Create a semantic core. Drawing up a semantic core. Free tools for creating a semantic core

The semantic core (abbreviated as SA) is a specific list of keywords that best describe the theme of the site.

Why do you need to create a semantic core of a website?

• the semantic core characterizes, it is thanks to it that the robots indexing the page determine not only the naturalness of the text, but also the topic in order to include the page in the appropriate search section. It is obvious that the robots work with complete autonomy after entering the site page address into the search resource database;
• a well-written message is the semantic basis of the site and reflects a suitable structure for SEO promotion;
• each page of the site, accordingly, is linked to a specific part of the web resource;
• thanks to the semantic core, a promotion strategy in search engines is formed;
• Based on the semantic core, you can estimate how much promotion will cost.

Basic rules for compiling a semantic core

To collect synonyms, you will need to collect sets of keywords. In this regard, you need to evaluate your strengths in relation to promotion for high- and medium-frequency queries. If you want to get the maximum number of visitors on a budget, you need to use high- and mid-frequency queries. If on the contrary, then medium- and low-frequency queries.

Even if you have a high budget, it makes no sense to promote your site only for high-frequency queries. Often such requests are too general in nature and have an unspecific meaning, for example “listen to music”, “news”, “sports”.

When selecting search queries, many indicators are analyzed that correspond to the search phrase:

• number of impressions (frequency);
• number of impressions without morphological changes and phrases;
• pages that are returned by a search engine when a search query is entered;
• pages in the TOP search for key queries;
• estimation of the cost of promotion upon request;
• keyword competition;
• predicted number of transitions;
• bounce rate (closing a website after clicking on a link) and seasonality of the service;
• geodependence of the keyword (geographical location of the company and its clients).

How can you collect a semantic core

In practice, the selection of a semantic core can be carried out using the following methods:

Competitors' websites can become a source of keywords for the semantic core. This is where you can quickly select keywords, as well as determine the frequency of their “surroundings” using semantic analysis. To do this, you will need to make a semantic assessment of a page of text; the most mentioned words form the morphological core;

We recommend creating your own semantic core based on statistics of special services. Use, for example, Wordstat Yandex - a statistical system of the Yandex search engine. Here you can see the frequency of the search query, as well as find out what users are searching for along with this keyword;

System “hints” appear when you try to enter a search phrase into the interactive line. These words and phrases can also be included in the SL as connected ones;

The source of keywords for synonyms can be closed databases of search queries, for example, the Pastukhov database. These are special data sets containing information about effective combinations of search queries;

Internal site statistics can also become a source of data about search queries that interest the user. It contains information about the source and knows where the reader came from, how many pages he viewed and what browser he came from.

Free tools for compiling a semantic core:

Yandex.Wordstat- a popular free tool used in compiling a semantic core. Using the service, you can find out how many times visitors entered a specific query into the Yandex search engine. Provides the opportunity to analyze the dynamics of demand for a given request by month.

Google AdWords is one of the most used systems for leaving the semantic core of a site. Using Google's keyword planner, you can calculate and forecast impressions for specific queries in the future.

Yandex.Direct Many developers use the most profitable keywords to select them. If in the future it is planned to place advertisements on the site, then the owner of the resource will receive a good profit with this approach.

Word fucker- the younger brother of Kay Collector, who is used to compile the semantic core of the site. Data from Yandex is taken as a basis. The advantages include an intuitive interface, as well as accessibility not only for professionals, but also for beginners who are just starting to engage in SEO analytics.

Paid tools for compiling a semantic core:

Pastukhov bases According to many experts, they have no competitors. The database displays queries that neither Google nor Yandex show. There are many other features inherent specifically to Max Pastukhov’s databases, among which we can note a convenient software shell.

SpyWords- an interesting tool that allows you to analyze competitors' keywords. With its help, you can conduct a comparative analysis of the semantic cores of the resources of interest, as well as obtain all the data about the PPC and SEO companies of competitors. The resource is Russian-language, understanding its functionality will not pose any problems.

A paid program created specifically for professionals. Helps to create a semantic core by identifying relevant queries. Used to estimate the cost of promoting a resource using keywords of interest. In addition to a high level of efficiency, this program is distinguished by its ease of use.

SEMrush allows you to determine the most effective keywords based on data from competing resources. With its help, you can select low-frequency queries characterized by a high level of traffic. As practice shows, for such requests it is very easy to promote a resource to the first positions in the search results.

SeoLib- a service that has won the trust of optimizers. It has quite a lot of functionality. Allows you to correctly compose a semantic core, as well as perform the necessary analytical activities. In free mode, you can analyze 25 requests per day.

Promoter allows you to collect the primary semantic core in just a few minutes. This service is used mainly for analyzing competing sites, as well as for selecting the most effective key queries. Word analysis is selected for Google in Russia or for Yandex in the Moscow region.

The semantic core is assembled quite quickly if you use sources and databases as a hint.

The following processes should be highlighted

Based on the content of the site and relevant topics, key queries are selected that most accurately reflect the meaning of your web portal.
- From the selected set, unnecessary queries are eliminated, possibly those queries that can worsen the indexing of the resource. Keyword filtering is carried out based on the results of the analysis described above.
- The resulting semantic core should be evenly distributed between the pages of the site; if necessary, texts with a specific topic and volume of keywords are ordered.

An example of collecting a semantic core using the Wordstat Yandex service

For example, you are promoting a nail salon in Moscow.

We think and select all sorts of words that suit the theme of the site.

Activity of the company

• manicure salon;
• nail salon;
• nail service studio;
• manicure studio;
• pedicure studio;
• nail design studio.

General name of services

Pedicure;
- manicure;
- nail extensions.

Now we go to the Yandex service and enter each request, having previously selected the region in which we are going to move.

We copy all the words into Excel from the left column, plus auxiliary phrases from the right.

We remove unnecessary words that do not fit the topic. The words that fit are highlighted in red below.

The number of 2320 queries shows how many times people typed this query, not only in its pure form, but also as part of other phrases. For example: manicure and price in Moscow, price for manicure and pedicure in Moscow, etc.

If we enter our query in quotation marks, then there will be another number here, which takes into account the word forms of the key phrase. for example: manicure prices, manicure prices, etc.

If you enter the same query, a query in quotation marks with exclamation marks, we will see how many times users typed the query “manicure price.”

Next, we break down the resulting list of words into site pages. For example, we will leave high-frequency queries on the main page and on the main sections of the site, such as manicure, nail studio, nail extensions. We will distribute the mid- and low-frequency ones over the remaining pages, for example: manicure and pedicure prices, gel nail extension design. Words should also be divided into groups according to meaning.

• Home page - studio, nail salon, etc.
• 3 sections - pedicure, manicure, prices for manicure and pedicure.
• Pages - nail extensions, hardware pedicure, etc.

What mistakes can be made when compiling the SYNOPSIS?

When compiling a semantic core, no one is immune from errors. The most common ones include the following:

1. There is always a danger of choosing ineffective queries that provide a minimum number of visitors.
2. When re-promoting a site, you should not completely change the content posted on the site. Otherwise, all previous parameters will be reset, including ranking in search results.
3. You should not use queries that are incorrect for the Russian language; search robots are already good at identifying such queries and, if they are spammed with keywords, they remove the page from the search.

We wish you good luck in promoting your site!

Often, novice webmasters, faced with the need to create a semantic core, do not know where to start. Although there is nothing complicated in this process. Simply put, you need to collect a list of key phrases that Internet users use to search for information on your website.

The more complete and accurate it is, the easier it is for a copywriter to write a good text, and for you to get high positions in searches for the right queries. How to correctly compose large and high-quality semantic cores and what to do with them next so that the site reaches the top and collects a lot of traffic will be discussed in this material.

The semantic core is a set of key phrases, ungrouped by meaning, where each group reflects one need or desire of the user (intent). That is, what a person thinks about when typing his query into the search bar.

The entire process of creating a kernel can be represented in 4 steps:

1. We are faced with a task or problem;
2. We formulate in our heads how we can find its solution through a search;
3. We enter a request into Yandex or Google. Besides us, other people do the same;
4. The most frequent variants of requests end up in analytics services and become key phrases that we collect and group according to needs. As a result of all these manipulations, a semantic core is obtained.

Is it necessary to select key phrases or can you do without it?

Previously, semantics was compiled in order to find the most frequent keywords on a topic, fit them into the text and get good visibility for them in the search. Over the past 5 years, search engines have been striving to move to a model where the relevance of a document to a query will be assessed not by the number of words and the variety of their variations in the text, but by assessing the disclosure of intent.

For Google, this began in 2013 with the Kolibri algorithm, for Yandex in 2016 and 2017 with Palekh and Korolev technologies, respectively.

Texts written without syntax will not be able to fully cover the topic, which means it will not be possible to compete with the TOP for high-frequency and mid-frequency queries. It makes no sense to rely on low-frequency queries - there is too little traffic for them.

If you want to successfully promote yourself or your product on the Internet in the future, you need to learn how to create the right semantics that fully reveal the needs of users.

Classification of search queries

Let's look at 3 types of parameters by which keywords are evaluated.

By frequency:

• High Frequency (HF) - phrases that define a topic. Consist of 1-2 words. On average, the number of search queries starts from 1000-3000 per month and can reach hundreds of thousands of impressions, depending on the topic. Most often, the main pages of websites are designed for them.
• Mid-frequency (MF) – separate directions in the topic. Mostly contain 2-3 words. With an exact frequency of 500 to 1000. Usually categories for a commercial site or topics for large information articles.
• Low frequency (LF) – queries related to the search for a specific answer to a question. As a rule, from 3-4 words. This could be a product card or the topic of an article. On average, searches range from 50 to 500 people per month.
• When analyzing metrics or statistics counter data, you can come across another type - micro low-frequency keys. These are phrases that are often asked once during a search. There is no point in sharpening the page for them. It is enough to be in the top for low frequencies, which includes them.

By competitiveness:

• Highly competitive (HC);
• Medium-concrete (SC);
• Low competitive (NC);

According to need:

• Navigational. Express the user’s desire to find a specific Internet resource or information on it;
• Informational. Characterized by the need to obtain information as a response to a request;
• Transactional. Directly related to the desire to make a purchase;
• Vague or general. Those for which it is difficult to accurately determine the intent.
• Geo-dependent and geo-independent. Reflect the need to search for information or complete a transaction in your city or without regional reference.

Depending on the type of site, you can give the following recommendations when selecting key phrases for the semantic core.

1. Information resource. The main emphasis should be on finding topics for articles in the form of mid-range and low-frequency queries with low competition. It is recommended to cover the topic broadly and deeply, sharpening the page for a large number of low-frequency keys.
2. Online store or commercial site. We collect HF, MF and LF, segmenting as clearly as possible so that all phrases are transactional and belong to the same cluster. We focus on finding well-converting low frequency NC keywords.

How to correctly compose a large semantic core - step-by-step instructions

We moved on to the main part of the article, where I will sequentially analyze the main stages that need to be completed to build the core of the future site.
To make the process clearer, all steps are given with examples.

Search for basic phrases

Working with the SEO core begins with selecting a primary list of basic words and phrases (VPs) that best characterize the topic and are used in a broad sense. They are also called markers.

These can be names of directions, types of products, popular queries from the topic. As a rule, they consist of 1-2 words and have tens and sometimes hundreds of thousands of impressions per month. It’s better not to use very wide keywords, so as not to drown in negative keywords at the expansion stage.

The most convenient way to select marker phrases is using . By entering a query into it, in the left column we see the phrases that it contains, in the right – similar queries from which you can often find suitable ones for expanding the topic. The service also shows the basic frequency of the phrase, that is, how many times it was asked per month in all word forms and with the addition of any words to it.

In itself, this frequency is of little interest, so to get more accurate values ​​you need to use operators. Let's figure out what it is and what it is needed for.

Yandex Wordstat operators:

1) “…” – quotation marks. A query in quotation marks allows you to track how many times a phrase was searched in Yandex with all its word forms, but without adding other words (tails).

2) ! - Exclamation point. Using it before each word in the query, we record its form and get the number of impressions in the search for a key phrase only in the specified word form, but with a tail.

3) “!... !... !...” - quotation marks and an exclamation point before each word. The most important operator for the optimizer. It allows you to understand how many times a keyword is requested per month strictly for a given phrase, as it is written, without adding any words.

4) +. Yandex Wordstat does not take into account prepositions and pronouns when making a request. If you need him to show them, put a plus sign in front of them.

5) -. The second most important operator. With its help, words that do not fit are quickly eliminated. To use it, after the analyzed phrase we put a minus sign and a stop word. If there are several of them, repeat the procedure.

6) (…|…). If you need to get data from Yandex Wordstat for several phrases at the same time, enclose them in brackets and separate them with a forward slash. In practice, the method is rarely used.

For the convenience of working with the service, I recommend installing a special browser extension “Wordstat Assistant”. Installed on Mozilla, Google Chrome, Ya.Browser and allows you to copy phrases and their frequencies with one click of the “+” or “Add all” icon.

Let's say we decide to make our blog using SEO. Let’s choose 7 basic phrases for it:

• semantic core;
• optimization;
• copywriting;
• promotion;
• monetization;
• Direct

Search for synonyms

When formulating a query to search engines, users can use words that are close in meaning, but different in spelling.

For example, “car” and “machine”.

It is important to find as many synonyms for the main words as possible in order to increase the coverage of the future semantic core. If this is not done, then during parsing we will miss a whole layer of key phrases that reveal the needs of users.

What we use:

• Brainstorm;
• Right column of Yandex Wordstat;
• Queries typed in Cyrillic;
• Special terms, abbreviations, slang expressions from the topic;
• Yandex and Google blocks - search together with the “query name”;
• Snippets of competitors.

As a result of all actions for the selected topic, we get the following list of phrases:

Basic Query Expansion

Let's parse these keywords to identify the basic needs of people in this area.
The most convenient way to do this is in the Key Collector program, but if you don’t mind paying 1,800 rubles for a license, use its free analogue - Slovoeb.

In terms of functionality, it is of course weaker, but it is suitable for small projects.
If you don’t want to delve into the operation of programs, you can use the Just-Magic and Rush Analytics service. But it’s still better to spend a little time and understand the software.

I will show the principle of operation in Key Collector, but if you work with Slovoeb, then everything will also be clear. The program interface is similar.

Procedure:

1) Add a list of basic phrases to the program and measure the basic and exact frequencies based on them. If we are planning promotion in a specific region, we indicate the regionality. For informational sites, this is most often not necessary.

2) Let's parse the left column of Yandex Wordstat using the added words to get all the queries from our topic.

3) As a result, we got 3374 phrases. Let's take the exact frequency from them, as in point 1.

4) Let’s check if there are any keys with zero base frequency in the list.

If there is, delete it and move on to the next step.

Negative words

Many people neglect the procedure for collecting negative keywords, replacing it with deleting phrases that are not suitable. But later you will realize that it is convenient and really saves time.

Open the Data -> Analysis tab in Key Collector. Select the type of grouping by individual words and scroll through the list of keys. If we see a phrase that does not fit, click the blue icon and add the word instead with all its word forms to the stop words.

In Slovoeb, working with stop words is implemented in a more simplified version, but you can also create your own list of phrases that are not suitable and apply them to the list.

Don’t forget to use sorting by Base Frequency and number of phrases. This option helps you quickly reduce the list of initial phrases or weed out rarely occurring ones.

After we have compiled a list of stop words, we apply them to our project and move on to collecting search tips.

Parsing hints

When you enter a query into Yandex or Google, search engines offer their own options for continuing it from the most popular phrases that Internet users type in. These keywords are called search suggestions.

Many of them do not fall into Wordstat, so when building a semantic one, it is necessary to collect such queries.

Kay Collector, by default parses them with a search of endings, Cyrillic and Latin alphabet and with a space after each phrase. If you are ready to sacrifice quantity in order to significantly speed up the process, check the box “Collect only the TOP hints without brute force and a space after the phrase.”

Often among search suggestions you can find phrases with good frequency and competition tens of times lower than in Wordstat, so in narrow niches I recommend collecting as many words as possible.

The time for parsing hints directly depends on the number of simultaneous calls to search engine servers. Maximum Kay Collector supports 50-thread operation.
But in order to parse requests in this mode, you will need the same number of proxies and Yandex accounts.

For our project, after collecting tips, we got 29,595 unique phrases. In terms of time, the entire process took a little more than 2 hours on 10 threads. That is, if there are 50 of them, we’ll do it in 25 minutes.

Determination of base and exact frequencies for all phrases

For further work, it is important to determine the basic and exact frequency and eliminate all zeros. We leave requests with a small number of impressions if they are targeted.
This will help you better understand the intent and create a more complete article structure than is in the top.

In order to remove the frequency, we first filter out all unnecessary things:

• repetitions of words
• keys with other symbols;
• duplicate phrases (via the “Implicit Duplicates Analysis” tool)

For the remaining phrases, we will determine the exact and base frequency.

A) for phrases up to 7 words:

• Select through the filter “Phrase consists of no more than 7 words”
• Open the “Collect from Yandex.Direct” window by clicking on the “D” icon;
• If necessary, indicate the region;
• Select the guaranteed impressions mode;
• Set the collection period to 1 month and check the boxes for the required frequency types;
• Click “Get data”.

b) for phrases of 8 words or more:

• Set the filter for the “Phrase” column – “consists of at least 8 words”;
• If you need to promote in a specific city, indicate the region below;
• Click on the magnifying glass and select “Collect all types of frequencies.”

Cleaning keywords from garbage

After we have received information about the number of impressions for our keys, we can begin to filter out those that are not suitable.

Let's look at the procedure step by step:

1. Go to “Group Analysis” of Key Collector and sort the keys by the number of words used. The task is to find non-target and frequent ones and add them to the list of stop words.
We do everything the same as in the “Minus words” paragraph.

2. We apply all the found stop words to the list of our phrases and go through it so as not to lose target queries. After checking, click “Delete Marked Phrases”.

3. We filter out dummy phrases that are rarely used in exact occurrences, but have a high base frequency. To do this, in the settings of the Key Collector program, in the “KEY&SERP” item, insert the calculation formula: KEY 1 = (YandexWordstatBaseFreq) / (YandexWordstatQuotePointFreq) and save the changes.

4. We calculate KEY 1 and delete those phrases for which this parameter is 100 or more.

The remaining keys need to be grouped by landing pages.

Clustering

The distribution of queries into groups begins with clustering phrases by top using the free program “Majento Clusterer”. I recommend a paid analogue with wider functionality and faster operating speed - KeyAssort, but the free one is quite enough for a small kernel. The only caveat is that to work in any of them you will need to buy XML limits. Average price - 5 rubles. for 1000 requests. That is, processing an average core for 20-30 thousand keys will cost 100-150 rubles. See the screenshot below for the address of the service you use.

The essence of key clustering using this method is to combine into groups those phrases that have Yandex Top 10:

• shared URLs with each other (Hard)
• with the most frequent request in the group (Soft).

Depending on the number of such matches for different sites, clustering thresholds are distinguished: 2, 3, 4 ... 10.

The advantage of this method is the grouping of phrases according to people’s needs, and not just by synonymous connections. This allows you to immediately understand which keywords can be used on one landing page.

Suitable for information specialists:

• Soft with a threshold of 3-4 and then cleaning by hand;
• Hard on 3, and then combining clusters according to the meaning.

Online stores and commercial sites, as a rule, are promoted according to Hard with a clustering threshold of 3. The topic is voluminous, so I will discuss it later in a separate article.

For our project, after grouping using the Hard method on 3, we got 317 groups.

Competition Check

There is no point in promoting for highly competitive queries. It’s difficult to get to the top, and without it there will be no traffic to the article. To understand which topics are profitable to write on, we use the following method:

We focus on the exact frequency of the group of phrases under which the article is written and the competition for Mutagen. For informational sites, I recommend taking on topics that have a total exact frequency of 300 or more, and a competitiveness coefficient of 1 to 12 inclusive.

In commercial topics, focus on the marginality of a product or service and how competitors in the top 10 are doing. Even 5-10 targeted requests per month may be a reason to make a separate page for it.

How to check competition on a request:

a) manually, by entering the appropriate phrase in the service itself or through mass tasks;

b) in batch mode through the Key Collector program.

Topic selection and grouping

Let's consider each of the resulting groups for our project after clustering and select topics for the site.
Majento, unlike Key Assort, does not allow you to download data on the number of impressions for each phrase, so you will have to additionally obtain them through Key Collector.

Instructions:

1) Upload all groups from Majento in CSV format;
2) Concatenate phrases in Excel using the “group:key” mask;
3) Load the resulting list into the Key Collector. In the settings, be sure to check the “Group:Key” import mode and not monitor the presence of phrases in other groups;

4) We remove the basic and exact frequency for keywords from the newly created groups. (If you use Key Assort, you don't need to do this. The program allows you to work with additional columns)
5) We are looking for clusters with unique intent, containing at least 3 phrases and the number of impressions for all queries totaling more than 300. Next, we check the 3-4 most frequent of them for competitiveness according to Mutagen. If among these phrases there are keys with competition less than 12, we take them to work;

6) We look through the remaining groups. If there are phrases that are close in meaning and worth considering on one page, we combine them. For groups containing new meanings, we look at the prospects for the total frequency of phrases; if it is less than 150 per month, then we postpone it until we go through the entire core. It may be possible to combine them with another cluster and get 300 exact impressions - this is the minimum from which it is worth taking the article into work. To speed up manual grouping, use auxiliary tools: quick filter and frequency dictionary. They will help you quickly find suitable phrases from other clusters;

Attention!!! How do you know that clusters can be merged? We take 2 frequency keys from those that we selected in step 5 for the landing page and 1 request from the new group.
We add them to Arsenkin’s “Upload Top 10” tool, specify the desired region if necessary. Next, we look at the number of intersections by color for the 3rd phrase with the rest. We combine groups if there are 3 or more of them. If there are no matches or one, you cannot combine - different intents, in the case of 2 intersections, look at the output by hand and use logic.

7) After grouping the keys, we get a list of promising topics for articles and semantics for them.

Removing requests for another content type

When compiling a semantic core, it is important to understand that commercial queries are not needed for blogs and information sites. Just like online stores do not need information.

We go through each group and clean out everything unnecessary; if we cannot accurately determine the intent of the request, we compare the results or use the following tools:

• Commercialization check from Pixel Tools (free, but with a daily check limit);
• Just-Magic service, clustering with a checkmark to check the commerciality of the request (paid, cost depends on the tariff)

After this we move on to the last stage.

Phrases optimization

We optimize the semantic core so that it is convenient for SEO specialists and copywriters to work with it in the future. To do this, we will leave in each group key phrases that reflect the needs of people as fully as possible and contain as many synonyms for the main phrases as possible.

Algorithm of actions:

• Let's sort the keywords in Excel or Key Collector alphabetically from A to Z;
• Let's choose those that reveal the topic from different angles and in different words. All other things being equal, we leave phrases with a higher exact frequency or which have a lower key 1 indicator (the ratio of the base frequency to the exact frequency);
• We delete keywords with less than 7 impressions per month, which do not carry new meanings and do not contain unique synonyms.

An example of what a well-composed semantic core looks like:

I marked in red phrases that do not match the intent. If you neglect my recommendations for manual grouping and do not check compatibility, it will turn out that the page will be optimized for incompatible key phrases and you will no longer see high positions for promoted queries.

Final checklist

1. We select the main high-frequency queries that set the topic;
2. We look for synonyms for them using the left and right columns of Wordstat, competitor sites and their snippets;
3. We expand the received queries by parsing the left column of Wordstat;
4. We prepare a list of stop words and apply them to the resulting phrases;
5. Parsing Yandex and Google tips;
6. We remove the base and precise frequencies;
7. Expanding the list of negative keywords. We clean from garbage and requests for pacifiers
8. We do clustering using Majento or KeyAssort. For informational sites in Soft mode, the threshold is 3-4. For commercial Internet resources using the Hard method with a threshold of 3.
9. We import the data into Key Collector and determine the competition of 3-4 phrases for each cluster with a unique intent;
10. We select topics and decide on landing pages for queries based on an estimate of the total number of accurate impressions for all phrases from one cluster (from 300 for information specialists) and competition for the most frequent of them according to Mutagen (up to 12).
11. For each suitable page, we look for other clusters with similar user needs. If we can consider them on one page, we combine them. When the need is not clear or there is a suspicion that there should be a different type of content or page as an answer to it, we check the search results or through the Pixel Tools or Just-Magic tools. For content sites, the core should consist of information requests; for commercial sites, transactional ones. We remove the excess.
12. We sort the keys in each group alphabetically and leave those that describe the topic from different angles and in different words. All other things being equal, priority is given to those queries that have a lower ratio of base frequency to exact frequency and a higher number of precise impressions per month.

What to do with the SEO core after its creation

We compiled a list of keys, gave them to the author, and he wrote an excellent article in full, revealing all the meanings. Eh, I’m daydreaming... A sensible text will only work if the copywriter clearly understands what you want from him and how to test himself.

Let’s look at 4 components, having worked them out well, you are guaranteed to receive a lot of targeted traffic to the article:

Good structure. We analyze the queries selected for the landing page and identify what needs people have in this topic. Next, we write an outline for the article that fully answers them. The task is to make sure that when people visit the site, they receive a voluminous and comprehensive answer regarding the semantics that you have compiled. This will give good behavioral and high relevance to the intent. After you have made a plan, look at your competitors' websites by typing the main promoted query into the search. You need to do it exactly in this order. That is, first we do it ourselves, then we look at what others have and, if necessary, we modify it.

Optimization for keys. We sharpen the article itself for 1-2 of the most frequent keys with competition for Mutagen up to 12. Another 2-3 mid-frequency phrases can be used as headings, but in a diluted form, that is, inserting into them additional words not related to the topic, using synonyms and word forms . We focus on low-frequency phrases from which a unique part is pulled out - the tail - and evenly introduced into the text. The search engines themselves will find and glue everything together.

Synonyms for basic queries. We write them out separately from our semantic core and set the task for the copywriter to use them evenly throughout the text. This will help reduce the density of our main words and at the same time the text will be optimized enough to get to the top.

Thematic-setting phrases. LSIs themselves do not promote the page, but their presence indicates that the written text most likely belongs to the “pen” of an expert, and this is already a plus for the quality of the content. To search for thematic phrases, we use the “Technical Specifications for a Copywriter” tool from Pixel Tools.

An alternative method for selecting key phrases using competitor analysis services

There is a quick approach to creating a semantic core that is suitable for both beginners and experienced users. The essence of the method is that we initially select keywords not for the entire site or category, but specifically for an article or landing page.

It can be implemented in 2 ways, which differ in how we choose topics for the page and how deeply we expand the key phrases:

• by parsing the main keys;
• based on competitor analysis.

Each of them can be implemented at a simple or more complex level. Let's look at all the options.

Without using programs

A copywriter or webmaster often doesn’t want to deal with the interface of a large number of programs, but he needs good themes and key phrases for them.
This method is just for beginners and those who don’t want to bother. All actions are performed without the use of additional software, using simple and understandable services.

What you will need:

• Keys.so service for competitor analysis – 1500 rub. Using promo code “altblog” - 15% discount;
• Mutagen. Checking the competitiveness of requests - 30 kopecks, collecting basic and exact frequencies - 2 kopecks per check;
• Bookvarix - free version or business account - 995 rub. (now with a discount of 695 RUR)

Option 1. Selecting a topic by parsing basic phrases:

1. We select the main keys from the topic in a broad sense, using brainstorming and the left and right columns of Yandex Wordstat;
2. Next, we look for synonyms for them, using the methods discussed earlier;
3. We enter all received marker requests into Bukvariks (you will need to pay a paid tariff) in the advanced mode “Search using a list of keywords”;
4. We indicate in the filter: “!Exact!frequency” from 50, Number of words from 3;
5. We upload the entire list to Excel;
6. We select all the keywords and send them for grouping to the Kulakov Clusterer service. If the site is regional, select the desired city. We leave the clustering threshold for informational sites at 2, for commercial sites we set it to 3;
7. After grouping, we select topics for articles by looking through the resulting clusters. We take those where the number of phrases is from 3 and with a unique intent. An analysis of the URLs of sites from the top in the “Competitors” column (on the right in the sign of Kulakov’s service) helps to better understand people’s needs. Also, don’t forget to check the competitiveness of Mutagen. We run 2-3 requests from the cluster. If everything is more than 12, then the topic is not worth taking;
8. The name of the future landing page has been decided, all that remains is to select key phrases for it;
9. From the “Competitors” field, copy 3 URLs with the appropriate type of pages (if the site is informational, we take links to articles; if it is a commercial site, then to stores);
10. We insert them sequentially into keys.so and upload all the key phrases for them;
11. We combine them in Excel and remove duplicates;
12. The service data alone is not enough, so we need to expand it. Let's use Bukvarix again;
13. The resulting list is sent for clustering to the “Kulakov Clusterer”;
14. We select groups of requests that are suitable for the landing page, focusing on intent;
15. We remove the base and exact frequency through Mutagen in the “Mass Tasks” mode;
16. We upload a list with updated data on the number of impressions in Excel. We remove zeros for both types of frequencies;
17. Also in Excel, we add a formula for the ratio of the base frequency to the exact one and leave only those keys for which this ratio is less than 100;
18. We delete requests for other types of content;
19. We leave phrases that reveal the main intention as fully as possible and in different words;
20. We repeat all the same steps in steps 8-19 for the remaining topics.

Option 2. Select a topic through competitor analysis:

1. We are looking for top sites in our field, driving in high-frequency queries and viewing the results through Arsenkin’s “Top 10 Analysis” tool. It is enough to find 1-2 suitable resources.
If we are promoting a site in a specific city, we indicate the region;
2. Go to the keys.so service and enter the urls of the sites we found and see which competitors’ pages bring the most traffic.
3. We check 3-5 of the most accurate frequency queries for competitiveness. If for all phrases it is above 12, then it is better to look for another topic that is less competitive.
4. If you need to find more sites for analysis, open the “Competitors” tab and set the parameters: similarity - 3, thematic - 10. Sort the data in descending order of traffic.
5. After we have chosen a topic, enter its name into the search results and copy 3 URLs from the top.
6. Next we repeat points 10-19 from the 1st option.

Using Key Collector or Sloboeb

This method will differ from the previous one only in the use of the Key Collector program for some operations and in a deeper expansion of the keys.

What you will need:

• Kay Collector program – 1800 rubles;
• all the same services as in the previous method.

"Advanced - 1"

1. We parse the left and right columns of Yandex for the entire list of phrases;
2. We remove the exact and basic frequency through Key Collector;
3. We calculate the indicator key 1;
4. We delete queries from zero and with key 1 > 100;
5. Next, we do everything the same as in paragraphs 18-19 of option 1.

"Advanced - 2"

1. We do steps 1-5, as in option 2;
2. We collect keys for each URL in keys.so;
3. Removing duplicates in Key Collector;
4. We repeat Points 1-4, as in the “Advanced -1” method.

Now let’s compare the number of keys received and their exact total frequency when collecting CN using different methods:

As we can see from the table, the best result was shown by the alternative method of creating a core for the page - “Advanced 1.2”. It was possible to obtain 34% more target keys, and at the same time, the total traffic across the cluster was 51% more than in the case of the classic method.

Below in the screenshots you can see what the finished kernel looks like in each case. I took phrases with an exact number of impressions from 7 per month so that I could evaluate the quality of the keywords. For full semantics, see the table at the “View” link.

A)


B)


IN)

Now you know that the most common method, as everyone does, is not always the most faithful and correct, but you shouldn’t give up other methods either. Much depends on the topic itself. For commercial sites where there are not many keys, the classic option is quite sufficient. You can also get excellent results on informational sites if you correctly draw up the copywriter’s specifications, do a good structure and SEO optimization. We will talk about all this in detail in the following articles.

3 common mistakes when creating a semantic core

1. Collecting phrases from top to bottom. It is not enough to parse Wordstat to get a good result!
More than 70% of queries that people enter rarely or periodically do not get there at all. But among them there are often key phrases with good conversion and really low competition. How not to miss them? Be sure to collect search tips and combine them with data from different sources (counters on websites, statistics services and databases).

2. Mixing information and commercial requests on one page. We have already discussed that key phrases differ according to the type of needs. If a visitor comes to your site who wants to make a purchase, and sees a page with an article as an answer to his request, do you think he will be satisfied? No! Search engines also think the same way when they rank a page, which means you can immediately forget about the top for mid-range and high-frequency phrases. Therefore, if you are in doubt about determining the type of request, look at the search results or use the Pixel Tools and Just-Magic tools to determine commerciality.

3. Choosing to promote very competitive queries. Positions for HF VC phrases depend 60-70% on behavioral factors, and to get them you need to get to the top. The more applicants, the longer the queue of applicants and the higher the requirements for sites. Everything is the same as in life or sports. Becoming a world champion is much more difficult than getting the same title in your city.
Therefore, it is better to enter a quiet niche rather than an overheated one.

Previously, getting to the top was even more difficult. At the top they stood on the principle that whoever had time, ate it. Leaders got into first place, and they could only be displaced by accumulating behavioral factors. How can you get them if you are on the second or third page... Yandex broke this vicious circle in the summer of 2015 by introducing the “multi-armed bandit” algorithm. Its essence is precisely to randomly increase and decrease the positions of sites in order to understand whether more worthy candidates have appeared to be in the top.

How much money do you need to start?

To answer this question, let’s calculate the costs of the necessary arsenal of programs and services to prepare and group key phrases into 100 articles.

The bare minimum (suitable for the classic version):

1. Word fucker - free
2. Majento clusterer - free
3. For captcha recognition - 30 rubles.
4. Xml limits - 70 rub.
5. Checking the competition of a request for Mutagen - 10 checks per day for free
6. If you are not in a hurry and are willing to spend 20-30 hours on parsing, you can do without a proxy.
—————————
The result is 100 rubles. If you enter captchas yourself, and receive xml limits in exchange for those transferred from your website, then you can actually prepare the kernel for free. You just need to spend another day setting up and mastering the programs and another 3-4 days waiting for the parsing results.

Standard set of semanticist (for advanced and classical methods):

1. Kay Collector - 1900 rubles
2. Kay Assort - 1700 rubles
3. Bukvariks (business account) - 650 rubles.
4. Competitor analysis service keys.so - 1,500 rubles.
5. 5 proxies - 350 rubles per month
6. Anti-captcha - approximately 30 rubles.
7. Xml limits - about 80 rubles.
8. Checking competition with Mutagen (1 check = 30 kopecks) - we’ll keep it to 200 rubles.
———————-
The result is 6410 rubles. You can, of course, do without KeyAssort, replacing it with a Majento clusterer and using Sloboeb instead of Key Collector. Then 2810 rubles will be enough.

Should you trust the development of the kernel to a “pro” or is it better to figure it out and do it yourself?

If a person regularly does what he loves and gets better at it, then following the logic, his results should definitely be better than those of a beginner in this field. But with the selection of keywords, everything turns out exactly the opposite.

Why does a beginner do better than a professional in 90% of cases?

It's all about the approach. The task of a semanticist is not to assemble the best kernel for you, but to complete his work in the shortest possible time and so that its quality suits you.

If you do everything yourself using the algorithms discussed earlier, the result will be an order of magnitude higher for two reasons:

• You understand the topic. This means that you know the needs of your clients or site users and will be able to maximally expand marker queries for parsing at the initial stage, using a large number of synonyms and specific words.
• Interested in doing everything well. The owner of a business or an employee of the company in which he works will, of course, approach the issue more responsibly and try to do everything to the maximum. The more complete the core and the more low-competitive queries it contains, the more targeted traffic it will be possible to collect, which means the profit will be higher for the same investments in content.

How to find the remaining 10% that will make up the core better than you?

Look for companies where the selection of key phrases is a core competency. And you immediately discuss what result you want, like everyone else or the maximum. In the second case, it will be 2-3 times more expensive, but in the long run it will pay off many times over. For those who want to order a service from me, all the necessary information and conditions. I guarantee quality!

Why is it so important to fully develop semantics?

Here, as in any area, the principle of “good and bad choices” works. What is its essence?
Every day we are faced with what we choose:

• meet a person who seems to be okay, but doesn’t attract attention, or, having understood yourself, build a harmonious relationship with the one you need;
• do a job you don’t like or find something you love and make it your profession;
• renting space for a store in a non-traffic area or waiting until it becomes available is a suitable option;
• take on the team not the best sales manager, but the one who showed himself best at today’s interview.

Everything seems to be clear. But if you look at it from the other side, imagining each choice as an investment in the future. This is where the fun begins!

Saved on this. core, 3-5 thousand. Happy as elephants! But what does this lead to next:

a) for information sites:

• Traffic losses are at least 1.5 times with the same investments in content. Comparing different methods for obtaining key phrases, we have already found out empirically that the alternative method allows you to collect 51% more;
• The project drops faster in search results. It’s easy for competitors to get ahead of us by giving a more complete answer in terms of intent.

b) for commercial projects:

• Fewer leads or higher value. If we have semantics like everyone else, then we are promoting according to the same queries as our competitors. A large number of offers with constant demand reduces the share of each of them in the market;
• Low conversion. Specific requests are better converted into sales. Saving on family kernel, we lose the most conversion keys;
• It's harder to advance. There are many people who want to be at the top - the requirements for each of the candidates are higher.

I wish you to always make a good choice and invest only in the positive!

P.S. Bonus “How to write a good article with bad semantics”, as well as other life hacks for promoting and making money on the Internet, read in my group

The semantic core is a scary name that SEOs came up with to denote a rather simple thing. We just need to select the key queries for which we will promote our site.

And in this article I will show you how to correctly compose a semantic core so that your site quickly reaches the TOP, and does not stagnate for months. There are also “secrets” here.

And before we move on to compiling the SY, let's figure out what it is and what we should ultimately come to.

What is the semantic core in simple words

Oddly enough, but the semantic core is a regular Excel file, which contains a list of key queries for which you (or your copywriter) will write articles for the site.

For example, this is what my semantic core looks like:

I have marked in green those key queries for which I have already written articles. Yellow - those for which I plan to write articles in the near future. And colorless cells mean that these requests will come a little later.

For each key query, I have determined the frequency, competitiveness, and come up with a “catchy” title. You should get approximately the same file. Now my CN consists of 150 keywords. This means that I am provided with “material” for at least 5 months in advance (even if I write one article a day).

Below we will talk about what you should prepare for if you suddenly decide to order the collection of the semantic core from specialists. Here I will say briefly - they will give you the same list, but only for thousands of “keys”. However, in SY it is not quantity that is important, but quality. And we will focus on this.

Why do we need a semantic core at all?

But really, why do we need this torment? You can, after all, just write quality articles and attract an audience, right? Yes, you can write, but you won’t be able to attract people.

The main mistake of 90% of bloggers is simply writing high-quality articles. I'm not kidding, they have really interesting and useful materials. But search engines don’t know about it. They are not psychics, but just robots. Accordingly, they do not rank your article in the TOP.

There is another subtle point with the title. For example, you have a very high-quality article on the topic “How to properly conduct business in a face book.” There you describe everything about Facebook in great detail and professionally. Including how to promote communities there. Your article is the highest quality, useful and interesting on the Internet on this topic. No one was lying next to you. But it still won't help you.

Why high-quality articles fall from the TOP

Imagine that your website was visited not by a robot, but by a live inspector (assessor) from Yandex. He realized that you have the coolest article. And hands put you in first place in the search results for the request “Promoting a community on Facebook.”

Do you know what will happen next? You will fly out of there very soon anyway. Because no one will click on your article, even in first place. People enter the query “Promoting a community on Facebook,” and your headline is “How to properly run a business in a face book.” Original, fresh, funny, but... not on request. People want to see exactly what they were looking for, not your creativity.

Accordingly, your article will empty its place in the TOP search results. And a living assessor, an ardent admirer of your work, can beg the authorities as much as he likes to leave you at least in the TOP 10. But it won't help. All the first places will be taken by empty articles, like the husks of sunflower seeds, that yesterday’s schoolchildren copied from each other.

But these articles will have the correct “relevant” title - “Promoting a community on Facebook from scratch” ( step by step, in 5 steps, from A to Z, free etc.) Is it offensive? Still would. Well, fight against injustice. Let's create a competent semantic core so that your articles take the well-deserved first places.

Another reason to start writing SYNOPSIS right now

There is one more thing that for some reason people don’t think much about. You need to write articles often - at least every week, but preferably 2-3 times a week - to get more traffic, faster.

Everyone knows this, but almost no one does it. And all because they have “creative stagnation,” “they just can’t force themselves,” “they’re just lazy.” But in fact, the whole problem lies in the absence of a specific semantic core.

I entered one of my basic keys into the search field - “smm”, and Yandex immediately gave me a dozen hints about what else might be interesting to people who are interested in “smm”. All I have to do is copy these keys into a notebook. Then I will check each of them in the same way, and collect hints on them as well.

After the first stage of collecting key words, you should end up with a text document containing 10-30 broad basic keys, which we will work with further.

Step #2 — Parsing basic keys in SlovoEB

Of course, if you write an article for the request “webinar” or “smm”, then a miracle will not happen. You will never be able to reach the TOP for such a broad request. We need to break the basic key into many small queries on this topic. And we will do this using a special program.

I use KeyCollector, but it's paid. You can use a free analogue - the SlovoEB program. You can download it from the official website.

The most difficult thing about working with this program is setting it up correctly. I show you how to properly set up and use Sloboeb. But in that article I focus on selecting keys for Yandex Direct.

And here let’s look step by step at the features of using this program for creating a semantic core for SEO.

First, we create a new project and name it by the broad key that you want to parse.

I usually give the project the same name as my base key to avoid confusion later. And yes, I will warn you against one more mistake. Don't try to parse all base keys at once. Then it will be very difficult for you to filter out “empty” key queries from golden grains. Let's parse one key at a time.

After creating the project, we carry out the basic operation. That is, we actually parse the key through Yandex Wordstat. To do this, click on the “Worstat” button in the program interface, enter your base key, and click “Start collection”.

For example, let's parse the base key for my blog “contextual advertising”.

After this, the process will start, and after some time the program will give us the result - up to 2000 key queries that contain “contextual advertising”.

Also, next to each request there will be a “dirty” frequency - how many times this key (+ its word forms and tails) was searched per month through Yandex. But I do not advise drawing any conclusions from these figures.

Step #3 - Collecting the exact frequency for the keys

Dirty frequency will not show us anything. If you focus on it, then don’t be surprised when your key for 1000 requests does not bring a single click per month.

We need to identify pure frequency. And to do this, we first select all the found keys with checkmarks, and then click on the “Yandex Direct” button and start the process again. Now Slovoeb will look for the exact request frequency per month for each key.

Now we have an objective picture - how many times what query was entered by Internet users over the past month. I now propose to group all key queries by frequency to make it easier to work with them.

To do this, click on the “filter” icon in the “Frequency” column. ", and specify - filter out keys with the value "less than or equal to 10".

Now the program will show you only those requests whose frequency is less than or equal to the value “10”. You can delete these queries or copy them to another group of key queries for future use. Less than 10 is very little. Writing articles for these requests is a waste of time.

Now we need to select those key queries that will bring us more or less good traffic. And for this we need to find out one more parameter - the level of competitiveness of the request.

Step #4 — Checking the competitiveness of requests

All “keys” in this world are divided into 3 types: high-frequency (HF), mid-frequency (MF), low-frequency (LF). They can also be highly competitive (HC), moderately competitive (SC) and low competitive (LC).

As a rule, HF requests are also VC. That is, if a query is often searched on the Internet, then there are a lot of sites that want to promote it. But this is not always the case; there are happy exceptions.

The art of compiling a semantic core lies precisely in finding queries that have a high frequency and a low level of competition. It is very difficult to manually determine the level of competition.

You can focus on indicators such as the number of main pages in the TOP 10, length and quality of texts. level of trust and tits of sites in the TOP search results upon request. All of this will give you some idea of ​​how tough the competition is for rankings for this particular query.

But I recommend you use Mutagen service. It takes into account all the parameters that I mentioned above, plus a dozen more that neither you nor I have probably even heard of. After analysis, the service gives an exact value - what level of competition this request has.

Here I checked the query “setting up contextual advertising in google adwords”. Mutagen showed us that this key has a competitiveness of "more than 25" - this is the maximum value it shows. And this query has only 11 views per month. So it definitely doesn’t suit us.

We can copy all the keys that we found in Slovoeb and do a mass check in Mutagen. After that, all we have to do is look through the list and take those requests that have a lot of requests and a low level of competition.

Mutagen is a paid service. But you can do 10 checks per day for free. In addition, the cost of testing is very low. In all the time I have been working with him, I have not yet spent even 300 rubles.

By the way, about the level of competition. If you have a young site, then it is better to choose queries with a competition level of 3-5. And if you have been promoting for more than a year, then you can take 10-15.

By the way, regarding the frequency of requests. We now need to take the final step, which will allow you to attract a lot of traffic even for low-frequency queries.

Step #5 — Collecting “tails” for the selected keys

As has been proven and tested many times, your site will receive the bulk of traffic not from the main keywords, but from the so-called “tails”. This is when a person enters strange key queries into the search bar, with a frequency of 1-2 per month, but there are a lot of such queries.

To see the “tail”, just go to Yandex and enter the key query of your choice into the search bar. Here's roughly what you'll see.

Now you just need to write down these additional words in a separate document and use them in your article. Moreover, there is no need to always place them next to the main key. Otherwise, search engines will see “over-optimization” and your articles will fall in search results.

Just use them in different places in your article, and then you will receive additional traffic from them as well. I would also recommend that you try to use as many word forms and synonyms as possible for your main key query.

For example, we have a request - “Setting up contextual advertising”. Here's how to reformulate it:

• Setup = set up, make, create, run, launch, enable, place...
• Contextual advertising = context, direct, teaser, YAN, adwords, kms. direct, adwords...

You never know exactly how people will search for information. Add all these additional words to your semantic core and use them when writing texts.

So, we collect a list of 100 - 150 key queries. If you are creating a semantic core for the first time, it may take you several weeks.

Or maybe break his eyes? Maybe there is an opportunity to delegate the compilation of FL to specialists who will do it better and faster? Yes, there are such specialists, but you don’t always need to use their services.

Is it worth ordering SY from specialists?

By and large, semantic core compilers will only give you steps 1 - 3 from our diagram. Sometimes, for a large additional fee, they will do steps 4-5 - (collecting tails and checking the competitiveness of requests).

After that, they will give you several thousand key queries that you will need to work with further.

And the question here is whether you are going to write the articles yourself, or hire copywriters for this. If you want to focus on quality rather than quantity, then you need to write it yourself. But then it won't be enough for you to just get a list of keys. You will need to choose topics that you understand well enough to write a quality article.

And here the question arises - why then do we actually need specialists in FL? Agree, parsing the base key and collecting exact frequencies (steps #1-3) is not at all difficult. This will literally take you half an hour.

The most difficult thing is to choose HF requests that have low competition. And now, as it turns out, you need HF-NCs, on which you can write a good article. This is exactly what will take you 99% of your time working on the semantic core. And no specialist will do this for you. Well, is it worth spending money on ordering such services?

When are the services of FL specialists useful?

It’s another matter if you initially plan to attract copywriters. Then you don't have to understand the subject of the request. Your copywriters won’t understand it either. They will simply take several articles on this topic and compile “their” text from them.

Such articles will be empty, miserable, almost useless. But there will be many of them. On your own, you can write a maximum of 2-3 quality articles per week. And an army of copywriters will provide you with 2-3 shitty texts a day. At the same time, they will be optimized for requests, which means they will attract some traffic.

In this case, yes, calmly hire FL specialists. Let them also draw up a technical specification for copywriters at the same time. But you understand, this will also cost some money.

Summary

Let's go over the main ideas in the article again to reinforce the information.

• The semantic core is simply a list of key queries for which you will write articles on the site for promotion.
• It is necessary to optimize texts for precise key queries, otherwise even your highest-quality articles will never reach the TOP.
• SY is like a content plan for social networks. It helps you avoid falling into a “creative crisis” and always know exactly what you will write about tomorrow, the day after tomorrow and in a month.
• To compile a semantic core, it is convenient to use the free program Slovoeb, you only need it.
• Here are the five steps of compiling the NL: 1 - Selection of basic keys; 2 - Parsing basic keys; 3 - Collection of exact frequency for queries; 4 — Checking the competitiveness of keys; 5 – Collection of “tails”.
• If you want to write articles yourself, then it is better to create a semantic core yourself, for yourself. Specialists in the preparation of synonyms will not be able to help you here.
• If you want to work on quantity and use copywriters to write articles, then it is quite possible to delegate and compile the semantic core. If only there was enough money for everything.

I hope this instruction was useful to you. Save it to your favorites so as not to lose it, and share it with your friends. Don't forget to download my book. There I show you the fastest way from zero to the first million on the Internet (a summary from personal experience over 10 years =)

See you later!

Yours Dmitry Novoselov

If you know the pain of search engines’ “dislike” for the pages of your online store, read this article. I will talk about the path to increasing the visibility of a site, or more precisely, about its first stage - collecting keywords and compiling a semantic core. About the algorithm for its creation and the tools that are used.

Order the collection of the semantic core from SEO specialists of the Netpeak agency:

Why create a semantic core?

To increase the visibility of site pages. Make sure that Yandex and Google search robots begin to find pages of your site based on user requests. Of course, collecting keywords (compiling semantics) is the first step towards this goal. Next, a conditional “skeleton” is sketched out to distribute keywords across different landing pages. And then articles/meta tags are written and implemented.

By the way, on the Internet you can find many definitions of the semantic core.

1. “The semantic core is an ordered set of search words, their morphological forms and phrases that most accurately characterize the type of activity, product or service offered by the site.” Wikipedia.

To collect competitor semantics in Serpstat, enter one of the key queries, select a region, click “Search” and go to the “Key phrase analysis” category. Then select “SEO Analysis” and click “Phrase Selection”. Export results:

2.3. We use Key Collector/Slovoeb to create a semantic core

If you need to create a semantic core for a large online store, you cannot do without Key Collector. But if you are a beginner, then it is more convenient to use a free tool - Sloboeb (don’t let this name scare you). Download the program, and in the Yandex.Direct settings, specify the login and password for your Yandex.Mail:
Create a new project. In the “Data” tab, select the “Add phrases” function. Select your region and enter the requests you received earlier:
Advice: create a separate project for each new domain, and create a separate group for each category/landing page. For example: Now collect semantics from Yandex.Wordstat. Open the “Data collection” tab - “Batch collection of words from the left column of Yandex.Wordstat”. In the window that opens, select the checkbox “Do not add phrases if they are already in any other groups.” Enter a few of the most popular (high-frequency) phrases among users and click “Start collecting”:

By the way, for large projects in Key Collector you can collect statistics from competitor analysis services SEMrush, SpyWords, Serpstat (ex. Prodvigator) and other additional sources.

What is the semantic core of a site? The semantic core of the site (hereinafter referred to as SY) is a set of keywords and phrases for which the resource progressing in search engines and which indicate that the site belongs to a certain topics.

For successful promotion in search engines, keywords must be correctly grouped and distributed across the pages of the site and contained in a certain form in meta descriptions ( title, description, keywords), as well as in headings H1-H6. At the same time, overspam should not be allowed, so as not to “fly away” to Baden-Baden.

In this article we will try to look at the issue not only from a technical point of view, but also to look at the problem through the eyes of business owners and marketers.

What is the collection of SY?

• Manual— possible for small sites (up to 1000 keywords).
• Automatic— programs do not always correctly determine the context of the request, so problems may arise with the distribution of keywords across pages.
• Semi-automatic— phrases and frequency are collected automatically, phrases are distributed and refined manually.

In our article we will consider a semi-automatic approach to creating a semantic core, as it is the most effective.

In addition, there are two typical cases when compiling a synonym:

• for a site with a ready-made structure;
• for a new site.

The second option is more preferable, since it is possible to create an ideal site structure for search engines.

What does the process of compiling a NL consist of?

Work on the formation of the semantic core is divided into the following stages:

1. Identification of directions in which the site will be promoted.
2. Collecting keywords, analyzing similar queries and search suggestions.
3. Frequency parsing, filtering out “empty” requests.
4. Clustering (grouping) of requests.
5. Distribution of requests across site pages (creation of an ideal site structure).
6. Recommendations for use.

The better you create the core of the site, and quality in this case means the breadth and depth of semantics, the more powerful and reliable the flow of search traffic you can direct to the site and the more customers you will attract.

How to create a semantic core of a website

So, let's look at each point in more detail with various examples.

At the first step, it is important to determine which products and services present on the site will be promoted in the search results of Yandex and Google.

Example No. 1. Let’s say the site has two areas of services: computer repair at home and training to work with Word/Exel at home. In this case, it was decided that training was no longer in demand, so there was no point in promoting it, and therefore collecting semantics on it. Another important point is that you need to collect not only requests containing "computer repair at home", but also "laptop repair, PC repair" and others.

Example No. 2. The company is engaged in low-rise construction. But at the same time he builds only wooden houses. Accordingly, queries and semantics by directions "construction of houses from aerated concrete" or "construction of brick houses" may not be collected.

Collection of semantics

We will look at two main sources of keywords: Yandex and Google. We’ll tell you how to collect semantics for free and briefly review paid services that can speed up and automate this process.

In Yandex, key phrases are collected from the Yandex.Wordstat service and in Google through query statistics in Google AdWords. If available, you can use data from Yandex Webmaster and Yandex Metrics, Google Webmaster and Google Analytics as additional sources of semantics.

Collecting keywords from Yandex.Wordstat

Collecting queries from Wordstat can be considered free. To view the data of this service, you only need a Yandex account. So let's go to wordstat.yandex.ru and enter the keyword. Let's consider an example of collecting semantics for a car rental company website.

What do we see in this screenshot?

1. Left column. Here is the basic query and its various variations with "tail". Opposite each request is a number showing how much this request is in in general has been used by various users.
2. Right column. Requests similar to the main one and indicators of their overall frequency. Here we see that a person who wants to rent a car, in addition to the request "car rental", can use "car rental", "car rental", "car rental" and others. This is very important data that you need to pay attention to so as not to miss a single request.
3. Regionality and history. By choosing one of the possible options, you can check the distribution of requests by region, the number of requests in a particular region or city, as well as the trend of changes over time or with the change of season.
4. Devices, from which the request was made. By switching tabs, you can find out which devices are most often searched from.

Check different versions of key phrases and record the received data in Excel tables or Google spreadsheets. For convenience, install the plugin Yandex Wordstat Helper. After installing it, plus signs will appear next to the search phrases; when you click on them, the words will be copied; you will not need to select and paste the frequency indicator manually.

Collecting keywords from Google AdWords

Unfortunately, Google does not have an open source of search queries with their frequency indicators, so here you need to work around it. And for this we need a working account in Google AdWords.

We register an account in Google AdWords and top up the balance with the minimum possible amount - 300 rubles (on an account that is inactive in terms of budget, approximate data is displayed). After that, go to “Tools” - “Keyword Planner”.

A new page will open, where in the “Search for new keywords by phrase, site or category” tab, enter the keyword.

Scroll down, click “Get options” and see something like this.

1. Top request and average number of requests per month. If the account is not paid, then you will see approximate data, that is, the average number of requests. When there are funds on the account, exact data will be shown, as well as the dynamics of changes in the frequency of the entered keyword.
2. Keywords by relevance. This is the same as similar queries in Yandex Wordstat.
3. Downloading data. This tool is convenient because the data obtained in it can be downloaded.

We looked at working with two main sources of statistics on search queries. Now let's move on to automating this process, because collecting semantics manually takes too much time.

Programs and services for collecting keywords

Key Collector

The program is installed on the computer. The program connects work accounts from which statistics will be collected. Next, a new project and a folder for keywords are created.

Select “Batch collection of words from the left column of Yandex.Wordstat”, enter the queries for which we collect data.

An example is included in the screenshot, in fact, for a more complete syntax, here you additionally need to collect all query options with car brands and classes. For example, “bmw for rent”, “buy a toyota with option to buy”, “rent an SUV” and so on.

WordEb

Free analogue previous program. This can be considered both a plus - you don’t need to pay, and a minus - the program’s functionality is significantly reduced.

To collect keywords, the steps are the same.

Rush-analytics.ru

Online service. Its main advantage is that you don’t need to download or install anything. Register and use it. The service is paid, but when you register, you have 200 coins in your account, which is enough to collect small semantics (up to 5000 requests) and parse frequency.

The downside is that semantics are collected only from Wordstat.

Checking the frequency of keywords and queries

And again we notice a decrease in the number of requests. Let's go ahead and try another word form of the same query.

We note that in the singular, this request is searched by a much smaller number of users, which means the initial request is a higher priority for us.

Such manipulations must be carried out with every word and phrase. Those requests for which the final frequency is equal to zero (using quotation marks and an exclamation mark) are eliminated, because “0” means that no one enters such queries and these queries are only part of others. The point of compiling a semantic core is to select the queries that people use to search. All queries are then placed in an Excel table, grouped by meaning and distributed across the pages of the site.

It’s simply not possible to do this manually, so there are many services on the Internet, paid and free, that allow you to do this automatically. Let's give a few:

• megaindex.com;
• rush-analytics.ru;
• tools.pixelplus.ru;
• key-collector.ru.

Removing non-target requests

After sifting through the keywords, you should remove unnecessary ones. What search queries can be removed from the list?

• requests with the names of competitors' companies (can be left in contextual advertising);
• requests for goods or services that you do not sell;
• requests that indicate a district or region in which you do not work.

Clustering (grouping) of requests for site pages

The essence of this stage is to combine queries that are similar in meaning into clusters, and then determine which pages they will be promoted to. How can you understand which requests to promote to one page and which to another?

1. By request type.

We already know that everything queries in search engines are divided into several types, depending on the purpose of the search:

• commercial (buy, sell, order) - promoted to landing pages, pages of product categories, product cards, pages with services, price lists;
• informational (where, how, why, why) - articles, forum topics, answer to question section;
• navigation (telephone, address, brand name) - page with contacts.

If you are in doubt what type of request it is, enter its search string and analyze the results. For commercial requests there will be more pages offering services, for informational requests there will be more articles.

There is also geo-dependent and geo-independent queries. Most commercial requests are geo-dependent, as people are more likely to trust companies located in their city.

2. Request logic.

• “buy iphone x” and “iphone x price” - need to be promoted to one page, since in both the first and second cases, a search is carried out for the same product and more detailed information about it;
• “buy iphone” and “buy iphone x” - need to be promoted to different pages, since in the first request we are dealing with a general request (suitable for the product category where iPhones are located), and in the second the user is looking for a specific product and this request should promote to the product card;
• “how to choose a good smartphone” - it is more logical to promote this request to a blog article with the appropriate title.

View search results for them. If you check which pages on different sites lead to the queries “construction of houses made of timber” and “construction of houses made of bricks”, then in 99% of cases these are different pages.

4. Automatic grouping using software and manual refinement.

The 1st and 2nd methods are excellent for compiling the semantic core of small sites where a maximum of 2-3 thousand keywords are collected. For a large system (from 10,000 to infinity of requests), the help of machines is needed. Here are several programs and services that allow you to perform clustering:

• KeyAssistant - assistant.contentmonster.ru;
  
• semparser.ru;
• just-magic.org;
• rush-analytics.ru;
• tools.pixelplus.ru;
• key-collector.ru.

After automatic clustering is completed, it is necessary to check the results of the program manually and, if errors are made, correct them.

Example: the program can send the following requests to one cluster: “vacation in Sochi 2018 hotel” and “vacation in Sochi 2018 hotel breeze” - in the first case, the user is looking for various hotel options for accommodation, and in the second, a specific hotel.

To eliminate the occurrence of such inaccuracies, you need to manually check everything and, if errors are found, edit.

What to do next after compiling the semantic core?

Based on the collected semantic core, we then:

1. We create the ideal structure (hierarchy) of the site from the point of view of search engines;
   or in agreement with the customer, we change the structure of the old website;
2. we write technical assignments for copywriters to write text, taking into account the cluster of requests that will be promoted to this page;
   or We are updating old articles and texts on the site.

It looks something like this.

For each generated request cluster, we create a page on the site and determine its place in the site structure. The most popular queries are promoted to the top pages in the resource hierarchy, less popular ones are located below them.

And for each of these pages, we have already collected requests that we will promote on them. Next, we write technical specifications to copywriters to create text for these pages.

Technical specifications for a copywriter

As with the site structure, we will describe this stage in general terms. So, technical specifications for the text:

• number of characters without spaces;
• page title;
• subheadings (if any);
• a list of words (based on our core) that should be in the text;
• uniqueness requirement (always require 100% uniqueness);
• desired text style;
• other requirements and wishes in the text.

Remember, don’t try to promote +100500 requests on one page, limit yourself to 5-10 + tail, otherwise you will get banned for over-optimization and will be out of the game for a long time for places in the TOP.

Conclusion

Compiling the semantic core of a site is painstaking and hard work, which needs to be given especially close attention, because it is on this that the further promotion of the site is based. Follow the simple instructions given in this article and take action.

1. Choose the direction of promotion.
2. Collect all possible queries from Yandex and Google (use special programs and services).
3. Check the frequency of queries and get rid of dummies (those with a frequency of 0).
4. Remove non-target requests - services and goods that you do not sell, requests mentioning competitors.
5. Form query clusters and distribute them across pages.
6. Create an ideal site structure and draw up technical specifications for the content of the site.