Compilation. How to assemble and ungroup the semantic core: a complete guide. Free tools for compiling a semantic core

At the moment for search promotion factors such as content and structure play the most important role. However, how to understand what to write the text about, what sections and pages to create on the site? In addition to this, you need to know exactly what exactly you are interested in. target visitor your resource. To answer all these questions, you need to collect semantic core.

Semantic core- a list of words or phrases that fully reflect the theme of your site.

In the article I will tell you how to pick it up, clean it and break it into structure. The result will be a complete structure with requests clustered by pages.

Here is an example of a query engine broken down into a structure:

By clustering, I mean splitting your search queries into separate pages. This method will be relevant both for promotion in the PS of Yandex and Google. In the article I will describe completely free way creating a semantic core, but I will also show options with various paid services.

By reading this article, you will learn

• Choose the right queries for your topic
• Collect the most complete core of phrases
• Clean from uninteresting requests
• Group and create structure

Having collected the semantic core, you can

• Create a meaningful structure on the site
• Create layered menu
• Fill pages with texts and write meta descriptions and titles on them
• Collect positions of your site for queries from search engines

Collection and clustering of the semantic core

Proper compilation for Google and Yandex begins with determining the main key phrases of your subject. For example, I will demonstrate its compilation on a fictitious online clothing store. There are three ways to collect the semantic core:

1. Manual. Using the Yandex Wordstat service, you enter your keywords and manually select the phrases you need. This method is fast enough if you need to collect keys for one page, however, there are two drawbacks.
   • The accuracy of the method is lame. You can always miss some important words if you use this method.
   • You will not be able to assemble a semantic core for a large online store, although you can use the Yandex Wordstat Assistant plugin to simplify it - this will not solve the problem.
2. Semi-automatic. In this method, I'm going to use a program to build the kernel and then manually break it down into sections, subsections, pages, and so on. This method compilation and clustering of the semantic core, in my opinion, the most effective. has a number of advantages:
   • Maximum coverage of all topics.
   • Quality breakdown
3. Auto. Nowadays, there are several services that offer fully automatic kernel collection or clustering of your requests. Fully automatic option - I do not recommend for use, because. the quality of collection and clustering of the semantic core is currently quite low. Automatic query clustering - is gaining popularity and has a place to be, but you still need to combine some pages by hand, because. the system does not provide a perfect off-the-shelf solution. And in my opinion, you will just get confused and will not be able to dive into the project.

To compile and cluster a full-fledged correct semantic core for any project, in 90% of cases I use a semi-automatic method.

So, in order for us to do the following steps:

1. Selection of queries for topics
2. Collecting the kernel by request
3. Purging of non-targeted requests
4. Clustering (we break phrases into structure)

I showed an example of selecting a semantic core and grouping for a structure above. I remind you that we have an online clothing store, let's start to disassemble 1 item.

1. Selection of phrases for your subject

At this stage, we need the Yandex Wordstat tool, your competitors and logic. In this step, it is important to collect a list of phrases that are thematic high-frequency queries.

How to select queries to collect semantics from Yandex Wordstat

Go to the service, select the city (s) / region (s) you need, drive in the most “fat” requests in your opinion and look at the right column. There you will find the thematic words you need, both for other sections, and frequency synonyms for the entered phrase.

How to select queries before compiling a semantic core with the help of competitors

Enter in search engine the most popular searches and select one of the most popular sites, many of which you probably already know.

Pay attention to the main sections and save yourself the phrases you need.

At this stage, it is important to do the right thing: to cover all kinds of words from your subject as much as possible and not miss anything, then your semantic core will be as complete as possible.

Applied to our example, we need to make a list of the following phrases/keywords:

• Cloth
• Shoes
• Boots
• Dresses
• T-shirts
• Underwear
• Shorts

What phrases to enter is meaningless: women's clothing, buy shoes, prom dresses, etc. Why?— These phrases are “tails” of the queries “clothes”, “shoes”, “dresses” and will be added to the semantic core automatically at the 2nd stage of collection. Those. you can add them, but that would be pointless double work.

What keys do you need to enter?"half boots", "boots" are not the same as "boots". It is the word form that is important, and not whether these words have the same root or not.

Someone will have a long list of key phrases, and for someone it consists of one word - do not be alarmed. For example, for an online store of doors, the word “doors” is quite possibly enough to compose the semantic core.

And so, at the end of this step, we should have a similar list.

2. Collection of queries for the semantic core

For the correct full-fledged collection, we need a program. I will show an example simultaneously on two programs:

• On a paid one - KeyCollector. For those who have or want to buy.
• On the free - Slovoeb. Free program for those who are not ready to spend money.

Opening the program

We create new project and call it, for example, Mysite

Now, to further collect the semantic core, we need to do a few things:

Create a new Yandex mail account (it is not recommended to use the old one due to the fact that it can be banned for many requests). So, you have created an account, for example [email protected] with password super2018. Now you need to specify this account in the settings as ivan.ivanov:super2018 and click the "save changes" button below. More details in the screenshots.

We select a region for compiling a semantic core. You need to select only those regions in which you are going to advance and click save. The frequency of requests and whether they will fall into the collection in principle will depend on this.

All settings are completed, it remains to add our list of key phrases prepared at the first step and click the "start collecting" button of the semantic core.

The process is fully automatic and quite long. You can make coffee for now, and if the topic is wide, for example, like the one we collect, then it’s for a few hours 😉

As soon as all the phrases are collected, you will see something like this:

And at this stage is over - proceed to the next step

3. Cleaning the semantic core

First, we need to remove requests that are not of interest to us (non-targeted):

• Associated with another brand, such as "gloria jeans", "ekko"
• Information queries, e.g. "I wear boots", "Jean size"
• Similar topics, but not related to your business, for example, “used clothes”, “wholesale clothes”
• Requests that are not related to the topic in any way, for example, “Sims dresses”, “Puss in Boots” (there are quite a lot of such requests after selection in the semantic core)
• Requests from other regions, metro, districts, streets (it doesn’t matter which region you collected requests for - another region still comes across)

Cleaning must be done manually as follows:

We enter the word, press "Enter", if in our created semantic core it finds exactly the phrases that we need, select the found one and press delete.

I recommend that you enter the word not in its entirety, but using a construction without prepositions and endings, i.e. if we write the word "glory", it will find the phrases "buy jeans at gloria" and "buy jeans at gloria". When writing "gloria" - "gloria" would not be found.

Thus, you need to go through all the points and remove queries that you do not need from the semantic core. This can take a significant amount of time, and you may end up removing most of the collected requests, but the result will be a complete clean and correct list of all possible promoted requests for your site.

Upload now all your queries to excel

You can also bulk remove non-target queries from the semantics, provided you have a list. You can do this with stop words, and it's easy to do for a typical group of words with cities, subways, streets. You can download a list of such words that I use at the bottom of the page.

4. Clustering the semantic core

This is the most important and interesting part - we need to divide our requests into pages and sections, which together will create the structure of your site. A bit of theory - how to guide when splitting requests:

• Competitors. You can pay attention to how the semantic core of your competitors from the TOP is clustered and do the same, at least with the main sections. And also see which pages are in the search results for low-frequency queries. For example, if you're not sure "do or don't" a separate section for "red leather skirts", then type the phrase into a search engine and see the results. If the search results contain resources where there are such sections, then it makes sense to make a separate page.
• Logics. Do the whole grouping of the semantic core using logic: the structure should be understandable and represent in your head a structured tree of pages with categories and subcategories.

And a couple more tips:

• It is not recommended to put less than 3 queries per page.
• Do not make too many levels of nesting, try to make sure that there are 3-4 of them (site.ru/category/subcategory/sub-subcategory)
• Do not make long URLs, if you have many levels of nesting when clustering the semantic core, try to shorten the url of categories high in the hierarchy, i.e. instead of "your-site.ru/zhenskaya-odezhda/palto-dlya-zhenshin/krasnoe-palto" do "your-site.ru/zhenshinam/palto/krasnoe"

Now to practice

Kernel Clustering by Example

To begin with, we will divide all requests into main categories. Looking at the logic of competitors, the main categories for a clothing store will be: men's clothing, women's clothing, children's clothing, as well as a bunch of other categories that are not tied to gender / age, such as just “shoes”, “outerwear”.

We group the semantic core with the help of Excel. Open our file and act:

1. Divided into main sections
2. We take one section and break it into subsections

I will show on the example of one section - men's clothing and its subsections. In order to separate some keys from others, you need to select the entire sheet and click conditional formatting-> cell selection rules-> text contains

Now in the window that opens, write "husband" and press enter.

Now all of our menswear keys are highlighted. It is enough to use the filter to separate the selected keys from the rest of our collected semantic core.

So let's turn on the filter: you need to select the column with queries and click sort and filter-> filter

And now let's sort

Create a separate sheet. Cut the highlighted lines and paste them there. In this way, you will need to further break the kernel.

Change the name of this sheet to "Men's Clothing", a sheet where the rest of the semantic core is called "All Queries". Then create another sheet, name it "Structure" and put it as the very first one. On the page with the structure, create a tree. You should end up like this:

Now we need to divide the large menswear section into sub-sections and sub-subsections.

For ease of use and navigation through your clustered semantic core, put links from the structure to the corresponding sheets. To do this, click right click click on the desired item in the structure and do as in the screenshot.

And now you need to methodically separate requests with your hands, simultaneously deleting what you might not have been able to notice and remove at the stage of cleaning the kernel. Ultimately, thanks to semantic core clustering, you should end up with a structure similar to this one:

So. What we have learned to do:

• Select the queries we need to collect the semantic core
• Collect all-possible phrases for these queries
• Clean up "garbage"
• Cluster and create structure

What you can do next by creating such a clustered semantic core:

• Create a website structure
• Create a menu
• Write texts, meta descriptions, titles
• Collect positions to track the dynamics of requests

Now a little about programs and services

Programs for collecting the semantic core

Here I will describe not only programs, but also plug-ins and online services that I use.

• Yandex Wordstat Assistant is a plugin that makes it convenient to select queries from wordstat. Great for quickly compiling a core for a small site or 1 page.
• Keycollector (slovoeb - free version) - complete program for clustering and creating a semantic core. Enjoys great popularity. A huge amount of functionality in addition to the main direction: Selection of keys from a bunch of other systems, the possibility of autoclustering, collecting positions in Yandex and Google, and much more.
• Just-magic is a multifunctional online service for compiling the core, auto splitting, checking the quality of texts and other functions. The service is shareware, for full-fledged work you need to pay a monthly fee.

Thanks for reading the article. Thanks to this step-by-step manual, you will be able to compose the semantic core of your site for promotion in Yandex and Google. If you have any questions - ask in the comments. Below are bonuses.

An article on how to create a semantic core on your own so that your online store is in the first positions of search engine results. The process of selecting keywords is not so simple. It will require attention and a relatively long time. But if you are ready to move forward and grow your business, this article is for you.It details the methods for collecting keywords, as well as which tools can help you with this.

The answer is banal - for the site to be "liked" by search engines. And so that when users request for specific keywords, it is your resource that is given out.

And the formation of the semantic core is the first, but very important and confident step towards the goal!

The next step is the creation of a kind of skeleton, which means distributed matched "keys" for certain pages of the site. And only after that you should move to a new level - writing and implementing articles, tags.

Note that the network presents several options for defining the concept of a semantic core (hereinafter referred to as SN).

In general, they are similar and if you summarize everything, you can form the following: a set of keywords (as well as related phrases and forms) to promote the site. Such words accurately characterize the direction of the site, reflect the interests of users and correspond to the activities of the company.

Our article provides an example of the formation of a SL for an online bed linen store. The whole process is divided into five consecutive stages.

1) We collect basic queries

In this case, we are talking about all the phrases that will correspond to the direction of the store. Therefore, it is so important to think over as precisely as possible those phrases that best characterize the goods presented in the catalog.

Of course, this is sometimes difficult to do. But the right column of Wordstat.Yandex will come to the rescue - it indicates phrases that are most often entered by users when using the phrase you have chosen.

Watch the Wordstat video (13 minutes total)

In order to get the results, enter the phrase you need in the service line and click on the "Select" button.

In order not to copy all requests manually, we recommend using the Wordstat Helper extension, created specifically for Mozilla browsers Firefox and Google Chrome. This addition will greatly simplify the work with the selection of words. How it works - see the screenshot below.

Save the selected words in a separate document. After brainstorming and add to it the phrases that you come up with.

2) How to expand SA: three options

The first step is relatively simple. Although it will require you to be careful. But the second is active brain activity. After all, each separately selected phrase is the basis of the future group of search queries by which you will advance.

To assemble such a group, you must use:

• synonyms;
• paraphrasing.

In order not to "download" at this stage, use special applications or services. How to do this is detailed below.

How to Expand Your BR with Google Keyword Planner

Let's go to the topic chapter (it's called the Keyword Planner) and collects those phrases that most accurately characterize the group of queries you are interested in. Do not touch other parameters and click on the "Get ..." button.

After that, just download the results.

How to extend CL with Serpstat (ex. Prodvigator)

You can also use another similar service that analyzes a competitor. After all, competitors are the best place to get the keywords you need.

Serpstat service (ex. Prodvigator) allows you to accurately determine for which key queries your competitors have become leaders in search engines. Although there are other services - which one to use, decide for yourself.

In order to select search queries, you need:

• enter one request;
• indicate the region of promotion you are interested in;
• click on the "Search" button;
• and when it is completed, select the "Search queries" option.

Then click on the "Export Table" button.

How to compose a semantic core: how to expand the CL using the Key Collector/Slovoeb

Do you have a large store with a huge number of products? In such a situation, you need a service Key Collector.

Although if you are just starting to learn the science of keyword selection and the formation of a semantic core, we recommend that you pay attention to another service - with a dissonant name Slovoeb . Its advantage is that it is completely free.

Download the app, go to the Yandex.Direct settings and enter your username/password from mailbox Yandex.

After that:

• open a new project;
• click on the Data tab;
• there click on the option Add phrases;
• indicate the region of promotion you are interested in;
• enter the requests that were generated earlier.

After that, start collecting SA from Wordstat.Yandex. For this:

• go to the "Data collection" section;
• then - you need to select the section "Batch collection of words from the left column";
• a new window will appear on your screen;
• in it - do as indicated in the screenshot below;

It should be noted that Key Collector is an excellent tool for voluminous, large projects and with its help it is easy to organize the collection of statistical data on services that analyze the "work" of competing sites. For example, these services include the following: SEMrush, SpyWords, Serpstat (ex. Prodvigator) and many others.

3) Remove extra "keys"

So, the base is formed. The volume of collected "keys" is more than solid. But if you analyze them (in this case, just read carefully), it turns out that not all the collected words correspond exactly to the theme of your store. And therefore, “non-target” users will come to the site using them.

Such words should be removed.

We present one more example. So, on the site you sell bed linen, but your assortment does not just have a fabric from which such linen can be sewn. Therefore, everything related to fabrics must be removed.

By the way, a complete list of such words will have to be generated manually. There is no "automatic" will not help. Naturally, it will take a relatively long time and in order not to miss anything, we recommend that you arrange a full-fledged brainstorming session.

We note the following types and types of words that will be irrelevant for online stores:

• the name and mention of competing stores;
• cities and regions in which you do not work and where you do not deliver goods;
• all words and phrases containing "free", "old" or "used", "download", etc.;
• the name of a brand that is not represented in your store;
• "keys" in which there are errors;
• repetitive words.

Now we will tell you how to remove all the words you do not need.

Form a list

We open the Slovoeb service, select the "Data" section in it, and there we go to the "Stop words" tab and "drive" manually selected words into it. Interestingly, you can write down the words either manually or simply upload a file with them (if you have prepared one).

Thus, you can quickly eliminate stop words from your list that do not correspond to the theme and features of the store.

How to compose a semantic core: a quick filter

You have received a kind of blank SA. Carefully analyze it and start removing unnecessary words manually. The same Slovoeb service will help to optimize the solution of this problem. Here is the sequence of steps you need to follow:

• take the first unnecessary word from your list, for example, let it be the city of Kyiv;
• drive it into the search (on the screen - the number 1);
• mark the appropriate lines;
• by clicking on them with the right mouse button, delete;
• press Enter in the search field to return to the original list.

Repeat the above steps as many times as necessary until you have reviewed the most possible list of words.

4) How to make a semantic core: we group queries

In order to understand how to distribute words on specific pages, you should group all the queries you have selected. To do this, it is necessary to form the so-called semantic clusters.

This concept means a group of “keys” similar in subject matter and meaning, which is drawn up in the form of a multi-level structure. Let's say the first-level cluster is the search query "bedding". But the clusters of the second level will be the search queries "blankets", "plaids" and the like.

In most cases, the definition of clusters is carried out during brainstorming. But it is important to have an excellent understanding of the assortment, the features of your product, but also take into account how the structure of competitors is built.

The next thing to look out for Special attention- at the last level of the cluster, there should be only those requests that exactly correspond to the only need of potential customers. That is, a specific type of goods.

Here the same Slovoeb service and the Quick Filter option described above will come to your aid again. It will help sort search queries into certain categories.

To perform this sorting, you need to perform several simple steps. First in search line service, enter a keyword that will be used when naming:

• categories;
• landing page, etc.

For example, it could be a brand of bed linen. In the results, mark the phrases that suit you and copy.

Those phrases that you do not need, just select the right mouse button and delete.

On the right side of the service menu do new group, naming it appropriately. For example, the brand name.

To transfer the phrases you have chosen to this part of the tab, you must select the Data line and click on the Add phrases inscription. For details, see screenshot.

Pressing Enter in the search box will return you to the original list of words. Follow the described procedure with all other requests.

The system will issue all selected phrases in alphabetical order, which makes it easier to work with them - you can easily determine what exactly can be deleted. Or group the words into a specific group.

We add that manual grouping also requires a sufficient amount of time. Especially when it comes to too many key phrases. Therefore, we recommend using automated paid programs. These include:

• key collector;
• Rush Analytics;
• Just-Magic and others.

There is also a completely free Devaka.ru script. By the way, note that it is often necessary to combine some types of queries.

Since there is no point in piling up a huge number of categories on the site, differing only in such names as “Beautiful bed linen” and “Fashion bed linen”.

To determine the importance of each individual key phrase for a particular category, simply transfer them to the Google planner, as shown in the screenshot.

Thus, you can determine how in demand a particular search query is. All of them can be divided into three categories, depending on the particular use:

• high-frequency;
• low-frequency;
• midrange;
• and even micro-low frequencies.

However, it is important to understand that there are no exact numbers that indicate whether a request belongs to a particular group. Here you should focus on the subject of both the site itself and the request. In a separate case, a request with a frequency of up to 800 per month can be considered low-frequency. In another situation, a request with a frequency of up to 150 will be high-frequency.

The most high-frequency requests from all selected ones will subsequently be included in the tags. But it is recommended to use the lowest frequencies in order to optimize specific store pages for them. Since there will be low competition among such queries, it is enough to simply fill such subsections with high-quality text descriptions so that the pages appear in the first rows of search results.

All of the above actions will allow you to form a clear structure in which there will be:

• all the necessary and important categories - to visualize the "skeleton" of your store, use the additional service XMind ;
• landing pages;
• pages that contain important information for the user - for example, with contact details, with a description of delivery conditions, etc.

How to extend the semantic core: an alternative method

With the development of the site, the expansion of the store, the SA will also increase. To do this, it is necessary to monitor and collect key phrases within each group. This greatly simplifies and speeds up the process of expanding the SA.

To collect similar requests, for a hint, use additional services, including:

• Serpstat (ex. Prodvigator);
• Ubersuggest;
• KeywordTool;
• and others.

The screenshot below shows how to use the Promoter service.

How to make a semantic core: what to do after passing our instructions

So, in order to independently create a CL for an online store, you need to perform a number of sequential steps.

It all starts with the selection of keywords that can only be used when searching for your products and which will subsequently become the main group of queries. Further, using the tools of search engines to expand the semantic core. It is also recommended to analyze competitor sites for this.

The next steps will be:

• analysis of all selected search queries;
• deleting requests that do not match the meaning of your store;
• grouping requests;
• formation of the site structure;
• constant tracking of search queries and extension of the SA.

The method of selecting a SL for an online store presented in this article is far from the only true and correct one. There are others. But we tried to present you the most convenient way.

Naturally, such indicators as the quality of text descriptions, articles, tags, store structure are also important for promotion. But we will talk about this in a separate article.

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Like almost all other webmasters, I make up the semantic core with the help of Key programs Collector is definitely the best program to compose the semantic core. How to use it is a topic for a separate article, although the Internet is full of information on this subject - I recommend, for example, a manual from Dmitry Sidash (sidash.ru).

Since the question was raised about the example of compiling the kernel, I give an example.

List of keys

Suppose we have a site dedicated to British cats. I drive the phrase "British cat" into the "List of phrases" and click on the "Parse" button.

I get a long list of phrases, which will begin with the following phrases (the phrase and particularity are given):

British cats 75553 British cats photo 12421 British Fold cat 7273 British cattery 5545 British breed cats 4763 British Shorthair cat 3571 colors of British cats 3474 British cats price 2461 cat blue British 2302 British Fold cat photo 2224 mating British British cats 1888 British cats character 1394 buy British buy a cat 1179 british cats 1179 longhair british cat 1083 pregnancy of british cat 974 cat british chinchilla 969 cats of british breed photo 953 cattery of british cats moscow 886 color of british cats photo 882 british cats care 855 british shorthair cat photo 840 scottish and british cats 763 british cat names 762 British blue cat photo 723 photo of British blue cat 723 British black cat 699 what to feed British cats 678

The list itself is much longer, I just gave the beginning of it.

Key grouping

Based on this list, I will have articles on the site about the varieties of cats (lop-eared, blue, short-haired, long-haired), there will be an article about the pregnancy of these animals, about what to feed them, about names, and so on down the list.

For each article, one main such query is taken (= the topic of the article). However, the article is not limited to just one request - other queries that are suitable in meaning are also added to it, as well as different variations and word forms of the main query, which can be found in the Key Collector below in the list.

For example, with the word "lop-eared" there are the following keys:

British Fold cat 7273 British Fold cat photo 2224 British Fold cat price 513 British Fold cat breed 418 British Blue Fold cat 224 Scottish Fold and British cats 190 British Fold cat photo 169 British Fold cat photo price 16 0 british fold cat buy 156 british fold blue cat photo 129 british fold cats character 112 british fold cat grooming 112 mating of british fold cats 98 british shorthair fold cat 83 color of british fold cats 79

To avoid overspam (and overspam can also be due to the combination of using too many keys in the text, in the title, in, etc.), I would not take them all with the inclusion of the main query, but individual words from them make sense use in the article (photo, buy, character, care, etc.) in order for the article to rank better for a large number of low-frequency queries.

Thus, under the article about lop-eared cats, we will form a group of keywords that we will use in the article. Groups of keywords for other articles will be formed in the same way - this is the answer to the question of how to create the semantic core of the site.

Frequency and competition

There is also an important point related to the exact frequency and competition - they must be collected in the Key Collector. To do this, select all queries with checkboxes and on the "Yandex.Wordstat frequencies" tab, click the "Collect frequencies "!" - the exact particularity of each phrase will be shown (that is, with this word order and in this case), this is a much more accurate indicator than the overall frequency.

To check the competition in the same Key Collector, you need to click the "Get data for Yandex PS" (or for Google), then click "Calculate KEI from the available data". As a result, the program will collect how many main pages for this query are in the TOP-10 (the more - the more difficult it is to get there) and how many pages in the TOP-10 contain such a title (similarly, the more - the more difficult it is to break into the top).

Then we need to act on the basis of our strategy. If we want to create a comprehensive site about cats, then the exact frequency and competition are not so important to us. If we only need to publish a few articles, then we take queries that have the highest frequency and at the same time the lowest competition, and write articles based on them.

The semantic core is a set of search phrases and words that are used to promote the site. These search words and phrases help the robots to determine the subject of the page or the entire service, that is, to find out what the company does.

In Russian, semantics is a branch of the science of language that studies the semantic content of the lexical units of a language. Applied to search engine optimization this means that the semantic core is the semantic content of the resource. It helps to decide what information to convey to users and in what way. Therefore, semantics is the foundation, the basis of all SEO.

What is the semantic core of the site for and how to use it?

• The correct semantic core is necessary to accurately calculate the cost of promotion.
• Semantics is a vector for building internal seo-optimization: the most relevant queries are selected for each service or product so that users and search robots find them better.
• Based on it, the site structure and texts for thematic pages are created.
• Keys from semantics are used to write snippets ( short descriptions pages).

Here is the semantic core - an example of its compilation in a company website for a construction company website:

The optimizer collects semantics, parses it into logical blocks, finds out the number of their impressions, and based on the cost of requests in the top of Yandex and Google, calculates the total cost of promotion.

Of course, when selecting a semantic core, the specifics of the company's work are taken into account: for example, if the company did not design and build houses from glued beams, then we would delete the corresponding queries and not use them in the future. Therefore, an obligatory stage of working with semantics is its coordination with the customer: no one knows the specifics of the company's work better than him.

Types of keywords

There are several parameters by which keywords are classified.

1. By frequency
   • high-frequency - words and phrases with a frequency of 1000 impressions per month;
   • mid-frequency - up to 1000 impressions per month;
   • low-frequency - up to 100 impressions.

Collecting frequency by keywords helps you find out what users most often request. But a high-frequency query is not necessarily a highly competitive query, and compiling semantics with high frequency and low competition is one of the main aspects in working with a semantic core.

2. Type:
   • geo-dependent and non-geo-dependent - promotions tied to the region and not tied;
   • informational - according to them, the user receives some information. Keys of this type are usually used in articles - for example, reviews or useful tips;
   • branded - contain the name of the promoted brand;
   • transactional - implying an action from the user (buy, download, order) and so on.
3. Other types are those that are difficult to attribute to any type: for example, the key is “profiled timber”. By entering such a request into a search engine, the user can mean anything: the purchase of timber, properties, comparisons with other materials, and so on.

   From the experience of our company, we can say that it is very difficult to promote any site for such requests - as a rule, these are high-frequency and highly competitive, and this is not only difficult to optimize, but also expensive for the client.

How to build a semantic core for a website?

• By analyzing competitor sites (in SEMrush, SerpStat, you can see the semantic core of competitors):

The process of compiling a semantic core

The collected requests are not yet the semantic core, here it is still necessary to separate the wheat from the chaff so that all requests are relevant to the client's services.

To make up the semantic core, requests must be clustered (divided into blocks according to the logic of the service). You can do this with the help of programs (for example, KeyAssort or TopSite) - especially if the semantics is voluminous. Or manually evaluate and sort through the entire list, remove inappropriate requests.

Then send to the client and check if there are any errors.

The finished semantic core is a yellow brick path to the content plan, blog articles, texts for product cards, company news, and so on. This is a table with the needs of the audience that you can satisfy using your site.

• Distribute the keys across pages.
• Use keywords in meta tags