Collection of the semantic core
Collecting a semantic core helps you understand what queries users enter into Google when searching for products, services, or information on a website's topic. Using this data, you can check your current structure, identify missing landing pages, distribute queries among URLs, and identify areas with potential for organic traffic.
What is the semantic core of a website?
Ordering a semantic core analysis makes sense both before launching a new project and for an existing website. This includes analyzing search demand, competitors, and current pages, collecting keywords, checking search volume, cleaning up semantics, identifying search intent, clustering queries, and linking them to target pages.
The prepared semantics are used for SEO structure, meta tags, content specifications, internal linking, and subsequent ranking monitoring. The client receives a working table where queries are categorized into thematic clusters, and each cluster is linked to an existing or planned website page.
A website's semantic core is a structured set of search queries that correspond to the project's theme, products, services, and the needs of the potential audience. The core may include commercial, informational, navigational, high-frequency, mid-frequency, and low-frequency queries, as long as they are relevant to the specific website's objectives.
Simply extracting keywords doesn't provide a ready-made structure for promotion. Queries need to be checked for relevance, search intent, and search volume, unnecessary phrases removed, suitable keywords combined into a semantic cluster, and a landing page defined for each group.
When compiling the core, search results for priority queries are taken into account. If Google shows different types of pages for two similar keywords, placing them on the same URL often doesn't make sense. This separation helps to more accurately structure the site and reduce the risk of query cannibalization.
Why does business need semantics?
Semantics reveals real search demand and helps connect it to the product range, services, and structure of the project. Before beginning active SEO, you can determine which pages already meet demand, which need to be expanded, and which areas aren't yet represented on the website.
The clusters are used to prepare the Title, Description, H1, H2-H3 structure, and content assignments. The semantic core is also used when planning new landing pages, informational materials, and internal linking between related website sections.
For businesses, this analysis provides a clear sequence of SEO work. The team sees which areas are in demand, which URLs need to be promoted first, and where the creation of additional pages is actually supported by search results.
How does a semantic core differ from a regular list of keywords?
A typical list can contain thousands of search phrases without specifying their purpose. It often contains duplicates, irrelevant queries, inappropriate regions, competitor queries, zero-volume phrases, and keywords with different intents that cannot be promoted on a single page.
In the completed semantic core, queries are cleaned and grouped. For each cluster, the intent, query frequency, website section, landing page, and priority are determined. If necessary, URL mapping is performed, which shows the relationship between the collected semantics and the existing project structure.
This file can be immediately used for further SEO work. It's suitable for preparing a content plan, technical specifications, new landing pages, catalog structure, and checking current website optimization.
What is included in the semantic core collection service?
The service begins with a project analysis and ends with a completed structured table. Between these stages, keyword collection, frequency checking, cleansing, intent determination, query clustering, and semantic distribution across the website pages are performed.
The number of stages may vary depending on the scale of the project. The depth of analysis varies for a small service website and a large online store, as the catalog, filters, brands, information demand, and number of possible landing pages all require different levels of analysis.
You can order semantic analysis as a standalone service or as part of preparation for a full-fledged SEO campaign. In both cases, the results should be suitable for further work, not remain a large spreadsheet without a clear structure.
Business, website, and search engine results analysis
Before collecting queries, products, services, regions, languages, and project priority areas are analyzed. For an existing website, the current structure, indexed pages, and key URL types already included in search results are additionally checked.
Next, competitors in organic search results are analyzed. SEO competitors may differ from companies a business considers direct competitors, as Google ranks directories, marketplaces, services, information projects, and service websites for the same queries.
Search results help understand the type of page that matches a specific query. Top-10 analysis is especially useful for mixed-intent searches, where similar phrases yield different document formats.
Formation of marker queries
Marker queries describe key products, services, categories, and user tasks. They are used as a starting point for expanding semantics through additional sources and help ensure key business areas are not lost.
The list of keywords is compiled based on the site structure, product range, client information, and competitive analysis results. For a large project, it's convenient to categorize the keywords into sections before mass keyword collection.
Once the base phrases are prepared, the expansion begins. A single marker can yield dozens or hundreds of related queries with varying frequencies, wording, and search intent.
Expanding semantics
To fully capture demand, multiple data sources are used. A single service rarely contains all search phrases, so queries are compared, supplemented, and verified before being included in the final core.
Sources are selected based on the region and project type. For an existing website, real queries from Search Console are useful; for a new project, competitors, similar queries, search suggestions, and SEO service databases are more important.
After data merging, a rough semantics is obtained. It still contains redundant queries and requires cleaning, frequency checking, and further grouping.
Semantics of search competitors
Websites that already rank for relevant topics help identify queries missed during manual search. Individual pages and domains are analyzed, and then keywords related to the client's products or services are selected.
Content Gap can be used for such an analysis. It reveals queries for which competitors are gaining visibility, while the site in question is either not yet present or has significantly weaker rankings.
Don't copy your competitor's entire list. Different companies have different product ranges, regions, structures, commercial terms, and landing pages, so each identified query is additionally checked for relevance.
Search suggestions and related queries
Search suggestions help find the actual phrases users enter when searching for products, services, and answers to questions. These sources are especially useful for long phrases and low-frequency search terms.
Similar queries expand thematic coverage and help identify adjacent audience needs. However, each new group is verified separately, as seemingly similar phrases may relate to a different intent or a different decision stage.
For informational sections, tooltips are a great addition to the future content plan. In commercial contexts, they help find clarifications based on features, price, geography, service type, and other selection criteria.
SEO services data
Serpstat, Ahrefs, Semrush, and other search query database services can be used to expand semantics. They help check competitors, find related keywords, and evaluate the visibility of individual pages.
Data from different services may vary, so the figures are not taken as absolute values. The main goal at this stage is to find useful queries and directions, which are then further verified.
SEO services are also used to analyze search results and group keywords. Automatic processing speeds up work with large data sets, but questionable groups still require manual review.
Google Keyword Planner and Google Search Console
Google Keyword Planner is used to expand the list of keywords and test search demand. It's especially helpful to consider the selected geography, as the popularity of a single query can vary significantly between regions.
Google Search Console provides data on queries that are already driving impressions to an existing website. The report identifies pages with a high number of impressions, queries near the first page of search results, and topics that are currently underserved.
These sources serve different purposes and complement each other well. Keyword Planner helps manage demand, while Search Console shows the actual connection between a website and user queries.
Checking the frequency of queries
Search volume shows how frequently users search for a specific phrase in a given region. It helps compare queries within a given search area and assess potential search demand before creating new pages.
High-frequency queries typically cover a broader topic and can have high competition. Low-frequency queries often more accurately describe a user's need, so they can be useful for categories, services, and informational materials.
A decision can't be made based on a single number alone. Search volume is always considered alongside intent, relevance, competition, and the current site structure.
Cleaning the semantic core
After mass collection, the list is left with phrases that are not suitable for the project. These include queries for other brands, inappropriate cities, irrelevant products, zero search volume, and information needs that the site does not plan to address.
Obvious duplicates and queries with stop words are also removed if they don't meet business requirements. For large projects, it's best to set cleanup rules separately for each section, as a single word may be redundant in one category but useful in another.
The result is a working array of queries that can be passed on to intent determination and clustering. Grouping an uncleared database too early increases the number of errors and unnecessary clusters.
Defining search intent
Search intent indicates the result a user expects to receive after entering a query. For commercial phrases, this could be a category, product card, or service page, while for informational queries, an article, instruction manual, or reference material is more often appropriate.
Sometimes a single query has mixed intent. In such cases, Google analyzes search results, the types of pages in the top 10, and the content of documents deemed relevant.
Separating queries by intent helps prevent commercial and informational tasks from mixing on a single URL. This is especially important for websites with a large number of services and expert content.
Search query clustering
Query clustering combines phrases that can be promoted on a single page. This is done by taking into account the meaning of the keywords, search intent, and document matches in the search results.
For large cores, automatic SERP clustering is used, after which the groups are manually verified. This approach speeds up the processing of thousands of phrases and preserves the ability to correct questionable groupings.
High-quality clustering directly impacts the future structure of a website. If a single intent is split across too many URLs, pages may begin to compete with each other.
Distribution of semantics across pages
After clustering, each set of queries is assigned a target page. For an existing project, current URLs are first checked to preserve useful pages and avoid creating unnecessary duplicates.
If a suitable URL is not available, the cluster can become the basis for a new category, subcategory, service page, filter, or informational piece. The decision depends on the intent and composition of the search results.
The resulting table records the section, subsection, page, and URL. This mapping of queries to URLs simplifies the work of the SEO specialist, developer, and copywriter.
Setting priorities
Not all clusters need to be implemented at the same time. Priority is determined based on search demand, commercial value, competition, current visibility, and the complexity of creating a new page.
For an existing website, high priority may be given to pages already near the top 10 and requiring semantic expansion or content improvement. For a new project, the main commercial areas are usually addressed first.
Priorities help allocate resources in stages. The team gets a clear plan for which pages to create or refine first.
I always check semantics through search results, because similar phrases don't necessarily lead to the same page. If Google shows different document types for them, it's better to split the cluster. For me, a good result of semantics collection is queries that can be distributed across the site structure without any guesswork and used in further SEO work.
Common mistakes when collecting a semantic core
Most problems arise not at the query export stage, but during their cleaning, grouping, and distribution. Even a large keyword list is of little help if it mixes different intents and lacks links to the site pages.
For commercial projects, semantic errors often lead to extra pages or missed requests. Therefore, the final file needs to be verified both from the user's perspective and against actual search results.
Below are some typical situations that should be avoided before implementing the structure.
Use only one query source
One service may not show some long-tail queries, new phrases, or queries from a specific competitor. Therefore, keyword collection is usually conducted from multiple sources.
Data is aggregated and cleaned after uploading. This approach expands coverage and reduces the likelihood of missing individual business or information clusters.
Copying a competitor's semantics without checking
A competitor may offer different services, product ranges, regions, and business models. Their semantics are useful as a source of ideas, but shouldn't be automatically transferred to the structure of another website.
Each identified query is checked for relevance. Phrases that are not relevant to the project are removed before clustering and URL distribution.
Ignore search intent
Similar words don't guarantee the same user needs. One search query might lead to a sales page, while another might lead to a tutorial, review, or comparison.
Combining different intents will blur the page. Therefore, the search result type is checked before deciding on the target URL.
Combine all similar queries on one page
Excessively large clusters often appear when grouping by keywords alone. They can mix different services, categories, or user tasks.
Such a page tries to cover too many topics and loses its specific focus. SERP clustering helps identify such groups and separate them before implementation.
Do not check frequency and region
A search query may be popular in one region and virtually nonexistent in another. For local businesses, this difference directly impacts page priorities.
Frequency is checked taking into account the target geography. For multilingual promotion, each language version is analyzed separately.
Creating too many landing pages
A large number of URLs doesn't in itself generate more organic traffic. If pages serve the same intent, they can compete in search results and complicate the structure.
A new URL is created when it has a dedicated cluster and a suitable search result type. The remaining queries are distributed within existing relevant pages.
Ignore the existing site structure
When working with a live website, semantics cannot be considered separately from the current URLs. Some pages may already have rankings, links, and accumulated behavioral signals.
Before creating new pages, we check whether existing ones can be used or expanded. This approach reduces unnecessary duplication and preserves existing visibility.
What we actually did
Dental clinic · Kyiv and Chernihiv
+44% clicks from search
A domain with no history and a site on a website builder. We built the semantic core for both cities, reworked the landing pages and built the link profile from zero. In four months: 34.8k clicks, impressions 1.32 → 1.76M, DR 0 → 41.
E-commerce · international
+96% clicks in two months
A catalog of digital 3D models. We clustered the semantics, rebuilt the hub pages and fixed duplicates and indexing errors. Google users 247 → 532, CTR 2.4% → 4%.
Medical center · Ukraine
+68.75% visibility in the first month
Narrow visibility and a small semantic core at the start. Semantics, landing page structure, metadata and internal linking, then gradual link building.
How long does it take to collect semantics?
The collection time depends on the number of destinations, the site's size, and the depth of clustering. For a compact service website, analysis takes less time than for an online store with a complex structure and tens of thousands of potential queries.
Additional time is required if semantic matching needs to be performed on hundreds of existing URLs, multiple languages need to be checked, or a large number of disputed clusters need to be manually analyzed. Therefore, the deadline is determined after a preliminary review of the project.
Before work begins, the results and scope of the analysis are documented. This helps determine in advance whether a complete semantic core analysis of the website is required or whether a single section is sufficient.
How much does it cost to collect a semantic core?
The cost of collecting a semantic core is calculated after a project assessment, as the scope of work depends heavily on the website structure. Collecting semantic core data for a small corporate website and a multi-tier online store requires a different number of sources, queries, and manual verification.
Therefore, a universal price for a semantic core without project information is of little value. Before calculating, it's advisable to know the website URL, region, language, number of categories, and the approximate size of the catalog or services.
If you need a turnkey semantic core, the clustering depth and the amount of work required to manage the structure are also taken into account. The more existing URLs need to be matched to queries, the longer URL mapping takes.
What does the price of a semantic core depend on?
The cost is affected by the number of services or categories, site size, promotion region, number of language versions, and volume of collected queries. The state of the current structure is also important if semantics are being collected for an existing project.
For an online store, the price increases with a large number of categories, brands, and filters. For a service website, the volume may increase due to a large number of product categories or multiple regions for promotion.
The cost also depends on the depth of manual cluster verification. The more complex the search results and the more queries with mixed intent, the more groups need to be analyzed separately.
Conditional graph of the influence of factors on the volume of work:
| Factor | Impact on the volume of work |
|---|---|
| Structure size | High level of influence |
| Number of directions | High level of influence |
| Number of regions and languages | Medium to high level of influence |
| Number of existing URLs | Medium level of influence |
| Clustering depth | High level of influence |
This graph shows the overall relationship but is not used as a fixed calculation formula. The exact cost of compiling a semantic core is determined after reviewing the project.
What is included in the price?
The cost of compiling a semantic core typically includes website and niche analysis, preparation of marker queries, collection of semantics, competitor analysis, frequency checking, and list cleaning.
The next block of work includes defining search intent, clustering, and manually checking for contentious groups. After this, queries are distributed across existing or new pages.
If agreed upon in advance, the final file also contains recommendations for developing the structure and priorities. It's best to define the specific scope of the service before work begins to ensure the outcome meets the project's objectives.
Why is a ready-made semantic core rarely suitable for a specific website?
A ready-made semantic core can be purchased as a source database of queries if it matches the topic. However, such a file typically doesn't take into account the specific website's structure, product range, geography, language, or current visibility.
After purchasing, the database still needs to be cleaned and clustered. Queries need to be matched to existing URLs, search results need to be checked, and areas of focus that aren't relevant to the business need to be removed.
Therefore, queries like "buy semantic core for website" and "buy semantic core price" should be considered with the expectation of further development. A ready-made core can speed up collection, but rarely replaces individual project development.
Related services
Clustering of semantics
Semantic clustering for SEO: how to group queries by intent and search results, the difference between soft and hard keywords, which services to use, and how to test clusters.
Development of SEO website structure
Website SEO structure development based on semantics, competitors, and search demand. We design categories, landing pages, URLs, and interlinking. Order website structure from Seo-Gen.
Answers to your questions
How much does it cost to collect a semantic core?
The cost depends on the number of categories, website size, region, language, and depth of analysis. Semantic core development for a small service website and a large online store requires different amounts of analysis.
The exact price for a semantic core is determined after a project evaluation. If the structure already exists, the number of URLs that need to be matched to the collected clusters is additionally taken into account.
How long does it take to compile a semantic core?
The time frame depends on the volume of queries, the number of sections, and the complexity of the clustering. A large online store requires more time to clean and distribute semantics than a compact corporate website.
Additional time may be required for multiple regions and language versions. The scope of work is assessed individually for each project before the start of work.
Is it possible to buy a ready-made semantic core?
A ready-made website query core can be purchased as a source database if it relates to the desired topic. However, before use, such a database must be verified, cleaned, and compared with the structure of a specific project.
Ready-made semantics typically don't take into account the product range, geography, current URLs, and search visibility of the site. Therefore, for full-fledged SEO, additional development is required.
What is included in the collection and clustering of the semantic core?
The work includes project and competitor analysis, query collection, frequency testing, cleaning, intent determination, and SERP clustering. After grouping, queries are distributed across existing and new pages.
Additionally, recommendations on structure and priorities may be prepared. The specific data set in the final table is agreed upon before the work begins.
Do I need to build a new core for an existing website?
A full rebuild isn't always necessary. You can first check the current semantics, structure, and queries from Google Search Console, and then add any missing areas.
If a site has significantly changed its product range or promotional geography, the core file is usually subject to a more thorough review. The decision depends on the state of the current structure and the quality of the old file.
How does the semantics of an online store differ from that of a service website?
For an online store, more attention is paid to categories, brands, characteristics, product types, and filters. For a service website, the analysis is more often focused on product categories, subservices, geography, and commercial query modifiers.
In both cases, queries are grouped by intent and search results. The difference lies in the project structure and the number of possible landing pages.
Why do we need query clustering?
Clustering shows which queries can be promoted by a single page. It helps determine the number of necessary URLs and avoid creating multiple pages for the same search intent.
SERP clustering takes into account the overlap of search results. After automatic processing, priority groups are further manually verified.
Is it possible to build a semantic core using only Google Keyword Planner?
Google Keyword Planner is suitable for testing demand and expanding the core list of keywords, but one source is usually not enough. Competitors, search suggestions, SEO services, and Search Console data are also useful for a complete core.
Combining sources helps obtain a more complete set of keywords. Afterwards, queries still undergo cleaning, clustering, and distribution across pages.
The semantic core forms the basis for the website's structure and subsequent SEO work. A high-quality collection includes demand, competitor, and search results analysis, query refinement, intent determination, SERP clustering, and the assignment of groups to landing pages.
If you need to order a semantic core for your website, send Seo-Gen the project address, the region you're promoting, and your main business areas. After assessing the structure, we can determine the scope of work, the cost of compiling the semantic core, and the format of the final file.
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More on: Collection of the semantic core
When is it worth ordering semantic core collection?
Ordering a semantic core is useful when decisions need to be made about website structure based on real search data. This applies to a new project, redesign, catalog expansion, launching a new feature, or situations where current pages have been underperforming for a long time without a noticeable increase in visibility.
For existing websites, semantic analysis is often combined with an analysis of existing URLs. This approach helps preserve pages that show potential, identify gaps in the structure, and identify queries that require a dedicated landing page.
If a company plans to commission website semantics, it's advisable to determine the key business areas, target regions, and language versions in advance. This information influences the search query set, SERP clustering results, and the final scope of work.
Before launching a new website
It's best to assemble the semantic core before finalizing the structure of a new project. This way, categories, subcategories, service pages, and information sections are created based on search demand, and the developer doesn't have to rework the architecture after the website launches.
First, business areas and keywords are studied, followed by an analysis of competitors, search suggestions, and related phrases. After cleaning and grouping, it becomes clear how many landing pages are actually needed and which clusters can be combined.
This procedure reduces the number of random pages and lowers the likelihood of duplicates. The SEO structure is developed simultaneously with the website, so the project's semantics are used even before the design and main content are prepared.
Before changing the structure of an existing site
When reworking an existing project, it's important to consider URLs that are already receiving impressions, rankings, and organic traffic. Therefore, semantics are compared with current pages, Google Search Console data, and the site's actual visibility.
After verification, you can determine which pages should be left unchanged, expanded with additional semantics, or merged. Queries for which the current structure does not contain a relevant landing page are considered separately.
This analysis helps avoid situations where useful URLs are removed during a redesign or where multiple new pages begin to compete with each other. Decisions on structure are made after reviewing queries and search results.
If SEO promotion does not provide the expected growth
The reason for poor performance may be incomplete semantics or incorrect distribution of queries across pages. A single URL is sometimes targeted for several different intents, even though Google displays different document types for these queries.
Checking the current core helps identify missed commercial queries, informational topics, long-tail keywords, and pages with potential cannibalization. Competitors' semantics and queries for which the site is already receiving impressions are also analyzed.
After such a review, a clear list of changes emerges: which pages to expand, which new URLs to create, which clusters to split, and which areas should not be included in the structure yet.
When expanding the range of products, services or regions
New products, services, and geographic areas require separate demand testing. The name used internally may differ from the wording users enter into Google, so limiting yourself to an internal list of terms is risky.
For a new direction, marker and related queries, search suggestions, competitor keywords, and data from professional SEO services are collected. The promotion region, search volume, and search results composition are then checked.
When launching additional language versions of a website, each version requires its own semantic core. Translating the existing Russian list typically doesn't reflect actual user wording or search demand in the other language.
Collection and clustering of the semantic core
Semantic core collection and clustering are typically performed in linked stages. First, the most complete set of relevant queries is generated, then redundant phrases are removed, and finally, the purified semantics are distributed into thematic groups.
A cluster must correspond to a single search query and be suitable for promotion on a single page. A simple keyword match is not sufficient, so in case of doubt, Google's actual search results are checked.
This approach is especially important for large projects. An online store can contain thousands of categories, subcategories, and features, while a service website can contain dozens of similar areas that require careful separation.
How is SERP clustering performed?
SERP clustering compares search results for different keywords. If Google returns many identical documents for two queries, this is one indication that the phrases may share common intent.
The match threshold depends on the method used and the project's objectives. After automatic processing, the results are manually reviewed, especially for priority commercial pages and queries with mixed search results.
This analysis helps make decisions based on the current SERP, not just similar keywords in queries. This reduces the number of poorly designed landing pages.
Why can't I group queries only by similar words?
Two phrases may contain the same words but lead the user to different types of pages. For example, one phrase might suggest purchasing a service, while another might suggest searching for instructions or comparing options.
The opposite situation also occurs regularly. Queries with different vocabulary sometimes yield identical search results and are successfully promoted on a single page.
Therefore, semantic analysis is complemented by SERP analysis. This approach brings the grouping closer to how Google interprets user queries.
Why is manual cluster checking necessary?
Automatic algorithms handle large volumes of data well, but they don't always accurately understand the business context. Errors are more common with mixed intent, local queries, new terminology, and niche services.
An SEO specialist checks contentious groups, compares document types, and, if necessary, splits or merges clusters. Special attention is paid to pages that may compete with each other.
What does the client receive after collecting the semantic core?
After completing the work, the client receives structured semantics, not a raw keyword dump. The final format depends on the project, but typically includes queries, search volume, clusters, intent, landing pages, and structural comments.
This file serves as the basis for subsequent SEO steps. It can be used to set tasks for creating new URLs, updating existing pages, preparing meta tags, writing content, and setting up internal linking.
By ordering a semantic core for your website before major revisions, you can determine the scope of the future structure in advance and avoid creating pages without confirmed search demand.
Table with search queries
The main result is conveniently presented in a table, where each row is associated with a specific query. In addition to the key itself, data is provided that helps understand its place in the structure and its subsequent use.
Example of the final table composition:
| Request | Frequency | Cluster | Intent | Chapter | Page | URL | Priority |
|---|---|---|---|---|---|---|---|
| Commercial inquiry | 590 | Cluster 1 | Commercial | Services | Service page | /service/ | High |
| Clarifying request | 170 | Cluster 1 | Commercial | Services | Service page | /service/ | Average |
| Information request | 320 | Cluster 2 | Informational | Blog | Article | /blog/topic/ | Average |
For a specific project, the set of columns may be broader. For a complex structure, subsections, page type, URL resolution, and SEO specialist commentary are added.
Distribution of requests by URL
URL mapping shows which page is responsible for each cluster. For existing projects, relevant pages are used first if their content and type match the search results.
New URLs are created only for clusters with independent intent. If several clusters are successfully promoted by a single page, there's no need to split them up to create additional landing pages.
This distribution helps avoid duplication and cannibalization. It also makes it clear which pages need to be updated and which areas require development from scratch.
Recommendations for the development of the structure
After clustering, you can see topics that aren't in the current menu or catalog. These could be new categories, subcategories, pages for individual services, useful filters, or articles.
Each structure expansion proposal is associated with a specific query cluster. This helps distinguish pages with proven demand from sections created purely to increase the number of URLs.
For large projects, it's convenient to implement recommendations in a prioritized manner. Pages with high commercial potential are worked on first, followed by additional areas and informational content.
The basis for further SEO optimization
The semantic core is used to prepare Title and Description meta tags, page headings, text structure, and technical specifications. It is also used to check internal linking between related commercial and informational pages.
Once implemented, semantics helps set up position monitoring and control site visibility across individual clusters. This is more convenient than tracking overall traffic without linking it to specific destinations.
As the site expands further, the core can be supplemented with new groups. A complete rebuild is usually only necessary if there are significant changes to the product range, geography, or structure of the project.
Semantic core for different types of websites
The approach to data collection depends on the type of project. An online store, a corporate service website, and an information portal all differ in structure, number of pages, search intent, and how users formulate queries.
The depth of clustering varies for each website type. For a store, it's necessary to analyze categories, subcategories, brands, and filters, while for services, more attention is paid to product areas, geography, and commercial modifiers.
Therefore, a custom semantic core is built for a specific structure. Using a single ready-made database for different websites rarely results in a high-quality distribution of queries.
Semantic core for an online store
The semantic core for an online store includes categories, subcategories, brands, product types, characteristics, and sales details. Additionally, informational queries are collected that can be used in the blog and linked to the relevant categories.
If you need to order a semantic core for an online store, it's helpful to first check the current catalog. Sometimes the business structure and search engine structure differ significantly, so some internal categories don't have independent demand, and popular categories aren't featured on the website.
The semantic core for an online store and its price depend primarily on the number of categories, product range, and filter depth. A large store's search volume can be tens of times higher than that of a small service website.
How to work with categories and filters?
Not every filter needs to be opened for indexing. A separate landing page requires its own search demand and a search result in which Google actually shows similar pages.
If a combination of characteristics isn't in demand, an indexed URL may create unnecessary duplicates and waste crawling resources. Therefore, filters are checked for semantics before mass page creation.
For priority combinations, you can create separate SEO pages with a clear URL, meta tags, and relevant product range. The remaining filters remain functional elements of the catalog.
Semantic core for a services website
The semantic core for service websites is built around key services, subservices, client needs, commercial specifications, and geography. Search queries containing the words "price", "cost", "order", and other indicators of commercial interest are separately checked.
For local businesses, the city or region is taken into account. For example, queries like "semantic core price Kyiv", "order semantic core in Kyiv", and general Ukrainian phrases may have different search results.
Informational queries for each service are also useful, but they shouldn't be automatically placed on the sales page. Some topics are better used for articles and linked internally to the main service.
Do I need to create a page for each request?
A separate page for each search phrase isn't necessary. A single cluster can contain dozens of phrases if they express the same intent and Google displays similar documents for them.
Excessive fragmentation creates weak URLs with similar content. Such pages are harder to maintain, and search engines may perceive them as competing documents.
The number of pages is determined after clustering and analyzing the search results. Queries are distributed based on meaning and intent, not on the "one keyword, one URL" principle.
Semantic core for an information website
Thematic clusters, user questions, and long-tail queries form the basis of an information project. Semantics helps create a content plan and determine which topics to cover in individual articles.
With a large number of articles, hierarchy is especially important. Parent topics are linked to more specific queries, and internal linking helps users navigate between related materials.
When ordering a semantic core for an informational website, we also analyze existing content. This helps avoid creating duplicate articles on topics that could be expanded on existing URLs.
How to order semantic core collection?
To get started, simply provide basic information about your website and business areas. After a preliminary analysis, we can determine the approximate volume of semantics, the complexity of the structure, and the composition of the final file.
If you need to commission semantic core collection for a website with an existing structure, it's recommended to provide access to Google Search Console data. For a new project, it's sufficient to describe the services, products, target regions, and planned languages.
Once the volume is agreed upon, queries are collected, cleaned, and grouped. The resulting semantics are transferred in a structured table and used for further SEO optimization.
Transfer of source data
To get started, you'll need a project URL or a description of the future website, a list of key services and products, the region of promotion, and the language. You can also specify the priority areas the business plans to develop first.
For an existing website, data on the current structure and access to Search Console are useful. This helps you keep track of queries for which pages are already receiving impressions and avoid missing out on promising areas.
If a project consists of several major sections, they can be assembled in stages. This format is convenient when a business plans to gradually expand its structure.
Collection, cleaning and clustering
After receiving the initial data, marker queries are generated and semantic data is collected from the approved sources. The resulting dataset is verified, cleaned, and supplemented with competitor data.
Next, the intent is determined and clustered based on search results. Controversial groups are manually verified, after which each cluster is assigned an existing or new landing page.
The result is checked for duplicates, oversized groups, and potential cannibalization. Only then is the spreadsheet prepared for transmission.
Transfer of the finished result
The client receives a file with requests, frequency, clusters, intent, and page distribution. Depending on the task, priorities and recommendations for restructuring may be added.
Once the core is in place, you can move on to creating new pages, updating existing URLs, preparing meta tags, and content assignments. Semantics remains the working foundation for further SEO.
If you need to commission a website semantic core, the cost is calculated after assessing the structure and scope of the relevant areas. For a preliminary estimate, simply submit your website address and briefly describe your priority services or categories.