Keyword Collection and Clustering From A to Z

Every website is created to attract an audience. Its structure is tailored to generate traffic, ensuring that users land on the right page to find a specific answer to their question. Search query clustering is the process of grouping keywords based on meaning and user intent. It helps distribute queries effectively across the site, establish a logical structure, and boost SEO performance by better aligning content with audience needs.
Below, you will find comprehensive information on what this process entails, as well as recommendations for the best tools to use.

Related material: Content marketing – why is it needed?

Clustering: what it is

Clustering is the division of queries into certain groups. After that, a list of keys is formed, consisting of a different number of positions.

The statistics are first grouped by decreasing frequency of queries. To make similar raw materials usable, clustering is performed. When working with the semantic kernel, sorting is considered the final stage.

The Purpose of Clustering

The volume of the semantic dataset depends on the scale of the project, often numbering in the thousands of entries. Such lists require sorting and grouping. This process creates clusters based on user interests, with larger clusters often subdivided into smaller ones. For example:

1. Buy a house.
2. Rent a house.
3. Rent out a house.
4. Buy a three-room house.
5. Rent out a room in a house.

To ensure that anyone looking to purchase a house lands on the real estate sales page, queries containing the word “buy” must be grouped into a single cluster:

1. Buy a house.
4. Buy a three-room house.

Consequently, the primary objectives of search query clustering are:

• distributing keywords to relevant site pages;
• establishing a logical structure for sections and categories;
• identifying topics for new content creation;
• increasing the precision of page optimization for search queries;
• improving the site’s alignment with user search intent.

Clustering methods

Clustering can be done automatically or manually. In the first case, the user is still involved, because some groups remain unsorted.

Services for clustering

It is much easier to perform automatic clustering with the help of special services than manually. Such sites take into account:

• competitive factor;
• search results.

Almost every service is identical to the others.

Clustering queries in Excel

The Excel spreadsheet processor is convenient for the manual clustering of keys. It allows you to sort, and automatically calculate the total frequency of queries in the cluster.

The clustering algorithm in Excel is as follows:

1. Loading all key queries.
2. Forming clusters – selecting the main queries with the maximum frequency.
3. Sorting all other sources into the formed clusters.

Manual clustering in Excel is possible if we are well acquainted with the topic of the site and if the number of queries does not exceed 100.

Serpstat.

Ukrainian multifunctional service. Serpstat algorithms are unique. Features of the portal:

1. Grouping is based on hierarchical principles. Key queries are grouped into clusters. They, in turn, are grouped into superclusters, and these into protoclusters.
2. You can set the strength of the connection as a separate parameter between phrases.
3. Clustering is performed in soft and hard modes. As a result, there are 6 ways for algorithms.
4. The results from the top 30 are analyzed.

If necessary, you can install the application and not just use the online service.

KeyAssort

The KeyAssort program has the following important features:

• Synonyms, transliteration, and queries with misspellings are taken into account when combining phrases;
• 3 clustering algorithms – hard, middle, and soft;
• the ability to collect intersections in a variable size of the TOP from 5 to 50;
• Convenience for manual adjustment: you can manually drag queries from one cluster to another, collapse and expand groups;
• You can search for words using filters and combine phrases from several groups into one.

The program allows you to cluster queries with different grouping strengths in two modules – for commercial and informational websites (Soft and Hard, respectively).

Key Collector

Key features of the Key Collector program:

• automatic selection of additional relevant queries;
• the ability to identify rare low-frequency queries that are not used by competitors;
• analysis of competitors’ keywords;
• issuing recommendations for search engine optimization (internal linking).
• Possibility of further data integration with SAPE, MainLink, and Rookee services.

MegaLemma.

This program allows you to:

• analyze users’ topical queries based on a frequency dictionary;
• clean thousands of keywords from garbage;
• automatically correct keyword errors;
• create a semantic core in the form of a single file;
• create a contextual campaign in Yandex and upload it to your account;
• store and apply stop word lists.

MegaLemma, like other programs, allows you to perform clustering for the purposes of information sites and contextual advertising using two different algorithms.

TopSite.

The TopSite program implements the hyperbolic clustering algorithm, which is used as an additional operation when checking positions. The developer claims that the implementation of this algorithm allows to improve the sorting of queries since the value of addresses from the top ten is significantly higher than from the second and third (the program uses the TOP 30 results as a base).

To use the algorithm and formulas that describe the hyperbolic decrease in the weight of the URL in the SERP, the user sets an additional parameter “Degree of similarity of search results”, which can take values from 0 (“minimal similarity”) to 20 (“very high similarity”).

The user can prevent the program from merging clusters if necessary, which can be useful in some cases.

MindSerp.

MindSerp includes 3 tools:

1. Clusterizer, which distributes queries into groups.
2. An optimizer that makes recommendations based on the analysis of search results.
3. Determining the commercial factor, allows you to classify a search phrase as commercial or not.

Clustering is performed in the usual way, with the strength of the relationship and the severity of the grouping set.

Online services for clustering queries

In addition to local programs, there are even more online services for clustering queries. Let’s consider the most popular ones.

Kg.ppc.panel

A simple and low-functional service that allows you to upload a list of queries, filter them, and use minus words. That’s all. The grouping results are unloaded in a separate list, without saving.

S: tools

This service performs clustering, taking into account the search results in the TOP 10. It performs its function no worse than local programs.

JustMagic.

One of the most interesting and original services. It includes a set of tools for SEO optimization: collecting the semantic kernel, analyzing texts, including the relevance of the query, and making suggestions for optimizing the existing SERP. Keyword clustering is one of the JustMagic modules.

Keys are grouped based on the top search engine results for each query.

Coolakov

Coolakov – presents a set of simple but necessary tools:

• Ping – checking websites for accessibility;
• CCI – checking the website quality index;
• Social Link Counter – checks pages for the number of tweets, likes, and shares;
• LI parser – parses liveinternet.ru statistics;
• clustering of queries;
• checking the disabling of links in Yandex by queries;
• searching for the most frequently occurring URLs of competitors in the TOP.

The clustering service itself is simple and straightforward. Grouping is carried out taking into account the search results. Data can be easily downloaded to Excel.

Topvisor

A comprehensive service called Topvisor is positioned as a search engine analyzer, but in reality, its functions go far beyond that. For example, it can adjust bids in Yandex. Direct, making up to 288 adjustments per day.

Query clustering is just one of the elements of the SEO process. The procedure is carried out on the basis of the search top in three possible variants of keyword strength – the soft, hard, and manual setting of parameters.

SEMparser

The service has an original name – a semantics structurizer, which certainly characterizes the authors as creative individuals. In addition to the common elements that are present in other developers, SEMparser allows you to create technical specifications for copywriters.

If we talk directly about the clustering of queries, we will not see anything surprising or new here. In general, the service is notable for its complexity: it is convenient to carry out all stages of work within one shell, rather than jumping from one program to another.

SE Ranking

The global SE Ranking service has physical offices in the USA, the UK, and Russia, which in itself indicates the high level and professionalism of the developers. According to most SEO specialists and digital marketers, SE Ranking is, if not the best, then at least one of the best online software programs in this field.

The service offers a wide range of tools:

• Audit of the website or its pages, checking the positions in the search;
• analysis and monitoring of links;
• selection of keywords;
• competitor analysis;
• lead generator;
• marketing plan;
• SMM (auto-posting and analytics).

The clustering of queries is one of the functions of the service, which is implemented on the basis of the top 10 search engines.

Rush Analytics.

A service with a typical set of functions: kernel collection, checking positions and hints, and text analysis.

Clustering can be performed using 1 of 3 algorithms:

1. Based on the automatic selection of the most high-frequency queries to which all others will be “tied”.
2. Based on the entered markers.
3. Hybrid algorithm. First, the method with markers is used. For queries that could not be linked, the highest-frequency keys are automatically selected according to Wordstat and re-clustered.

The user can also set the strength of the link – the accuracy of clustering.

Clustering algorithms and principles

It doesn’t matter how the clustering is done. The most important thing is to attract people to the landing page.

Principles.

Queries are grouped based on:

1. Subject division. Objects of the same type are divided into minimal segments. The visitor should be directed to a specific page, not some analog.
2. Target restriction. A single group of keywords collects queries from people who are united by a single task. For example, “buy a watch” and “buy a Hublot watch” are already in different groups.
3. Combining information and commercial queries. This clustering principle also has possible limitations. For example: “How to drink tea in America” and “Where to buy tea in America” cannot be grouped into a single cluster.

Clustering algorithms

Above, we have reviewed popular services and programs. They are based on their own algorithms. That is why different offers are created.

Clustering by top

The services use search engine algorithms to identify the semantic and semantic affiliation of keywords. As a result, they analyze the composition of the SERPs. As shown earlier, they can belong to the same group of clusters or to different ones.

The relationship between semantics and meaning has different degrees of strength. The algorithms define hard and soft as the two characters for grouping.

Clustering by word form

In this case, phrases belong to the same group if the words they contain have the same root. Example: “Good white blood cell count in women” and “Normal white blood cell count in women” belong to the same cluster.

Question/non-question clustering

It makes sense to divide queries into narrative and interrogative ones in cases where there are a lot of the second type of keys. They are usually grouped on separate pages.

However many specialists do not use this method. After all, the user can formulate their request any way they want.

The problem of clustering

Grouping queries is not difficult, especially with modern services. The problem lies in the presence of a list of keys that are not automatically assigned to a group. The number of such requests is up to 30% of the total. Yes, algorithms correct the situation, but you also need to use your mind and hands.

This is especially true when working with highly specialized portals. Let’s say a wheat query is clustered. Then the keywords will not be able to be grouped.

Conclusion.

• When working on the semantic core of a website, it is important to cluster search queries.
• To automatically group keys, you need to use specialized programs and services.
• Adjustments must be made manually.