Keyword Grouping Tool

Similarity Threshold

More granular grouping More general grouping

Minimum cluster size

Paste your keywords

Delimeter

Use column header names

Group similar keywords together in seconds!

FREE ONLINE TOOL – get similar keywords grouped together in seconds
Paste up to 10.000 keywords
… and download your instantly generated keyword grouping
Works for SEO, PPC, amazon, youtube and ebay keyword research grouping
Transforms your micro niche or nich keywords into bigger groups of keywords you can optimize on

How to use the Keyword Grouping Tool?

1) Paste your keyword data

Add up to 50.000 keywords of your favorite keyword source. You can use free sources like the google keyword planner, google trends or Ubersuggest. But of course you can also use paid keyword tools like moz, semrush or ahrefs. Using your Google Ads search terms is also a good keyword source. If you add additional metric columns to your queries our tool is making the aggregations for your keyword groups.

2) Customize your grouping preferences

Use cases are different. You have to possibility to fine tune the keyword clustering results with two parameters. By setting the minimum cluster size you avoid groups of keywords that contain to few keywords for your liking. The second parameter is the keyword group granularity. If you put the slider to most right position your keyword groups will be smaller in size and more granular.

3) Download Keyword Groupings

Depending on the size of your keyword list it will normally take some seconds before you are able to download the result. The generated CSV file will contain one column with the keyword group id and another column with the concatenated raw queries. If you provided additional metrics like keyword search volume or a calculated keyword value for your business then you will also find the aggregated numbers per keyword group in your file.

Import the keyword groupings to Excel or Google Sheets and refine your keyword clustering

Why you should use grouping techniques in your keyword research?

Optimize Keyword Topics

Google loves holistic content on your website. So does your website user. If you want to tell the full story to the user you should start thinking in keyword topics instead of single keywords. Keyword Grouping helps to discover relevant aspects of a big topic. You can use the grouping results in big content hub pages on a single holistic page but also link from there to several sub topics that appeared in some keyword clusters.

Keyword Niche Discovery

Everybody is searching for long tail keywords with low competition. When you just look at single keywords and judge them by their search volume you will probably be not successful in running a good long-tail strategy. When you are able to cluster multiple micro niche keywords together they suddenly appear as a new niche topic. Covering this keyword topic with good content will give good ranking potential.

More data mean better decisions

If you provided some additional metrics data to our keyword grouping tool you will realize that the numbers get bigger right away. A lot of keywords that are grouped together will cover a large amount of search volume. Without this grouping perspective you would miss these opportunities or you make probably wrong priorizations.

How does the keyword grouping logic work?

Preprocessing of keywords

First the keywords are transformed to lowercase. Every word within the complete search query is getting stemmed to its root form. To be able to use cluster algorithms every query is transformed to a vector representation. If you are looking for ways to visualize your clusters python also has plotting libraries or modules that are creating nice looking word clouds in just some lines of code.

Weighting the terms

In your free keyword grouping tool we are using TF-IDF weightings for every word in the vector space. There are different approaches that even go further. You can use for example word2vec embeddings to be able to cluster even on their semantic meaning. This works great if you build a custom model for all of your keywords.

Running Cluster Algorithms

There is also more than one way to do the keyword clustering. K-Means is a well known clustering algorithm that can also been used on our keyword vectors. Because finding a good value for “K” – in other words the numbers of clusters – we are using DBSCAN in our tool where the number of keyword groups is found by the algorithm.

Next level approaches for keyword grouping

Maybe our free keyword clustering tool offers everything you need, the stop reading at that point. If you want start coding to build th perfect fitting solution for your business, then you will find some nice approaches you can have a look at. Python is a great programming language for those kind of tasks – this will enable you to build your own SEO tools.

Python modules you should look at

Of course you can also do keyword clustering in R – python is just my personal choice for tasks like these. With sklearn, nltk, gensim and pandas you have very powerful modules to solve nearly every data science problem out there. All the mentioned cluster techniques like k-means or DBSCAN are part of those modules. If you are searching for a way of visualizing your keyword clusters you will find some plotting libraries as well as word cloud generators that do the job in just some lines of code.

Semantic Keyword Clustering

The next level of keyword grouping is to detect semantic similar queries and cluster them together. Modules like word2vec will make this possible. Instead of using pre-trained vector models you should consider building your own model with all keywords you know. You can also use the ranking webpages of these keywords and use its website content to further train the word2vec model. Word Mover’s distance (WMD) on top of this vector model will give you great results in semantic keyword grouping.