Keyword Grouping Tools: 6 Options Tried & Tested (Which Is Best?)

Keyword grouping, or keyword clustering, has become a big part of modern SEO. But the way we approach it today looks very different from even a few years ago.

Search engines have moved well beyond exact-match keywords. One page can now rank for hundreds, or even thousands, of related terms, as long as it properly matches search intent and covers a topic in depth.

That’s why grouping keywords into meaningful clusters is essential if you want to build topical authority and avoid cannibalization issues.

The challenge is that doing this manually doesn’t scale. As keyword lists grow, it becomes harder to spot patterns, overlap, and intent relationships without the right tools.

Keyword grouping tools help you quickly turn large keyword lists into structured clusters using SERP data, natural language processing (NLP), or a mix of both.

We tested out the best keyword grouping tools and here’s what we found.

6 Best Keyword Grouping Tools Worth Trying Today

Choosing the right keyword grouping tool can save hours of manual work and significantly improve how you structure your content. But not all tools approach keyword clustering in the same way. Some rely on real-time SERP data, while others use NLP to map keyword intent at scale.

Here’s a rundown of the best keyword clustering tools available right now, what they do well, and where each one fits depending on your workflow and budget.

1. KeyClusters

By far the best keyword grouping tool we tested is KeyClusters.

This tool uses real-time SERP results to cluster keywords into groups based on the frequency of the same pages appearing in the top 10 results.

For example, if 3 or more of the same pages rank for a collection of keywords, then these keywords are grouped together.

To avoid keywords appearing in duplicate groups, the tool cross-references clusters to ensure keywords only appear in groups with the highest frequency of similar pages.

The tool works seamlessly with CSV exports from Ahrefs and SemRush, or you can upload a custom keyword file (for example, one for Google Search Console).

You can see the tool in action here.

To test the tool out, we uploaded a 1000 keyword file from Ahrefs on the topic “chicken recipes”.

The KeyClusters dashboard is simple and intuitive to use, and we like that you can group keywords by device (mobile, desktop), geolocation, and any language.

The tool took about three minutes to cluster the 1000 keywords, which is pretty quick given that it uses real-time Google SERP data.

Here’s a snapshot of the result. Pretty good if you ask us.

In terms of pricing, you get a 100 free credits when you sign up to KeyClusters. Pricing starts at $4.97 per 1000 keywords for their monthly subscription product, or you can use the tool on a PAYG basis for $9.99 per 1000 keywords. Credits never expire and you can cancel anytime.

2. SE Ranking

SE Ranking is an all-in-one SEO software similar to Ahrefs and SemRush. But unlike their competitors, they also have a sophisticated keyword grouping tool.

Like KeyClusters, SE Ranking uses SERP data to group keywords. It analyzes overlapping URLs across search results to determine which keywords can realistically be targeted on the same page.

It’s a well-developed tool that provides flexibility. And if you’re already using it for rank tracking or audits, the clustering feature fits naturally into your workflow.

What sets SE Ranking apart is the level of control you get over clustering. You can adjust the accuracy by defining how many shared URLs are required to group keywords. This gives you flexibility depending on whether you want tighter, article-level clusters or broader topic groupings.

You can also choose between different clustering methods:

• Hard clustering, where all keywords in a group must share common URLs
• Soft clustering, where keywords relate to a main term but not necessarily to each other

This makes it easier to tailor clusters based on your content strategy.

Another useful feature is the ability to localize clustering by country, language, and device.

Overall I was pretty impressed with SE Ranking. I ran a few tests with different accuracy and method settings, and the best result was with an accuracy setting of 3 and the hard method analysis that forces all keywords in a group to share URLs.

SE Ranking uses a subscription-based model:

• Core plan starts at around $129/month
• Higher-tier plans (like Growth) start around $279/month

Within these plans, you get access to a full SEO suite, including:

• Rank tracking across major search engines
• Keyword and competitor research
• Backlink monitoring
• Website and on-page audits

For keyword grouping specifically, you’ll typically pay $0.004 per keyword query, or $0.005 per keyword query if you want to include search volume data.

3. Keyword Insights

Keyword Insights is one of the more advanced keyword grouping tools on the market, combining SERP data with machine learning to deliver highly detailed clusters.

Like other tools, it analyzes live search results to group keywords based on overlapping URLs. But where it stands out is in the depth of insight it provides on top of those clusters.

One of its strongest features is search intent classification. The tool uses machine learning to categorize keywords into intent types so you can quickly understand whether a cluster should be targeted with a blog post, landing page, or product page. This is a really handy feature.

Another thing we liked about Keyword Insights is how much data you get back from each cluster. Instead of just grouping keywords, Keyword Insights gives you a full breakdown to help guide content decisions, including:

• Cluster volume and opportunity metrics
• Keyword difficulty and average ranking positions
• Dominant search intent for each cluster
• Recommended primary keyword for content creation
• SERP data and ranking URLs

This makes it much easier to move from keyword research to actual content planning without needing additional tools.

Overall, it did a great job. There were a few clusters that looked a little strange, but overall it got it right. We like how it separates keyword variations by row.

We were particularly impressed with the Hub-and-Spoke analysis it does. Basically, the tool attempts to define silos of articles that can be interlinked to each other.

Although this feature sounds quite promising, the Hubs-and-Spokes it found from our test list were quite random and broad.

Keyword Insights uses a credit-based subscription model:

• Basic plan starts at $58/month for 10,000 credits
• Professional plan is $99/month for 20,000 credits
• Enterprise plans are custom-priced for larger teams

Credits are used across features, including clustering (typically 1 credit per keyword), content briefs, and AI-assisted writing tools.

4. Keyword Cupid

As one of the first keyword grouping tools on the market, Keyword Cupid has a large community of users and is a mature software.
Instead of relying heavily on NLP or content-based signals, Keyword Cupid focuses almost entirely on SERP data. The idea is simple: if Google ranks the same pages for a group of keywords, those keywords likely belong together.

To do this, the tool uses a mix of live SERP scraping and machine learning models to identify patterns in ranking URLs. It then builds clusters based on how closely those SERPs overlap.

Here’s a typical output from Keyword Cupid.

As you can see the keyword clusters are very tight and accurate.

Here’s what a silo looks like.

Again, the analysis here is very helpful, especially for those looking to create a full site plan and strategy on interlinking articles.

You also get a high level of flexibility when running analyses. The tool allows you to:

• Upload your own keyword data (including metrics like CPC, difficulty, or impressions)
• Choose geo-location and device type for SERP analysis
• Compare how different search engines interpret the same keyword set
• Adjust clustering behavior based on your dataset

Another interesting feature is its “on-demand” machine learning approach. Instead of relying on pre-trained models, Keyword Cupid builds models based on your specific keyword dataset. This can lead to more tailored clustering results, especially for niche topics.

The tool also includes extras like SERP-based on-page insights, content length benchmarks, and project-based report organization, which are useful if you’re working across multiple sites or clients.

The downside is that Keyword Cupid is pretty pricey. It uses a monthly subscription model with tiered plans:

• Starter plan starts at $9.99/month (500 keyword credits)
• Freelancer plan is $49.99/month (5,000 credits)
• Agency plan is $149.99/month (20,000 credits)
• Enterprise plan is $499.99/month (80,000 credits)

You can buy additional credits separately if you need to.

5. Surfer SEO

Surfer SEO is an on-page content optimization tool that we use extensively at Contentellect.

The tool comes with a content planner that is great for generating keyword groups. Like most of the insight generated in Surfer, the content planner uses NLP insight on search intent to group keywords.

What we really like about Surfer’s keyword planner is that you don’t need to upload a list of keywords from a third party. The tool comes with a built-in keyword discovery tool that also pulls in search volume. Groups are then classified by search intent into broad categories like informational, local, customer investigation etc.

From the content planner it’s easy and quick to start working on an article within Surfer’s content editor.

The whole process from keyword research to grouping and then working on an article is seamless, and like other features in Surfer, the UI/UX is beautiful.

Here’s what the content planner looks like. We gave the tool the seed keyword: “work anniversary”.

As you can see, the content planner creates groups as individual tiles, and with a click of a button you can start writing an article for each tile.

So what’s not to like?

Not much really. The one shortcoming is that the keywords are somewhat limited compared to tools like Ahrefs and SemRush, and because you can’t upload your own keyword, you’re totally dependent on whatever Surfer spits out.

Also, if you don’t plan to use their content optimization tool, then the cost for just the keyword planner is quite expensive.

Surfer SEO uses a subscription-based pricing model, with plans designed around content production and optimization workflows.

Here’s how the current pricing is structured:

• Standard plan: $119/month
• Pro plan: $219/month
• Peace of Mind plan: $359/month

Each plan includes access to Surfer’s core features, such as the Content Editor, keyword clustering through the content planner, and SERP-based optimization insights.

As you move up the tiers, you get higher usage limits and additional features

→ See our full Surfer SEO review.

6. SEO Scout (Free & Paid)

SEO Scout is a paid tool, but they offer a free keyword grouper as well.

The free tool is simple and easy to use. You paste in a list of keywords, choose a language, and it groups them based on word similarities. It’s quick, and for smaller keyword lists, it gives you a decent starting point.

Here are the results I got from my chicken recipe keyword list.

And here is what the CSV file looks like.

The real value comes from the paid version.

SEO Scout’s full platform takes a more structured approach to keyword grouping by combining its own keyword research data with clustering. Instead of just grouping keywords, it builds out topic clusters that are ready to use in a content plan.

The tool automatically pulls in:

• Related keywords, questions, and search suggestions
• Long-tail variations grouped by theme
• Estimated total search volume across clusters

This makes it easier to see not just how keywords relate, but how much traffic each cluster could bring.

Another useful feature is how it connects clustering to content production. You can send keyword groups directly into a content planner, where you can start building outlines and mapping out supporting articles.

This ties into a broader SEO strategy. By interlinking a main pillar page with supporting content and FAQs, you can build topical authority more effectively and improve your chances of ranking across a wider set of keywords.

Here is the current pricing for SEO Scout paid plans:

• Starter plan starts at $49/month
• Business plan is $99/month
• Agency plan is $199/month

The paid plans unlock additional features like deeper keyword data, content optimization, site tracking, and clustering tied directly to content planning.

4 Free Keyword Grouping Tools

If you’re just getting started or working with a limited budget, free keyword clustering tools can still give you useful insights. While they don’t offer the same level of accuracy or depth as paid tools, they’re a quick way to spot patterns and group related keywords.

Answer Socrates

If you are looking for a powerful yet budget-friendly alternative to premium keyword tools, Answer Socrates has quickly become a standout.

While primarily known as a question-discovery engine, its recent updates have turned it into a capable machine-learning clustering platform.

The tool works by pulling real-time data from Google’s Auto Complete, People Also Ask (PAA) sections, and Google Trends. It then organizes these thousands of keywords into topical maps in under 60 seconds.

One of its unique features is Recursive Search, which digs deeper than standard variations to find the questions users ask after their initial query. This helps you build more comprehensive content silos.

Unlike many free tools that hide essential data, Answer Socrates includes search volume, CPC, and competition metrics in its exports.

Answer Socrates offers free versions of its tools as well as paid plans:

• Free: 3 searches per day and 1,500 monthly cluster credits (requires an account)
• Socrates Lite ($15/mo): 100 searches and 3,000 cluster credits per month
• Seneca ($29/mo): 500 searches and 12,000 cluster credits per month
• Aurelius ($49/mo): Unlimited searches and 40,000 cluster credits per month

ZenBrief

As far as free keyword clustering tools go, ZenBrief is another strong option.

Most free tools use a Lemma-based approach (i.e. grouping keywords based on their root similarities like cluster, clusters, clustering – all have root similarities and would therefore form a group).

ZenBrief uses an NLP methodology to understand the intent behind a keyword. This type of technique is a lot more accurate than Lemma-based clustering, although it’s not as accurate as grouping methodologies that use SERP data.

The tool is very easy to use. You can upload as many as 30k keywords at one time (as long as the file is under 1MB). ZenBrief then analyses the keywords with its NLP algorithm to form groups.

Here’s the result from our chicken recipe keywords.

You can also download the clusters to CSV, and the result looks as follows.

Of course, it has its limitations. It only supports English, there is no geolocation and you can’t import or analyze search volume. Also, as an NLP-based keyword grouper, the accuracy is not tight enough to define article specific groups.

For example, many of the groups above have keywords that would actually need individual articles as the intent is quite different between each.

Keyword Clarity

Keyword Clarity’s free keyword grouping tool is definitely worth checking out, especially if you like visual mind-maps or spider diagrams.

The tool works seamlessly with Google Search Console or you can upload keywords from other sources.

The visual layout helps you quickly spot relationships between keywords and understand how topics branch out.

One of the main advantages of Keyword Clarity is how intuitive it is to use. You don’t need to rely on complex formulas or manual sorting. The tool surfaces keyword clusters automatically and lets you interact with them directly in the interface.

You can also manipulate the clusters within the tool and export the results for further analysis or content planning.

That said, like most free tools, Keyword Clarity doesn’t rely on real-time SERP data. It likely uses linguistic methods such as lemmatization or phrase similarity, which can make the clusters less precise at an article level.

Here’s a snapshot from our chicken recipe list.

For a free tool, we were quite impressed with Keyword Clarity. It’s a nice option if you want a visual way to explore keyword relationships, but you’ll still need to sense-check clusters before building content around them.

MarketBold

MarketBold has a product called Keyword Grouper Pro that also does clustering for free.

All you have to do with Keyword Grouper Pro is insert a list of keywords and set the minimum group length (this is the number of terms the tool will consider to form a group).

You can also set words to exclude from the analysis. For example, we uploaded our chicken recipe list, which understandably has those two words in most of the phrases. So we excluded them.

The list processed very quickly. From the 1748 words it analysed, it formed 55 groups that had 3 or more terms in common.

The results are somewhat useful for those looking for a quick overview of how keywords relate to each other, but like the other free tools mentioned above, the output is not that helpful in defining what articles to write.

For example, in the salad group above, these keywords would probably need separate articles as the search intent is quite different between each.

Final Thoughts

Keyword grouping is a big part of any effective SEO content strategy (see our epic case study on keyword clustering!). As search engines get better at understanding intent and context, it’s no longer about targeting a single keyword per page. It’s all about covering topics properly.

The right keyword clustering tool can make that process faster and far more accurate. Whether you’re using a SERP-based tool for precision or a free option for quick insights, the idea is to organize your keywords in a way that aligns with how Google ranks content.

If you’re working with large keyword lists or managing content at scale, investing in a more advanced tool is usually worth it. But even free tools can help you spot patterns and build a solid foundation.

At the end of the day, keyword clustering is just one part of the process. What really moves the needle is how you turn those clusters into well-structured content.

That’s where we come in.

At Contentellect, we help businesses and agencies turn keyword research into scalable, SEO-driven content that actually ranks. If you’re looking to produce content clusters consistently (without overloading your team), we can support you with reliable, high-quality delivery.

Keyword Grouping FAQ

What is keyword grouping?

Keyword grouping, or keyword clustering, is an SEO keyword research methodology that attempts to cluster keywords into topical groups or entities. Keyword grouping helps eliminate keyword cannibalization issues (i.e. creating multiple articles that target similar keywords, where one article would suffice). It also helps generate insight on keyword search intent and how to cover a topic in its entirety to become a topical authority.

How does keyword grouping software work?

Most keyword grouping software use one of two primary methodologies to group keywords. The most common method uses Natural Language Processing (NLP) to help identify and group keywords with similar intent. NLP results are usually good at identifying keywords at a silo level but not at an article level.

To get a more granular view of keyword groups, some tools use SERP data. Real-time SERP data helps identify overlapping URLs and keywords. Where keywords and URLs overlap consistently, grouping them based on their SERP relationships is possible. This methodology generally provides a more accurate measure of a keyword group.

How many keywords should be in a cluster?

There’s no fixed number. Some clusters may contain just a few closely related keywords, while others can include dozens.

What matters most is intent. If all keywords in a cluster can be satisfied by a single page, they belong together.

Should I use SERP-based or NLP-based clustering?

It depends on your goal.

• SERP-based clustering is more accurate for deciding what content to create, since it reflects what Google ranks
• NLP-based clustering is faster and useful for getting a high-level view of topics

In most cases, SERP-based clustering is the better choice for SEO-focused content planning.

Can keyword clustering help with content strategy?

Yes, and it’s one of the main benefits. Clustering helps you:

• Avoid targeting the same keywords across multiple pages
• Identify content gaps more easily
• Build structured topic clusters and internal linking strategies

This leads to stronger topical authority and better rankings over time.

Do I need a keyword clustering tool?

Not always, but it becomes essential as your keyword list grows. If you’re working with a small list, you can group keywords manually. But once you’re dealing with hundreds or thousands of keywords, tools save significant time and improve accuracy.

Can I use free keyword clustering tools effectively?

Yes, but with limitations. Free tools are useful for:

• Spotting general keyword patterns
• Organizing smaller datasets
• Getting a rough idea of topic groupings

However, they usually lack SERP data, so you’ll need to validate clusters before building content around them.