Lightning-fast keyword clustering tool that transforms 5,000+ keywords into optimized groups in minutes. Advanced soft & hard algorithms with unparalleled accuracy. Support for 70+ languages. Trusted by leading SEO professionals worldwide.
The first 7 days are free.
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Check out the features of the tool and get detailed instructions on how to use the keyword grouping tool.
❌ Takes 8+ hours to group 1000 keywords manually
❌ 30% error rate in semantic relationships
❌ Miss competitor clustering opportunities
❌ Can’t handle multilingual projects
✅ Our advanced clustering solves this in 5 minutes
No more guesswork or manual mapping of keywords to URLs. Our advanced Keyword Grouper analyzes your keyword list and automatically matches them to the most relevant target URLs based on semantic intent and content relevance.
By grouping similar keywords using advanced semantic algorithms and aligning them with true user search intent, you can increase organic visibility by 340% and achieve dramatically better SEO results.
Transform your Google Ads performance with precision keyword grouping for highly relevant ad groups, improved Quality Scores up to 8.5+, and reduced cost-per-click. Export results directly to Google Ads Editor format for instant campaign setup.
The soft and hard approaches offer distinct benefits for your keyword research. Soft clustering helps identify semantic relationships and similarities between keywords, while hard clustering allows you to categorize and group keywords based on more complicated criteria. By using both approaches, you can increase the relevance and performance of your keyword research, resulting in better SEO results.
Our keyword grouping tool starts by selecting the highest search volume keyword and compares it with other keywords based on the number of common URLs in the Google TOP. If the number of matches meets the specified grouping precision, the keywords are grouped together. It’s the so-called soft grouping approach. Our tool then performs a thorough analysis to guarantee that related keywords are appropriately placed in the most relevant keyword groups.
The algorithm begins by selecting the keyword with the highest search volume and compares it to other keywords based on the number of common URLs in the Yandex or Google TOPs. It further verifies that all keywords within a group share the same URLs in the SERP TOP. When the number of matches satisfies the specified grouping precision, the keywords are seamlessly clustered together, forming cohesive and optimized keyword groups.
Our way to group keywords offers a strategic approach to organize and optimize your keywords. With the soft and hard approaches, you can group keywords based on semantic relationships or specific criteria, respectively. Using tools such as Google Search Console, you can analyse and refine your keyword groups for maximum impact. Stay ahead of the game and unlock the full potential of your SEO strategy with effective keyword grouping techniques.
The user-friendly interface will help you select a search engine and any location in the world down to a city.
Choose the keyword grouping method: soft or hard clustering. Soft is better for less competitive websites, while hard is better for popular keywords. Set the clustering accuracy: higher means more related keywords grouped together. Enter the keywords to analyze. The tool will group your keywords based on your settings.
Upload a list of your keywords as well as a list of negative keywords that will be excluded from the list before clustering.
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In the report you will receive after the Keyword Grouping Tool has done its work, you will get everything you need to build the perfect site structure or pillar page.
Keyword clustering helps you expand your semantic core with new keywords, with same search intent which search engines consider important and show in the snippets of sites from the SERP
During clustering, we identify the most successful competitors and show them to you. We will show you the keywords by which they are at the top of the search engine results
Identify the competitor’s URL that ranks highest for all the keywords in the cluster. You will only have to copy its optimization
We’ll show which URL on your site is already maximally relevant to all keywords in the cluster. This will help you understand which URL needs to be optimized first
Shows the search volume of each keyword and the total of the cluster
We show the size of the cluster so it’s easy to decide which groups are important and which are not
Use hard clustering for product categories. Separate brand + product combinations. Group size: 5-8 keywords per product page for precise targeting.
Apply soft clustering for topic discovery. Create pillar content from main clusters. Typical group size: 15-25 keywords per comprehensive article.
Export clusters to Google Ads Editor format. Build SKAG campaigns from hard clustering. Achieve Quality Score 8+ with precise keyword-ad alignment.
Cluster keywords by language and region. Account for cultural search differences. Optimize for local search intent patterns across 70+ markets.
I tested this platform for organizing my SEO research. The interface processes each keyword efficiently and handles keyword analysis well. The 7-day free trial allowed me to evaluate the features without commitment. Results were delivered quickly, though I’d recommend comparing with other tools before making a final decision.
The service automatically sorts terms into logical clusters. I found it useful for organizing my PPC campaigns, as each keyword group was clearly separated by search intent. The keyword group structure provides flexibility for campaign management. Pricing seems reasonable for the functionality offered, though manual review is still necessary.
This keyword grouping tool handles large datasets well and supports multiple search engines. The accuracy settings let you control clustering precision. Export options work smoothly with regional targeting features. The keyword grouping tool learning curve is minimal, making it accessible for beginners and professionals alike.
The algorithm analyzes search results to form each cluster based on common URLs in top rankings. Processing time was reasonable for my dataset. The results helped identify content gaps and each cluster provided clear insights. Documentation could be more comprehensive, but the core functionality delivers what’s promised.
I used this service for semantic grouping of my client’s terms. The system handles both competitive and long-tail phrases effectively. The negative keyword exclusion feature saves time during preprocessing. Results align well with search intent patterns, and the grouping methodology works efficiently for campaign optimization.
The platform processes your keyword list and provides structured output in Excel format. I found the search volume integration helpful for prioritizing clusters. The marker system allows for custom categorization of your keyword list. Success depends heavily on input data quality and strategic implementation.
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Create a task. To create a task and cluster your keywords, go to the clustering tab and click on “Create new task”.
Step one: Search Engine and Region.
Here you need to enter a task name (mandatory field). You can enter any name; it is often convenient to enter the name of a site so that you can easily find the desired task in the future.
Next, specify the search engine by the data on which the clustering will be performed.
For Google, all regions and languages of the world are currently available.
Step two: Task settings
Clustering method:
Type – Choose a clustering algorithm.
We have 3 clustering algorithms:
They work on the same basic principle — a comparison of the similarities of the top search engines — but are designed to solve slightly different problems.
Algorithm using manually entered core keywords (markers):
This algorithm is most effective when your site already has an extensively branched semantic structure (directory) so you don’t need to expand it, you know all the markers, and you just need to understand which keywords you are going to use to promote existing pages. In this case, take your markers (category/page titles), collect the Google search suggestions for them, mark the markers as 1 and the collected keyword cloud as 0, and perform clustering. In the output, you will get a ready-made semantic core for your categories, while keywords that are not assigned to your structure will remain unclustered.
Upload format: keyword | marker(1/0) – download sample input file.
Search Volume clustering algorithm
This algorithm solves the inverse problem of the manual marker algorithm. You do not yet know the structure of your site and can not allocate markers: you just collected keywords, search suggestions, and search volume. Next, you need to structure the semantic core. In this case, the search volume clustering algorithm is the best way to do it.
The entire list of keywords is sorted by decreasing search volume. The algorithm tries to link all the possible words from the list to the highest volume keyword and forms a cluster, then iterates for the next highest volume keywords.
Don’t worry that keywords might bind to the wrong cluster on the first pass of the algorithm; we use binary tree machine learning algorithms to prevent this 🙂
Data loading format: keyword | search volume – download sample input file
Combined algorithm of Search Volume and marker clustering – combines the approaches of the previous two methods.
This algorithm is suitable for the task of simultaneously selecting keywords for the existing site structure and expanding it. It works as follows: first, we try to link all possible keywords to your marker keywords and generate a ready-made structure linked to your markers. Next, all the keywords that have not been linked to your markers are sorted by decreasing search volume and grouped. As a result, you get:
a) A ready-made semantic core for the existing categories of your site.
b) Expansion of the semantic core for your site.
We strongly recommend using the combined algorithm; it gives the best results.
Load data format: keyword | marker(1/0) | search volume – download sample input file
The better the clustering accuracy, the more similar phrases will fall into one group (cluster).
In other words, this option is responsible for how many common URLs are in the top 10 of the search engine so that keywords are in the same cluster.
Each topic has its own necessary and sufficient threshold of similarity to get a quality semantic core. For example, when optimizing an online shop, it would be a big problem if during clustering keywords “Redmond Multicooker RX500” and “Redmond Multicooker RX500-1” fell into one cluster, because they are different products and should be promoted on different product cards. Here we recommend using an accuracy of 5.
For info topics, such as sites for discounts or recipes, such accuracy is not needed. Here, the task is to get the maximum number of grouped clusters for writing articles. For these sites, we recommend a precision of 3 or 4. For sites in very competitive topics, where the fight for the top is mainly competitive high-volume keywords, we recommend using increased accuracy of clustering (6 or 7), and creating separate pages for non-clustered keywords.
We recommend you choose options 3-6 and see from the results which query clustering has sufficient completeness and accuracy for your semantics. The higher the accuracy, the smaller the keyword groups will be.
Define relevant URLs for clusters of an existing site.
Simply enter the domain and our algorithms will try to determine the relevant URLs for the resulting clusters.
This option works in the following way: if your site is already in the top 10 of a search engine by the main (marker) keyword, we will show this URL and highlight it in green. If there are no keywords for your site in TOP10, we will select the URL for the marker keyword with the use of the site: operator.
This option works in the following way: if your site is already in the top 10 of a search engine by the main (marker) keyword, we will show this URL and highlight it in green. If there are no keywords for your site in TOP10, we will select the URL for the marker keyword with the use of the site: operator.
Step three: Keywords and price
Upload a file with the keywords.
Supported formats: xls, xlsx. For Search Volume clustering, the input format is keywords; search volume. For Manually entered core keywords (markers) clustering data format: keyword; marker (1/0 ). For clustering by a combination of Search Volume and marker clustering data format: keyword; marker; search volume.
Enter negative words
Phrases containing negative words will be excluded from the list before clustering. This functionality helps save clustering credits and solves the problem of manually clearing negative words from the results. It is especially useful if you are clustering a pre-cleaned list of keywords.
We suggest using ready-made negative keyword lists by geographical names and different topics, or create your own negative words list.
Click “Create New Task” – your task has been sent for clustering!
You can now track the status of the task in the Queue tab or the list of clustering tasks.
Rush Analytics currently has 4 statuses:
The output of the clustering in XLSX format is as follows:
Download a sample to see how this works
The option works in the following way: if your site is already in TOP10 by the main (marker) keyword, we will show this URL and highlight it in green. If your site is not in the top 10 of search results for any of the keywords, we will select the URL for the marker keyword using the site operator:
You can then combine logically related groups to build the structure of the site.
The choice depends on your specific needs and requirements. While a free keyword grouping tool may offer basic functionality, a paid tool often offers more features and support for more complex keyword grouping tasks. It is recommended that you consider your objectives and budget before deciding which option is best for you.
By identifying relevant keyword groups, you can optimize your ad targeting, improve ad performance, and increase the chances of reaching your desired audience. A keyword’s search volume — which indicates how frequently it’s searched for — plays a critical role in this process. By identifying relevant keywords with a high search volume, you not only refine your ad targeting but also bolster ad performance.
A keyword clusterer, such as Rush Analytics, can help boost long tail keywords by grouping related keywords together. By clustering similar keywords, you can identify common themes and patterns, allowing you to create more targeted and specific content or ad campaigns for long tail keywords. This can result in improved visibility, higher click-through rates, and better conversion rates for these keywords.
