13 Best Keyword Clustering Tools (Free & Paid Tested) – Complete 2025 Guide

Introduction to Keyword Clustering Tools

Keyword clustering is one of the most powerful yet underutilized strategies in modern SEO. Instead of creating separate pages for every keyword variation, clustering allows you to group related keywords and target them with a single, comprehensive piece of content.

New to keyword clustering?

Think of it like organizing a messy closet. Instead of having 100 separate keyword “outfits” scattered everywhere, clustering groups related keywords into organized “sections” so you can create one comprehensive piece of content that targets multiple related searches.

But here’s the problem: not all clustering tools are created equal.

We tested 13 keyword clustering tools, 8 free options and 5 premium solutions using a standardized dataset of 216 content marketing related keywords.

This comprehensive analysis reveals which tools deliver professional results and which ones to avoid. Our testing uncovered massive quality differences, with scores ranging from 9/100 to 89/100, proving that your choice of clustering tool can make or break your content strategy.

Our testing methodology was rigorous and unbiased. We used the same 216 content marketing keywords across all tools, measuring clustering quality, coverage, processing time, and workflow integration.

We spent real money on trials, created accounts, and put each tool through realistic SEO scenarios.

The results? Some tools are game-changers, while others are completely broken.

Key Findings From Our Testing:

• Quality gap is massive: Scores ranged from 9/100 to 95/100.

• SERP-based tools consistently outperformed pattern-matching (70-95/100 vs 11-35/100).

• $1 trials delivered professional results, while truly free tools were mostly broken.

• Premium tools justify their cost only if you need complete content workflows.

Before diving into our tool reviews, it’s important to understand that not all clustering approaches are equal. The methodology a tool uses determines whether you get professional results or waste your time.

Different Clustering Methodologies Explained

Not all clustering tools work the same way. Understanding the different methodologies helps you choose the right tool for your needs:

Pattern-Based Clustering (Least Accurate)

These tools group keywords based on shared words or text patterns. For example, “content marketing strategy” and “content marketing tips” would be clustered together because they share “content marketing.”

The problem? Google might show completely different results for these searches, meaning they need separate pages. Our testing showed pattern-based tools scored 11-35/100 on average.

Semantic/NLP Clustering (Moderate Accuracy)

Tools like ZenBrief use natural language processing to understand meaning and context. They group keywords based on semantic similarity rather than just shared words.

Better, but still limited. These tools understand language but can’t see what Google actually ranks. They scored 33-47/100 in our testing.

AI/LLM-Based Clustering (Moderate Accuracy)

AI/LLM-based clustering uses large language models to group keywords by semantic similarity rather than search engine behavior. It’s fast and effective at spotting related meanings. Like recognizing that “buy shoes online” and “purchase sneakers from web” are similar but it doesn’t check SERP intent.

Because it lacks SERP overlap detection, it can mistakenly group keywords that look similar but trigger completely different search results in Google. That’s why its accuracy is moderate: great for quick, broad clustering, but unreliable for high-precision SEO where user intent matters. It’s best suited for early-stage research or when speed matters more than precision.

These tools scored 47/100 in our testing.

SERP-Based Clustering (Highest Accuracy)

The gold standard.

SERPs are Search Engine Results Pages – Basically what you see when you Google something. The top 10 websites that appear for any search.

These tools analyze Google’s actual search results (SERP Overlap) to group keywords. If two keywords show similar top-ranking pages, they will be grouped in the same cluster.

What is SERP Overlap?

When two keywords show similar websites ranking in Google’s top 10 results, they have “SERP overlap.” High overlap (70%+ shared URLs) means keywords can likely be targeted on the same page. Low overlap means they need separate pages.

Why it works: You’re clustering based on Google’s actual ranking behavior and intent classification, not assumptions. SERP-based tools scored 70-89/100 in our testing.

Why SERP-Based Clustering is Superior

Here’s why SERP-based clustering consistently outperformed other methods in our testing:

Real Google Data vs. Assumptions Pattern-matching tools assume “crm tools” and “crm software” should be clustered together because they’re similar. But Google shows different results for these searches, meaning they need separate content strategies.

SERP-based tools actually check Google’s results and discover this difference, preventing costly content cannibalization.

Content cannibalization happens when you have multiple pages competing for the same keywords, confusing Google about which page to rank.

Intent Detection Consider these keywords:

Search Intent refers to what the user actually wants when they search. Google shows different types of results based on whether someone wants to buy something (commercial), learn something (informational), or compare options (comparison).

• “best project management software” (comparison intent)
• “project management software pricing” (commercial intent)
• “how to choose project management software” (informational intent)

Semantic tools might cluster these together because they’re topically related. SERP-based tools recognize the different intents and separate them appropriately.

Competitive Intelligence SERP-based clustering reveals which competitors dominate specific keyword clusters, helping you identify content gaps and opportunities that other clustering methods miss.

Our Testing Proof:

• SERP-based tools: 70-89/100 average score
• Semantic tools: 33-47/100 average score
• Pattern-based tools: 11-35/100 average score

The data is clear: if you want clustering that actually works for SEO, SERP-based is the only way to go.

For more detailed explanation on how SERP clustering works, check our Keyword clustering guide.

With this understanding of clustering methodologies, let’s see how real tools perform when put to the test.

Free vs Paid Clustering Tools: What’s the Difference?

The landscape of keyword clustering tools spans from completely free options to enterprise-grade solutions. Here’s what separates them:

Free & Low-Cost Tools ($0-$1)

Most tools in this category use basic pattern matching or limited semantic analysis. However, our testing revealed some $1 trials that deliver professional-grade results:

• Truly Free: SEO Scout, Pemavor, Keysearch, Contadu.
• $1 Trials: Keyword Insights, Keyword Cupid.
• Credit-Based: Serpstat (expensive per keyword).
• AI-Powered: ChatGPT (manual approach).

Limitations: Smaller keyword limits, basic clustering methods, limited workflow integration.

Premium Tools ($19-$119/month)

These tools offer advanced SERP-based clustering, complete workflows, and enterprise features:

• Full-Featured: Keyword Insights Pro, Ahrefs, SEMrush.
• Content-Focused: Writersonic.
• Enterprise: Higher keyword limits, team features, API access.

Advantages: SERP-based accuracy, complete content workflows, advanced analytics.

Theory is helpful, but real-world testing reveals the truth. Here’s what happened when I put 8 free clustering tools through identical tests.

8 Best Free Keyword Clustering Tools (2025 Tested)

How We Tested These Tools

I tested these tools by uploading 216 keywords around “content marketing” – a mix of long-tail and generic keywords that I researched from Ahrefs. I cleaned up the data before uploading to make sure all the keywords was relevant to the topic.

Here’s how I evaluated each tool:

What I looked for:

• How many clusters were produced?
• How long it took to cluster them?
• Were the clusters actually useful and actionable?
• Could I bring my own keywords easily?
• Was there any workflow to take clusters further (like creating content briefs, content creation, performance tracking)?

My scoring system weights the important stuff:

• Cluster quality gets the highest weight (because what’s the point if clusters are garbage?).
• Number of clusters produced is also heavily weighted.
• Workflow integration matters a lot for actually using the results.
• Ease of uploading keywords matters somewhat.
• Speed matters least (I’d rather wait for good results).

What to expect from free tools: Limited keyword processing, fairly fast results, no competitor visibility features, and pretty much no workflow to actually create content from your clusters.

How I Calculated Final Scores

Each tool gets points in each category, then I add them up:

• Example – Keyword Insights: Clustering Quality (38/40) + Cluster Quantity (28/30) + Workflow Integration (20/20) + Input Flexibility (6/7) + Processing Speed (2/3) = 89/100.
• Example – SEO Scout: Clustering Quality (12/40) + Cluster Quantity (18/30) + Workflow Integration (0/20) + Input Flexibility (3/7) + Processing Speed (2/3) = 35/100.

This weighting ensures clustering quality and workflow matter most, while speed has minimal impact on the final score.

The Tools I Tested

1. Keyword Insights $1 Trial

What It Does

Keyword Insights is a SERP-based clustering tool that uses live Google search results to figure out how Google actually sees your keywords. For a dollar, you get access to some pretty sophisticated features.

Key features:

• Handle up to 200,000 keywords and 5M for Enterprise plans (way more than you’ll ever need for most projects).
• Uses live SERP data from 212 countries and 127 languages.
• Shows you competitor visibility in clusters.
• Classifies search intent and has rank checking capabilities.
• Integrates with Google Search Console and WordPress.
• Has an AI Writer Agent for content creation.

My Testing Results

• 141 clusters from my 216 keywords.
• Took 17 minutes to process.
• 100% coverage – every keyword got clustered.
• Quality was excellent – the logical grouping made total sense.

The coolest thing? It actually spotted content cannibalization issues on my test site. For “b2b content marketing,” it showed me that I had two similar pieces of content competing against each other. That’s the kind of insight you actually want from a clustering tool.

User Experience

The setup was easy and I could navigate to the clustering feature without any issues. There are helpful guides built right into the app, so I didn’t have to hunt around for help.

Uploading keywords was super intuitive – just upload your CSV and map the columns. The tool automatically removed duplicates and let me combine keywords from multiple sources.

The clustering process itself was straightforward, though analyzing the output might be tricky if you’re new to SEO.

Once I had my clusters, I could use pre-made filters to quickly find content gaps and opportunities.

Pros & Cons

Strengths: Accurate SERP-based clustering, excellent workflow integration, fast processing.

Weaknesses: Limited free credits, AI Writer Agent costs 1200 credits (expensive), requires $1 payment and account creation.

Final Verdict

Score: 89/100 – This is what professional clustering looks like, even at the $1 trial level.

Best for: Users wanting accurate, fast workflow-integrated clustering.

Avoid if: You need unlimited free processing or use the AI Writing Agent. (You need the pro version for that).

2. SEO Scout Keyword Grouping

What It Does

SEO Scout is a basic text pattern-based tool that groups keywords by looking for similar words. It’s free and simple, but you get what you pay for.

Key features:

• Unlimited keywords (though your browser will hate you with large lists).
• Text pattern matching.
• No account or sign up needed.

My Testing Results

• 36 clusters from 216 keywords.
• 2 minutes to process (super fast).
• 100% coverage but with a major problem…

The issue? Since it’s just matching text patterns, I got tons of duplicate clusters. The same keywords showed up in different clusters, which makes the whole thing pretty useless for actual content planning.

User Experience

Dead simple – just paste your keywords, select language, and go. The interface is clean but there’s zero documentation or help.

You’re on your own.

Pros & Cons

Strengths: Fast processing, no signup required.

Weaknesses: Poor clustering quality, duplicate clusters everywhere, no workflow features, can’t save your work.

Final Verdict

Score: 35/100 – Fine for quick pattern spotting, but don’t expect professional results.

Best for: Quick pattern identification in small keyword lists.

Avoid if: You need accurate clustering or workflow integration.

3. ZenBrief Keyword Clustering

What It Does

Zenbrief uses an NLP-based combined approach of vector quantization and Google’s BERT, a neural-based technique for Natural Language Processing. Since late Google 2019, Google uses BERT to understand the intent behind user’s search queries.

Compared to old techniques (word2vec for example), BERT – which stands for Bidirectional Encoder Representations from Transformers – is able to understand context and therefore group keywords that have similar meanings. they then use an optimization technique to find the optimal number of clusters in order to maximize the quality of each cluster.

Key features:

• Uses NLP based clustering (BERT – the same tech Google uses to understand search intent).
• Up to 20,000 keywords.
• You can adjust cluster sizes.
• Good FAQ explaining how it works.

My Testing Results

• 11 clusters from 216 keywords.
• 3 minutes to process.
• Only 58% coverage – 42% of my keywords didn’t get clustered at all.

That coverage issue is a deal-breaker. What’s the point of sophisticated NLP if it can’t handle nearly half your keywords?

User Experience

Easy to use – you can paste keywords or upload a text file. But, I had to format the keywords before I was able to paste them in.

The interface is clean and they actually have decent documentation explaining their approach.

Pros & Cons

Strengths: Uses advanced NLP, fast processing, good documentation.

Weaknesses: Terrible coverage (missed 42% of keywords), no workflow features, can’t save work.

Final Verdict

Score: 33/100 – The tech is cool but the execution falls short.

Best for: Users wanting NLP-based clustering for smaller keyword sets.

Avoid if: You need complete keyword coverage or workflow integration.

4. Contadu Keyword Grouper

What It Does

Contadu a basic keyword grouping tool based on common text processing algorithms with a very basic method of text distance analysis.

If you need clustering analysis incorporating semantic models (NLP), user intentions, potential of certain clusters and competition performance you need to upgrade for a paid version of the tool. 

Key features:

• Maximum 100,000 keywords per clustering job.
• Text processing algorithm-based clustering.
• Two clustering methods: common subwords and predefined groups.
• Account creation for saving results.

My Testing Results

• 8 clusters from 216 keywords.
• 4 minutes to process.
• One cluster had 205 keywords in it.

You read that right – 205 keywords in a single cluster. That’s not clustering, that’s just dumping everything in one bucket. Completely unusable.

The tool gives you two options: build clusters based on common subwords, or assign keywords to predefined groups. I tried both. Neither worked well.

Example of how bad it was: It grouped “ai content marketing” and “ai content marketing tools” together. These need separate targeting – Google shows completely different results for these searches. But this tool can’t tell the difference.

As you can see Google ranks completely different results for both of these keywords and they don’t belong in the same cluster.

User Experience

Despite poor clustering quality, the interface is well-designed. Easy setup with account creation option, and you get two different clustering methodologies to try.

The tool gives you two clustering options. 

1. Build keyword clusters based on common subwords.
2. Assign keywords to predefined groups.

Build keyword clusters based on common subwords

This option allows you to select the number of keywords in a clutter and language. You also have the option to force group all the keywords but you get a warning about potentially getting lower quality results. 

Assign keywords to predefined groups

This option clusters keywords based on a pre-defined groups. You get an option to select the accuracy. 

Pros & Cons

Strengths: Fast processing, can save results with account.

Weaknesses: Absolutely terrible clustering quality, unusable output, no workflow features.

Final Verdict

Score: 13/100 – I can’t recommend this tool for anything.

Best for: Not recommended based on testing results.

Avoid if: You need any level of clustering accuracy or usability.

5. Keyword Cupid

What It Does

Keyword Cupid uses state-of-the-art neural network models to reverse engineer Google’s knowledge graph, in real time. They scrape live data and train machine learning models to provide users with an optimized and holistic content strategy.

Key features:

• Up to 80,000 keywords.
• SERP + Machine Learning clustering.
• Cool Mindmap visualization.
• $1 trial available.
• Private group access.

My Testing Results

• 46 clusters from 216 keywords.
• 40 minutes to process (slowest of all tools).
• 100% coverage with very good quality.

The clustering was actually really good. I didn’t find any incorrect groupings or duplicates. The clusters made sense and both the Mindmap view and spreadsheet view were easy to understand.

Clicking each ‘cluster’ opened up new sub clusters under it.

At the end, you’re shown the top 10 Google SERP results, but it’s not clear how to use this information. I was expecting it to flow naturally into their content brief module.

User Experience

The signup process was easy and creating a project was straightforward. They have a handy dropdown to select your keyword data source (Ahrefs, SEMrush, etc.). But the interface feels a bit outdated and their social media hasn’t been updated in 4 years which makes me believe this tool is not actively developed or promoted. (I could be wrong though)

The problem? While the clustering was good, I couldn’t figure out how to actually use it for content creation. The tool mentions content briefs, but I couldn’t find clear instructions on how to generate them.

The tool says, I need to create the content brief from the Mindmap but, I was unable to figure out how to do it. My guess is that brief feature requires a subscription.

Pros & Cons

Strengths: Good clustering accuracy, unique Mindmap view, no duplicate clusters.

Weaknesses: Very slow (40 minutes!), unclear workflow, outdated interface.

Final Verdict

Score: 70/100 – Good for clustering accuracy, but workflow is confusing.

Best for: Users prioritizing clustering accuracy over speed and workflow.

Avoid if: You need fast results or clear content planning workflows.

6. Pemavor Free Keyword Grouping Tool

What It Does

The Pemavor Keyword Grouping Tool is a free, web-based utility designed to help marketers and SEOs quickly group large lists of keywords based on shared word patterns. It’s especially useful for PPC campaign structure, SEO content planning, and keyword organization at scale.

The tool uses a combinatorial pattern-matching algorithm that scans each keyword and groups them based on shared words, stems, or recurring terms. It does not use SERP-based clustering like some advanced SEO tools. Instead, it focuses purely on string similarity and token overlaps.

Key features:

• Maximum 10,000 keywords per clustering job.
• Pattern-matching algorithm.
• Customizable similarity threshold.
• No registration required.

My Testing Results

• 4 clusters from 216 keywords.
• 2 minutes to process.
• 53% coverage – 102 keywords (33%) went unclustered.

Four clusters. From 216 keywords. Each cluster had an average of less than 6 keywords. This is basically useless for any real SEO work.

User Experience

Super simple – just paste keywords, set similarity threshold and cluster size, and go. No signup required, which is nice, but there’s no way to save your work.

Since it’s purely pattern-based, it created tiny clusters and left a third of my keywords unclustered. The output was completely unusable for content planning.

Pros & Cons

Strengths: Fast processing, no signup required.

Weaknesses: Worst clustering quality of all tools, 33% unclustered keywords, unusable output.

Final Verdict

Score: 11/100 – Don’t waste your time.

Best for: Not recommended for any use case.

Avoid if: You need any level of clustering utility.

7. Keysearch Keyword Clustering Tool

What It Does

The Keyword Cluster Tool by Keysearch.co is a feature designed to help SEOs and content creators organize large keyword lists into topic-based groups. The main goal is to simplify keyword targeting by grouping similar search terms based on their search engine results page (SERP) similarity. Ensuring that all keywords in a cluster can be targeted effectively within a single page or topic.

Unlike basic string-matching tools, Keysearch’s cluster tool uses SERP-based clustering, which compares the top-ranking results for each keyword. If two keywords show similar top results in Google, the tool considers them topically related and places them in the same cluster. This approach ensures the clusters are not just linguistically similar, but contextually and semantically aligned.

Key features:

• SERP-based clustering algorithm (claimed).
• CSV upload and paste input options.
• Integration with Keysearch SEO suite.

My Testing Results

• 2 clusters from 216 keywords.
• 2 minutes to process.
• One cluster had 2 keywords, the other had 213 keywords.

This isn’t clustering – this is a malfunction. I’m pretty sure the tool is broken and the owners don’t know it.

User Experience

The interface looks fine and the process seemed normal, but the output was completely unusable. Either their algorithm is fundamentally flawed or something is seriously wrong with their system.

Pros & Cons

Strengths: Clean interface, fast processing.

Weaknesses: Tool appears to be broken, completely unusable output.

Final Verdict

Score: 9/100 – Avoid until they fix whatever’s wrong.

Best for: Not recommended – tool appears broken.

Avoid if: You need any functional clustering capability.

8. ChatGPT-Based Clustering (Manual Approach)

What It Does

ChatGPT is an advanced conversational AI developed by OpenAI. It is designed to understand and generate human-like text, allowing users to have natural and intelligent interactions with a machine. You can ask it questions, get help with tasks, generate content, brainstorm ideas, write code, or simply have a conversation.

I decided to test ChatGPT as a clustering tool using a custom prompt. This represents the DIY approach for people who want to try clustering without specialized tools.

I created this prompt, 

Keyword Clustering Analysis Request

Objective

Create comprehensive keyword clusters from the provided list of 216 keywords using a dual-methodology approach that combines semantic analysis to identify meaningful thematic groupings for SEO strategy development.

Clustering Methodology

Semantic Matching Analysis

Group keywords that share similar search intent and meaning

Consider synonyms, related terms, and conceptual relationships

Account for topic relevance and thematic connections

Key features:

• Advanced conversational AI capabilities.
• Semantic and thematic analysis.
• Custom prompt-based clustering.
• Unlimited keyword processing (within context limits).

My Testing Results

• 128 clusters from 216 keywords.
• 1 minute to process (fastest of all).
• 100% coverage.

While ChatGPT’s semantic clustering did a decent job grouping keywords based on meaning, it struggled to separate keywords with fundamentally different search intents on Google. This limitation stemmed from the fact that we didn’t feed it any SERP-related intent data.

Had we provided that, ChatGPT could have used it to produce more accurate clusters. But sourcing and integrating SERP data is time-consuming, and at that point, it’s more efficient to use a purpose-built SERP-based clustering tool. That said, ChatGPT remains a solid option for fast, rough clustering ideal if you’re not overly concerned about precision.

The good news: ChatGPT did a decent job with semantic clustering. It understood thematic relationships and grouped related concepts together logically.

I exported the data and created a pivot table to better understand the clusters

The bad news: It can’t see Google’s actual search results, so it missed important intent differences that only SERP data would reveal.

As you can see the “b2b content marketing” cluster generated by ChatGPT doesn’t match Googles intent as none of these keywords share any common URLs in the SERPs. (Some keywords do but as a overall cluster this is not correct).

User Experience

Pretty straightforward if you know how to write good prompts. I uploaded my CSV and ChatGPT processed it easily.

I created a prompt asking ChatGPT to cluster my 216 keywords using semantic analysis and thematic grouping. The AI understood the task and got to work.

Pros & Cons

Strengths: Fast, good semantic understanding, familiar interface.

Weaknesses: No SERP context, requires prompting skills, no quality assurance.

Final Verdict

Score: 47/100 – Decent for quick semantic grouping, but lacks the SERP insights you need for real SEO work.

Best for: Quick semantic clustering when other tools aren’t available.

Avoid if: You need SERP-based accuracy or professional workflow integration.

What I Learned From Testing All These Free Clustering Tools

After putting 8 free tools through the same test, here’s what became crystal clear:

Free Tools Quick Comparison

Tool	Score	Clusters	Coverage	Speed	Best For
Keyword Insights ($1)	89/100	141	100%	17 min	Professional work
Keyword Cupid ($1)	70/100	46	100%	40 min	Accuracy on budget
ChatGPT	47/100	128	100%	1 min	Quick semantic grouping
SEO Scout	35/100	36	100%	2 min	Pattern identification
ZenBrief	33/100	11	58%	3 min	NLP experimentation
Contadu	13/100	8	95%	4 min	Not recommended
Pemavor	11/100	4	47%	2 min	Not recommended
Keysearch	9/100	2	99%	2 min	Avoid (broken)

The quality gap is massive. Scores ranged from 9/100 (Keysearch) to 89/100 (Keyword Insights). That’s not a small difference – that’s the difference between completely unusable and professional-grade results.

SERP-based clustering wins every time. Tools that actually look at Google’s search results (like Keyword Insights and Keyword Cupid) consistently outperformed pattern-matching tools.

Workflow integration matters more than I expected. Getting clusters is just the first step. The tools that help you actually do something with those clusters provide way more value.

“Free” often means “broken.” The truly free tools (no trial, no payment) were mostly unusable. The $1 trials provided exponentially better results.

My Recommendations

For professional SEO work: Keyword Insights ($1 trial) – 89/100 The clustering quality and workflow integration justify the small cost.

For accuracy on a budget: Keyword Cupid ($1 trial) – 70/100. Good clustering quality, though the workflow is confusing.

For quick pattern analysis: SEO Scout – 35/100 Fast and free, but don’t expect professional results.

Skip entirely: Keysearch (broken), Pemavor (unusable), Contadu (terrible quality).

When to Upgrade to Paid Tools

Consider paid clustering tools when you need:

• Regular clustering of large keyword lists (5000+ keywords).
• Professional workflow integration.
• Team collaboration features.
• Competitive analysis.
• Search intent classification.

Bottom line: For serious SEO work, spending a dollar or two on quality clustering tools provides dramatically better results than struggling with free alternatives. The time you save and insights you gain make it a no-brainer investment.

Now that we’ve seen what free tools can (and can’t) do, let’s explore premium options. Do they justify their cost, or are the $1 trials sufficient for most users?

Top 5 Premium Keyword Clustering Tools

How I Tested Premium Tools

After seeing the massive quality differences in free tools, I wanted to test the premium options to see if they’re worth the investment. I used the same 216 content marketing keywords and put each tool through real-world scenarios.

I still have a few other premium tools I plan to test, including Surfer SEO and SnapSEO. Once I’ve had a chance to try them out, I’ll update this article along with the rankings and recommendations.

My Premium Tool Scoring System

For premium tools, I used a more comprehensive scoring approach since these tools offer advanced features:

• Clustering Accuracy (40 points): How well clusters match Google’s actual search intent.
• Workflow Integration (25 points): Content creation, AI features, and next-step capabilities.
• Feature Completeness (20 points): Search intent classification, competitor analysis, export options.
• User Experience (10 points): Interface design, ease of use, learning curve.
• Value for Money (5 points): Features vs cost, hidden fees, credit systems.

Unlike free tools where basic functionality matters most, premium tools are judged on their ability to deliver complete SEO workflows and professional-grade insights.

1. Keyword Insights Pro

What It Does

This is the full version of the tool that impressed me in the $1 trial. The Keyword Clustering feature in Keyword Insights uses real-time Google SERP data to intelligently group keywords that rank for similar results. Instead of relying on outdated string-matching or basic logic, it looks at how Google interprets the intent behind each keyword helping you create smarter, more focused content strategies.

Key features:

• Handle 200,000 to 5M keywords per clustering job.
• Real-time SERP analysis from 212 countries.
• Search intent classification.
• Competitor visibility reporting.
• Google Search Console and WordPress integration.
• Complete AI Writer Agent and content brief workflow.

My Testing Results

• 141 clusters from my 216 keywords (same as the trial).
• 17 minutes to process.
• 100% coverage – every keyword got clustered.
• Quality was exceptional – the logical grouping was spot-on.

But here’s where the Pro version really shines: the workflow integration is incredible.

I clicked “Quick actions” and immediately got 26 new content ideas for topics I wasn’t ranking for.

The competitor visibility report showed me exactly how my test domain (HubSpot) stacked up against competitors – turns out Content Marketing Institute owns this niche.

The game-changer: I could go from cluster to published content in one workflow. I selected a cluster, generated a detailed content brief with their AI, then sent it to their Writer Agent to create a full article. The entire process was seamless.

User Experience

The setup was just as easy as the trial version. Helpful guides and videos are built right into the app, so I never had to leave to find help. The interface is clean and intuitive – no steep learning curve here.

What impressed me most was the “Quick actions” feature. Instead of staring at clusters wondering what to do next, I could immediately see actionable insights and workflows.

Pros & Cons

Strengths: Best-in-class SERP clustering, complete workflow integration, competitor analysis, seamless content creation.

Weaknesses: Credits can get expensive for large projects, AI Writer Agent uses 1200 credits per article, no cluster performance tracking over time.

Final Verdict

Score: 95/100 – This is what professional clustering should look like.

Best for: SEO professionals and agencies who want the complete workflow from clustering to content creation.

Avoid if: You’re on a tight budget or only need basic clustering without content creation.

2. SEMrush Keyword Strategy Builder

What It Does

The SEMrush Keyword Strategy Builder is essentially a keyword clustering tool, albeit with a more polished interface and additional features. It automates the process of grouping keywords into clusters based on search intent and SERP similarities, facilitating the creation of structured SEO content strategies.

Key features:

• Maximum 2,000 keywords per clustering job.
• Topical map generation.
• Search intent classification.
• SEO metrics (keyword difficulty, search volume).
• Authority scores for competitors.

My Testing Results

• 25 clusters from 216 keywords.
• 15 minutes to process.
• 83% coverage – some keywords went unclustered.

Here’s where it got disappointing: I only got 25 clusters, and one cluster had 65 keywords in it.

The problem: SEMrush uses a black box method for SERP overlap with no user control. In my test, this created unusable clusters mixing keywords like ‘ai content marketing‘ and ‘ai content marketing tools‘ into a single cluster where these require separate pages according to Google.

There are only 2 overlapping urls for these keywords.

Source: https://serpsimilarity.com/

As you can see, Keyword Insights correctly placed these keywords into separate clusters, and the intent classification makes it clear what kind of content to create. In this case, the ‘tools’ cluster is dominated by AI content marketing tool lists and comparison style articles.

The workflow issue: If you want to create content, you need to buy an additional ContentShake AI subscription for $60/month. This means additional monthly costs for content creation workflows.

User Experience

The interface is polished and professional – very easy to upload keywords. I liked that you can add new keywords to existing cluster reports without starting over (unique feature).

Not many tools we’ve tested had this feature.

The unique Authority score for competitors was useful, and the overall SEMrush ecosystem integration is solid if you’re already using their platform.

Pros & Cons

Strengths: Can track cluster performance over time, integrates with SEMrush’s large and extensive keyword database and unique Authority score.

Weaknesses: Poor clustering quality for the price, no SERP overlap control, limited workflow without expensive add-ons, 2,000 keyword limit per run.

Final Verdict

Score: 52/100 – Disappointing for a premium tool from a major company.

Best for: Existing SEMrush users who want everything in one platform (despite limitations).

Avoid if: You need accurate clustering or don’t want to pay extra for content creation workflows.

3. Writersonic AI Keyword Clustering

What It Does

Writesonic‘s AI Topic Clustering tool is designed to help you improve your website’s search engine optimization (SEO) efforts. It works by grouping together keywords that are related to each other in terms of topic or theme.

The tool functions somewhat like creating a map or a diagram of keywords. It takes the keyword you provide and create clusters based on their semantic or contextual similarities. This process helps you visualize the relationships between different keywords and understand how they fit together within the broader topic or theme you’re focusing on.

Key features:

• AI-powered clustering from seed terms.
• Automatic hub-and-spoke content mapping.
• Search intent classification.
• Built-in content brief and writing workflows.
• No manual keyword upload so its automatic clustering (seed term only).

My Testing Results

• 16 clusters from a single seed term.
• 2 minutes to process.
• Can’t measure coverage since I couldn’t upload my keyword list.

This tool is fundamentally different. You can’t upload your own keywords.

It generates clusters based on what it thinks is relevant to your seed term.

The good: The clusters looked logical and were clearly marked as hub vs supporting content. The UX is absolutely beautiful – one of the best I’ve seen.

The bad: Without SERP-based clustering, it made the same mistakes as semantic tools. For example, it put “b2b content marketing agency” and “b2b content marketing trends” in the same cluster, when these need separate pages.

There are zero SERP overlap between these keywords.

Source: https://serpsimilarity.com/

Keyword Insights placed these two keywords in separate clusters because their search intent is fundamentally different, even though they look similar.

The keyword “b2b content marketing agency” returns mostly commercial results such as agency websites or curated lists promoting services. This indicates the searcher is likely ready to hire or compare providers, placing them in the mid to bottom of the funnel.

On the other hand, “b2b content marketing trends” returns entirely informational content, including articles about trends, strategies, and industry insights, without any immediate call to action. This suggests the user is still researching and is likely at the top of the funnel. Since the search results show zero overlap and serve different user goals, Keyword Insights correctly puts them in separate clusters to reflect the need for distinct content approaches.

User Experience

This has the best user experience of any tool I tested. The interface is gorgeous, the workflow is intuitive, and getting started takes seconds.

The workflow is very easy to use.

I was able to go from these clusters to AI generated content easily.

But the lack of keyword upload flexibility is a major limitation. You’re stuck with whatever keywords their AI thinks are relevant.

Pros & Cons

Strengths: Best UX/workflow design, excellent for content ideation, great for validating topical cluster concepts.

Weaknesses: No keyword upload flexibility, semantic clustering lacks SERP accuracy, limited to their keyword data (Which we think is coming from Ahrefs).

Final Verdict

Score: 61/100 – Beautiful tool, but limited functionality.

Best for: Content creators who want quick topic ideas and beautiful workflows/Feature packed AI generated content.

Avoid if: You need accurate clustering or want to upload your own keyword research and have more control.

4. Ahrefs Keywords Explorer

What It Does

Ahrefs employs a “Parent Topic” methodology to cluster keywords. This involves analyzing the top-ranking page for a given keyword and determining which keyword drives the most traffic to that page. All related keywords are then grouped under this Parent Topic, facilitating a more organized and strategic approach to content creation.

One of the standout features of Ahrefs’ clustering tool is its speed. Unlike some tools that may take considerable time to process large keyword lists, Ahrefs can cluster up to 10,000 keywords in seconds. This rapid processing is particularly beneficial for SEO professionals managing extensive keyword databases.

Key features:

• Lightning-fast clustering (10,000 keywords in seconds).
• Parent Topic methodology.
• Search intent classification.
• Complete SEO metrics (difficulty, volume, DR).
• Treemap visualization.

My Testing Results

• 121 clusters from 216 keywords.
• Less than 1 minute to process (fastest of all premium tools).
• Nearly 100% coverage.

The speed was impressive – Clustering happened almost instantly. While speed isn’t the most important factor for clustering quality, it’s valuable for large-scale analysis work.

Where it worked well: The “b2b content marketing” cluster was 90% accurate, comparable to other full SERP-based tools.

Where it fell short: Since it only looks at the top-ranking result (not the full SERP), some clusters mixed different intents. The “content marketing agency” cluster had keywords that should be separated.

Keyword Insights, a full SERP-based clustering tool, successfully handles these nuances and complex situations with accuracy.

The trade-off: Ahrefs prioritizes speed over precision. For quick analysis of thousands of keywords, this works well. For precise content planning, the accuracy limitations become more apparent.

User Experience

Ahrefs’ interface is clean and professional. The treemap visualization makes it easy to see cluster relationships and filter results.

If you’re already using Ahrefs, the integration is seamless.

The workflow limitation: their AI Content Helper tool isn’t integrated with clustering and costs an extra £79/month (similar to SEMrush’s approach).

Pros & Cons

Strengths: Incredibly fast clustering, handles large keyword sets, good visualization and quality, integrates with Ahrefs ecosystem. Ahrefs’ massive keyword database means you rarely need external keyword research.

Weaknesses: Less accurate than full SERP-based clustering, limited content workflows, AI content features cost extra.

Final Verdict

Score: 81/100 – Great for speed and scale, but accuracy suffers.

Best for: Users who need to cluster thousands of keywords quickly for analysis.

Avoid if: You need the highest clustering accuracy or integrated content workflows.

5. Serpstat Clustering Tool

What It Does

Serpstat’s Keyword Clustering Tool allows you to upload keywords and automatically groups them based on how similar their search engine results pages (SERPs) are. This SERP-based approach ensures that each cluster contains keywords that Google already sees as contextually related.

Once clustered, these keyword groups can be assigned to specific website pages, helping to structure content more effectively, target multiple search intents, and improve organic rankings through tighter topical relevance.

Key features:

• Maximum 50,000 keywords per clustering job.
• SERP-based clustering algorithm.
• Soft and hard clustering options.
• Credit-based pricing (5 credits per keyword).

My Testing Results

• 37 clusters from 216 keywords.
• 15 minutes to process.
• Only 35% coverage – 76 keywords went unclustered.
• Cost: 5 credits per keyword (1,085 credits total).

The tool gives you “soft” and “hard” clustering options, but no control over SERP overlap percentages. I went with soft clustering and ended up with a bunch of unclustered keywords.

The clusters that did form were pretty small and didn’t provide much actionable insight.

User Experience

The platform provides a professional experience within their broader SEO suite. Easy integration, clean interface, but limited clustering-specific guidance.

The settings were not so easy to understand and I couldn’t set my desired SERP overlap for this test run.

Pros & Cons

Strengths: SERP-based approach, professional interface.

Weaknesses: Poor coverage (26% unclustered), expensive credits, no workflow features.

Final Verdict

Score: 30/100 – Might be okay if you’re already a Serpstat user, but there are better options.

Best for: Existing Serpstat users needing occasional clustering.

Avoid if: You need high coverage rates or cost-effective clustering.

What I Learned About Premium Tools

After testing premium options, here’s what became clear:

Premium Tools Quick Comparison

Tool	Score	Clusters	Coverage	Workflow	Monthly Cost	Best For
Keyword Insights Pro	95/100	141	100%	Complete	$58	Full SEO workflow
Ahrefs Keywords Explorer	81/100	121	100%	Basic	$99+	Speed & scale
Writersonic	61/100	16*	N/A	Excellent	$19+	Content creation
SEMrush Strategy Builder	52/100	25	83%	Limited	$119+	All-in-one platform
Serpstat	30/100	37	74%	None	$69+	Existing user

*Seed term only, can’t upload keyword lists.

Keyword Insights Pro: is in a league of its own. While other tools either lack accuracy (SEMrush, Writersonic) or workflow integration (Ahrefs), Keyword Insights delivers both. The 95/100 score isn’t just about clustering quality – it’s about the complete workflow from research to published content.

Speed vs. Accuracy trade-offs are real: Ahrefs clusters 10,000 keywords in seconds, but Keyword Insights 17-minute processing delivers far more accurate results. For professional SEO work, accuracy wins.

Workflow integration separates the winners: SEMrush and Ahrefs charge extra for content creation features. Writersonic has great workflows but poor clustering. Only Keyword Insights includes everything in one package.

Premium doesn’t always mean better: SEMrush scored lower (52/100) than some free tools, proving that brand names don’t guarantee quality.

My Premium Tool Rankings

1. Keyword Insights Pro: 95/100 – Complete content solution.
2. Ahrefs Keywords Explorer: 81/100 – Speed champion.
3. Writersonic: 61/100 – Beautiful UX, Very good content workflow.
4. SEMrush Strategy Builder: 52/100 – Disappointing for the price.
5. Serpstat: 30/100 – Disappointing workflow and results.

When Premium Makes Sense

Upgrade to premium when you need:

• Professional-grade clustering accuracy.
• Complete content creation workflows.
• Team collaboration features.
• Medium to Large-scale keyword processing (20,000+ keywords regularly).
• Competitive analysis integration.

The sweet spot: Keyword Insights Pro offers the best value in the premium category. You get enterprise-level clustering with complete workflows at a fraction of what other platforms charge for similar functionality.

Bottom line: If you’re serious about content strategy and SEO, the investment in Keyword Insights Pro pays for itself with the first project. The time savings and content quality improvements make it a no-brainer for professional use.

How to Choose the Right Clustering Tool for Your Needs

Based on our testing of 13 tools, here’s your decision framework:

If You’re Just Starting Out

• Budget: $0-1.
• Choose: Keyword Insights $1 Trial (89/100).
• Why: Professional results for the price of a candy.

If You Need Speed Over Precision

• Budget: $99+/month.
• Choose: Ahrefs Keywords Explorer (81/100).
• Why: 10,000 keywords clustered in seconds.

If You Want Beautiful UX & Content Creation

• Budget: $19+/month.
• Choose: Writersonic (61/100).
• Why: Gorgeous interface and excellent content workflows.

If You Need Complete SEO Workflow

• Budget: $58+/month.
• Choose: Keyword Insights Pro (95/100).
• Why: Best clustering accuracy + full content creation pipeline.

If You’re Already Using SEMrush/Ahrefs/Serpstat

• Choose: Their built-in clustering tools.
• Why: Ecosystem integration (despite lower scores).

Avoid Entirely

• Keysearch (9/100) – Broken.
• Pemavor (11/100) – Unusable output.
• Contadu (13/100) – Poor quality.

Quick Decision Tree

• Need free? → SEO Scout (35/100) for basic pattern matching.
• Have $1? → Keyword Insights Trial (89/100).
• Need enterprise scale? → Keyword Insights Pro (95/100).
• Want fastest processing? → Ahrefs (81/100).

Frequently Asked Questions

What’s the difference between free and paid clustering tools?

Free tools use basic pattern matching or limited semantic analysis. Paid tools use real-time SERP data and offer complete content workflows. Our testing showed paid tools scored 52-95/100 vs free tools at 9-89/100.

How many keywords should I cluster at once?

Start with 100-500 keywords for your first project. Most tools handle this easily. For larger projects (10000+ keywords), use Keyword Insights Pro or Ahrefs.

Can I use ChatGPT instead of clustering tools?

ChatGPT scored 47/100 in our testing. It’s good for quick semantic grouping but lacks SERP data, so it misses important search intent differences. Use it for brainstorming, not final clustering.

Why do some tools give completely different clusters?

Different methodologies produce different results. Pattern-matching tools group by similar words. SERP-based tools group by Google’s actual behavior. SERP-based consistently outperformed others in our testing.

How often should I re-cluster my keywords?

Re-cluster quarterly or when Google algorithm updates significantly impact your rankings. Search intent can shift over time.

What’s SERP overlap and why does it matter?

SERP overlap measures how many of the same websites rank for different keywords. High overlap (70%+) means keywords can target the same page. Low overlap means separate pages needed.

Are $1 trials worth it?

Absolutely. Keyword Insights $1 trial scored 89/100 – better than most premium tools. Keyword Cupid’s $1 trial scored 70/100. Both deliver professional results.

Can clustering tools replace keyword research?

No. Clustering organizes existing keywords into groups. You still need keyword research tools to find keywords first. Many clustering tools integrate with research platforms.

What if my clusters seem wrong?

Check the tool’s methodology. Pattern-matching tools often create illogical clusters. SERP-based tools are more accurate but may reveal intent differences you didn’t expect. Trust the SERP data over assumptions.

Do I need different tools for different languages?

Most tools support multiple languages, but SERP-based tools like Keyword Insights offer the best international coverage (212 countries, 127 languages). Check language support before choosing.

Final Thoughts

After testing 13 keyword clustering tools with the same 216-keyword dataset, the results speak for themselves. The quality spectrum is vast. From completely broken tools to professional-grade solutions that genuinely improve content strategy.

The key takeaway?

Methodology matters more than marketing. SERP-based clustering consistently outperformed pattern-matching and semantic approaches because it’s based on Google’s actual behavior, not assumptions about how keywords should be grouped.

Whether you choose a free tool, a $1 trial, or a premium solution depends on your specific needs and budget. The important thing is understanding what each approach offers and choosing accordingly.

Keyword clustering has matured from an advanced SEO tactic to a fundamental content planning requirement. The tools exist across every price point. The choice is yours.