If you’re not too familiar with keyword clustering, it may seem like a complicated strategy reserved only for SEO experts. But good news: keyword clustering is easy to do.
So what exactly is keyword clustering? In simple terms, keyword clustering is the practice of grouping together similar keywords that share common search intent. This makes it an easy way to tell which keywords should be included in the same article.
In short, keyword clustering has two benefits:
- Allows you to rank for more keywords for the same article
- Prevents keyword cannibalization
The first benefit is straightforward. The more you cover a particular topic, the more chances you have to rank for additional keywords and get more traffic.
The other benefit of keyword clustering is to help prevent keyword cannibalization. Keyword cannibalization is when you have two articles trying to rank for keywords that are too closely similar. For example, if you had “how to cook a pizza” and “how to bake a pizza”, even if those keywords are technically worded differently, they really mean the same thing. If you wrote an article on each of those keywords, Google would only rank one of those pages.
Keyword clustering is the practice of grouping together similar keywords that share common search intent. This has two benefits:— Ben @ Keyword Chef (@KeywordChef) March 11, 2023
1. Allows you to rank for more keywords for the same article
2. Prevents keyword cannibalization
What tips do you have for keyword clustering?
Now that we understand what keyword clustering is, we can learn how to do it.
How to cluster keywords
In early SEO days, keyword clusters were based on the linguistics of the keywords themselves. Today, however, clustering is best done by matching search intent, also known as SERP-based clustering.
With SERP-based keyword clustering, SERPs are analyzed for every keyword. If two keywords meet the minimum number of matching links between their SERPs, we can assume they share the same search intent. Usually, the minimum number of matching links is 3 or 4. The higher the number, the more relevant the keywords will be to each other.
As you can probably see, this is not an easy process to do manually. It’s quite time-consuming to check the SERPs for every keyword and compare links. Thankfully, we can cluster keywords easily in just a few clicks using Keyword Chef.
Clustering Keywords in Keyword Chef
Let’s see how this Keyword Clustering Tool feature works in Keyword Chef…
The first step to clustering keywords is to create a keyword report. If you want to target a country other than the United States, be sure to change the geo-location settings first. This can be done by clicking on the globe left of the search. This is important because Keyword Chef will be fetching the search results for each keyword.
Once we have our location set, we can create a report one of two ways:
- Importing a custom list of keywords
- Performing a keyword search
For this example, I’ll be importing a list of keywords manually by clicking the import button right of the search bar.
Note: you can only cluster keywords if there are fewer than 10,000 keywords in your report.
Once the keywords are imported, click the ‘Get All SERPs’ button (this will require paid credits). This will load the SERPs for all the keywords in your report. Once complete, you’ll find a ‘Similar’ badge next to your keyword. Clicking this badge will reveal clustered keywords that have 3 or more matching links in the SERPs to the main keyword.
Keyword Chef also tells you the search volume and match percentage. The match percent is how similar the keyword is to the main keyword.
What should I do with the clustered keywords?
A common question people ask is how to use Similar Keywords. People often ask questions like:
- How do I use clustered keywords in my article?
- Should clustered keywords be used as subheadings?
- Do I need to include all the clustered keywords?
Like most SEO answers, it depends – and it depends on the keyword.
Here’s a guide you can to help decide how to handle them:
- Close variants: Close variants are keywords that mean the same thing but use different words. For example, “how can you tell if an avocado is bad” and “when avocado is bad” are really the same question and will have a high match %. In these instances, you can include the similar keyword naturally in your article.
- Related but different: Unlike close variants that mean the same thing, related but different keywords mean something different but are still closely related. For example, “how can you tell if an avocado is bad” and “can overripe avocado be eaten” are different questions, but many people who want to know if an avocado is bad also want to know if it can be eaten. In this case, you could make the similar keyword a subheading.
When it comes to how many similar keywords to include, It’s not necessary to include all of them. Oftentimes, there are dozens of keywords that would make including them all quite difficult.
If you want a keyword clustering tool that has SERP-based clustering, get started by registering an account on Keyword Chef.