibalization issues.
Lower Clustering Levels
The lower clustering level (1-2 matching results) produces fewer pages to write with a lot of keywords to cover on the singular web page.
This happens due to a high chance to have 1-2 matching documents on the search results page.
Having lower clustering levels can yield incorrect groupings and you could end up writing one-page covering multiple corpora (not matching search intent).
Perfect Clustering Levels
The perfect clustering levels for grouping keywords is 3-10 matching results.
You are now getting enough different groups with a higher quantity of keywords than the higher clustering group.
There is a debate on the settings whether to tweak the lower number to the 2 or 4 figure.
Google Is Not Always Correct
Google is still stupid comparing to an algo but all in all, we are trying to rank for a machine, so structuring content and queries around it make more sense than following our own bias.
Google isn’t always right and to rank sometimes you might have to follow google SERP
The thing is that a tool can only show the door, it will never be able to open it.
So a user who interprets the world is always needed, that’s why a keyword clustering tool is never going to replace a skilled SEO.
It’s only meant to help to make sense of the initial organization of the groupings.
Why Create Topic Clusters for SEO
Covering a topic in its entirety is what gives you the expertise in Google eyes.
If you cover all topics related to a subject you are showing to search engines you understand everything within this niche.
Creating topical clusters is what gets you past authority wall so the minute you publish a new article on that particular topic you jump straight onto page one as passed the EAT guidelines set out by Google.
This video shows nicely the importance of creating topic clusters for SEO:
Instead of optimising your website for single keywords, focus on building the site out to dominate a topic in its entirety with multiple pages and blog posts.
Each page or post will target a tightly correlated group of keywords, but all built around a slightly broader topic.
That gives you a chance to dominate a topic through multiple related pages, each focused on specific visitor intent.
That’s tough to beat because you are correlating content to a page level but creating the clusters to become the expert in the whole topic area.
Keyword Collection Techniques
The keyword clustering tools only group together keywords you load in so the keyword collection techniques are very important.
Here are the best techniques to capture keyword collection:
Google Search Console Query Data
Ahrefs to analyse competitor organic keywords
Semrush to search a broad seed topic
Answer the Public to pull in question-based phrases
People Also Ask
Google Suggest Autocomplete
Collecting the dataset of keywords from the techniques above will cover the topic in its entirety for your grouping to create a list of topically related articles.
If you know the niche very well and understand the intent of the searches this is a very accurate method.
The problem is it is not scalable and you need to be an industry expert to be able to carry out this manual clustering process.
It is vulnerable to human error and not clustered based on Google algorithms.
Semantic Clustering Process
The semantic clustering process uses various methods on comparing words in the target keywords.
The keywords are grouped based on semantic commonness which is similar to the Levenshtein method.
In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences.
The semantic is certainly scalable and ok for an initial grouping exercise.
The problem is that it’s not accurate and clusters phrases together which might be close in linguistic search strings but could have completed different intent and belong in a different corpus SERP intent.
Examples of where the semantic clustering will fail is grouping together phrases like “running shoes” and “running socks”. In semantic commonness, you can see why these will be grouped together.
But within Google algorithms clustering this will bring a completely different set of results because almost closely related they will have totally different intents in the search.
Similar SERP Clustering Process
The similar SERP clustering process is based on Google algorithms to help cluster your keywords.
The search term is searched and compares results in the search engine results pages for overlapping results.
This is next level compared to manual or semantics because it is much more data-driven by using Google algorithms to find this grouping.
The problem with this method is what settings do you allow with splitting the pages (two results overlapping, three webpages to overlap or more?). And if you choose three search results matching then will this take into account the positions like if it ranks in 8,9,10 but all the others in better results 1-7 are different then should this be grouped?
In SEO the term clustering is a group of keywords you can rank together on the same webpage.
Manually trying to work out keyword intent is failing us all.
SERP intent is so important and beats out keyword intent.
Keyword clustering helps to see concepts behind keyword strings
You’ll spend hours identifying and mapping keywords, but if you don’t take it one step further to find SERP intent, your content might never rank.
Keyword Clustering tools will provide you with the following goals:
Understand every page you need to create, matching Google SERPs intent
Complete years of keyword research mapping out within an hour
Allow staff with minimal knowledge to do keyword research and content planning effectively
Reduce keyword research and search intent errors by using Google itself
SERP intent will let you know exactly how to target that blog post to match what Google wants to rank.
The keyword clustering tools can organise and segment the grouping of words to match the search results for what pages you need to write.
There are many questions related to clustering below.
Do Off-Topic Clusters Affect Your Other Content Hubs?
Michal from Surfer SEO believes off-topic articles can affect your main money terms.
But if that’s the case how can sites rank for multiple topics?
Like affiliates rank for garden tools, men’s shavers and then televisions.
Or do you think what might be happening is google gives your domain a CONTENT OVERALL SCORE? Like it does “domain authority” for links.
Then if you go off-topic that’s fine as long as the content is high quality and you cover that whole topic.
But if you add content that’s not ranking it can lower your overall DOMAIN CONTENT SCORE?
I’m just trying to get my head around how some off-topic pages can affect other well-written articles in a different cluster.
I would love your input on this interesting statement here.
I’m a full-blown Search Engine Optimization specialist earning the majority of my income from SEO-focused endeavours, including affiliate marketing, lead generation, as well as SEO services. Love travelling the world networking while working on my laptop. Life is a perception of your own reality. You have no excuses and should be making memories every single day.