The semantic core has been selected, what to do next. What to do with the semantic core. Defining base keys

The more semantic core, the more significant a share of traffic you can attract with its help. However, when selecting several thousand words, certain difficulties arise, in particular, there is a risk of using empty queries that do not bring any benefit to the site in terms of promotion. Obviously, working with such a huge list of “keywords” needs to be optimized.

It’s an empty idea to try to expand a small semantic core if necessary. Typically, the site structure is formed specifically for the initially selected queries, and when adding new ones, serious, but not always appropriate, modification may be required. If the semantic core is initially large, then there will be no need to expand it. Web resources that are promoted through several thousand requests are formed on the basis of the core, pages are subsequently written for it, and the entire structure of the site is worked out.

Large semantic cores mainly use low frequency queries. There is no point in promoting a site whose semantic core consists of 10-20 keywords using low-frequency queries; it would be more advisable to consider the possibility of promoting using mid- and high-frequency queries. However, keep in mind that this will cost much more.

Of course, an extensive semantic core can bring significant profits to the site owner by attracting large and relatively inexpensive traffic. But there are also negative sides.

Firstly, viewing a huge list of queries and directly compiling a semantic core containing more than 1000 “keywords” requires the optimizer to spend a lot of time. Secondly, in order for work with the kernel to be as effective as possible, a specialist will have to delve into the topic and thoroughly study the features specific area business. Thirdly, the work is significantly slowed down by the lack of tools necessary to systematize requests.

High labor intensity

You can select keywords and phrases to compile a semantic core using various Internet services: Google Analytics, Yandex.Metrica or wordstat.yandex.ru. In addition, product descriptions, product catalogs, and analysis of the websites of competing companies can provide the necessary information.

To check the volume of the primary core, you need to enter a word characterizing the topic in the wordstat.yandex.ru line. Let it be a “brick”. The service displays a frequency of over 150,000 impressions per month for this word in Moscow and the Moscow region. However, the percentage of queries containing only one word “brick” is negligible, which means promoting the site using single “keywords” is pointless.

As a rule, the most frequently requested phrases are those consisting of two (facing brick, brick price) or three (do-it-yourself brick, facing brick price) words. Then the frequency decreases. At the same time, queries containing four or more words can also generate very decent traffic.

But great amount queries selected in this way cannot be used for promotion, since most of them do not correspond to the theme of the site. Therefore, unnecessary “garbage” must be removed.

There are several ways to filter out unnecessary requests. Firstly, using standard stop words (forum, download, etc.) or specific words for a specific topic. Secondly, on a geographical basis (buy... in Moscow, order... in Tambov, etc.). Thirdly, by checking the search engine for the correctness of words (identifying spelling errors and typos).

However, the above actions will lead to the fact that expensive mid- and high-frequency queries will remain in the semantic core and words associated with new services and goods will be completely excluded, and they also need to be taken into account when promoting. This is the first difficulty of working with a voluminous semantic core.

Knowledge of the site's subject matter

In order to effectively select the necessary queries, you need to have a good understanding of the site’s subject matter and the terminology of the business to which it is dedicated. Often webmasters do not have sufficient knowledge in all areas.

There are two options for solving the problem. Firstly, you can clarify the information with the customer. Secondly, do the check yourself, spending a significant amount of time on it:

search results for the desired query can be analyzed for the presence of main “keywords” for a specific topic. As a rule, in the snippets located on the first page of the search results there are about 20-30 occurrences of such words;
you can distribute queries into groups and form the necessary structure of the site, having previously analyzed the TOP competitors and structured the list of “keywords” based on the data received.

The need to obtain and analyze a large amount of new information is the second difficulty of working with an extensive semantic core.

Conclusion: the process of manually selecting key queries is very time-consuming. The optimizer can be helped by special tools that can significantly optimize the operations of creating the semantic core of the site.

An example of compiling the semantic core of a website

Good bad

An incorrectly composed semantic core of a site is fraught with promotion for inappropriate search queries or highly competitive keywords, which is not...

Organic search is the most effective source of attracting targeted traffic. To use it, you need to make the site interesting and visible to users search engines Yandex and Google. There is no need to reinvent the wheel here: it is enough to determine what the audience of your project is interested in and how they search for information. This problem is solved when constructing a semantic core.

Semantic core- a set of words and phrases that reflect the theme and structure of the site. Semantics- a branch of linguistics that studies the semantic content of language units. Therefore, the terms “semantic core” and “semantic core” are identical. Remember this remark, it will prevent you from slipping into keyword stuffing or cramming content with keywords.

By creating a semantic core, you answer the global question: what information can be found on the site. Since customer focus is considered one of the main principles of business and marketing, the creation of a semantic core can be looked at from a different perspective. You need to determine which search queries users are looking for information to be published on the site.

Constructing a semantic core solves another problem. It's about about the distribution of search phrases across resource pages. By working with the core, you determine which page most accurately answers a specific search query or group of queries.

There are two approaches to solving this problem.

The first assumes creating a website structure based on the results of analyzing user search queries. In this case, the semantic core determines the framework and architecture of the resource.
The second approach involves preliminary planning of the resource structure before analyzing search queries. In this case, the semantic core is distributed over the finished frame.

Both approaches work one way or another. But it is more logical to first plan the structure of the site, and then determine the queries by which users can find this or that page. In this case, you remain proactive: you choose what you want to tell potential clients. If you adjust the resource structure to the keys, then you remain an object and react to the environment, rather than actively changing it.

Here it is necessary to clearly emphasize the difference between the “SEO” and marketing approaches to building the core. Here is the logic of a typical old-school SEO: to create a website, you need to find keywords and select phrases that will easily get you to the top of the search results. After this, you need to create the site structure and distribute the keys among the pages. Page content needs to be optimized for key phrases.

Here is the logic of a businessman or marketer: you need to decide what information to broadcast to the audience using the site. To do this, you need to know your industry and business well. First you need to plan the approximate structure of the site and a preliminary list of pages. After this, when building a semantic core, you need to find out how the audience searches for information. With the help of content, you need to answer the questions that the audience asks.

What negative consequences does using the “SEO” approach lead to in practice? Due to development according to the principle of “dancing from the stove”, the information value of the resource decreases. Businesses must set trends and choose what to tell customers. Businesses should not limit themselves to reactions to the statistics of search phrases and create pages just for the sake of optimizing the site for some key.

The planned result of constructing a semantic core is a list of key queries distributed across the pages of the site. He contains Page URLs, search queries and indication of their frequency.

How to build a website structure

The site structure is a hierarchical layout of pages. With its help, you solve several problems: plan information policy and logic for presenting information, ensure the usability of the resource, and ensure that the site meets the requirements of search engines.

To build a structure, use a tool convenient for you: table editors, Word or other software. You can also draw the structure on a piece of paper.

When planning your hierarchy, answer two questions:

What information do you want to communicate to users?
Where should this or that information block be published?

Imagine that you are planning the website structure of a small confectionery shop. The resource includes information pages, a publications section, and a showcase or product catalog. Visually the structure might look like this:

For further work with a semantic core, arrange the site structure in the form of a table. In it, indicate the names of the pages and indicate their subordination. Also include columns in the table for page URLs, keywords, and their frequency. The table might look like this:

You'll fill in the URL, Keys, and Frequency columns later. Now move on to searching for keywords.

What you need to know about keywords

To select a semantic core, you must understand what are keywords And what keywords does the audience use?. With this knowledge, you will be able to correctly use one of the keyword research tools.

What keywords does the audience use?

Keys are words or phrases that use potential clients to find the information you need. For example, to make a cake, the user enters search bar request “Napoleon recipe with photo”.

Keywords are classified according to several criteria. By popularity, high-, medium- and low-frequency queries are distinguished. According to various sources, search phrases are grouped as follows:

TO low frequency Requests with a frequency of impressions of up to 100 per month are included. Some specialists include requests with a frequency of up to 1000 impressions in the group.
TO mid-frequency Requests with a frequency of up to 1000 impressions are included. Sometimes experts increase the threshold to 5,000 impressions.
TO high frequency queries include phrases with a frequency of 1000 impressions or more. Some authors consider keys with 5,000 or even 10,000 queries to be high-frequency.

The difference in frequency estimates is due to the different popularity of topics. If you are creating a core for an online store that sells laptops, the phrase “buy a Samsung laptop” with a display frequency of about 6 thousand per month will be mid-frequency. If you are creating a core for the site sports club, the query “aikido section” with a frequency of about 1000 queries will be high-frequency.

What do you need to know about frequency when compiling a semantic core? According to various sources, from two-thirds to four-fifths of all user requests are low-frequency. Therefore, you need to build the broadest possible semantic core. In practice, it should be constantly expanded to include low-frequency phrases.

Does this mean that high- and mid-frequency queries can be ignored? No, you can't do without them. But consider low-frequency keywords as the main resource for attracting target visitors.

According to user needs, keys are combined into the following groups:

Information. The audience uses them to find information. Examples of information requests: “how to properly store baked goods”, “how to separate the yolk from the white”.
Transactional. Users enter them when they plan to take an action. This group includes the keys “buy a bread machine”, “download a recipe book”, “order pizza for delivery”.
Other requests. We are talking about key phrases that are difficult to determine the user’s intent. For example, when a person uses the key "cake", he may be planning to buy culinary product or cook it yourself. In addition, the user may be interested in information about cakes: definition, characteristics, classification, etc.

Some experts highlight separate group navigation requests. With their help, the audience searches for information on specific sites. Here are some examples: “connected laptops”, “city express track delivery”, “register on LinkedIn”. Navigation queries that are not specific to your business can be ignored when compiling a semantic core.

How to use this method of classification when building a semantic core? First, you must consider the needs of your audience when distributing keywords across pages and creating a content plan. Everything is obvious here: publications of information sections must respond to information requests. This should also contain most of the key phrases without any expressed intent. Transactional questions should be answered by pages from the “Store” or “Showcase” sections.

Secondly, remember that many transactional issues are commercial. To attract natural traffic for the request “buy samsung smartphone", you will have to compete with Euroset, Eldorado and other business heavyweights. You can avoid unequal competition using the recommendations given above. Maximize the kernel and reduce the request frequency. For example, the frequency of the request “buy a smartphone Samsung Galaxy s6” is an order of magnitude lower than the frequency of the key “Buy a Samsung Galaxy smartphone.”

What you need to know about the anatomy of search queries

Search phrases consist of several parts: body, specifier And tail. This can be seen with an example.

What about the query “cake”? It cannot be used to determine the user's intent. It is high-frequency, which determines high competition in the search results. Using this request for promotion will bring a large share of untargeted traffic, which negatively affects behavioral metrics. The high-frequency and non-specific nature of the request “cake” is determined by its anatomy: it consists only of the body.

Pay attention to the request “buy a cake”. It consists of a body "cake" and a specifier "buy". The latter determines the user's intent. It is the specifiers that indicate whether the key is transactional or informational. Look at the examples:

Buy a cake.
Cake recipes.
How to serve the cake.

Sometimes specifiers can express exactly the opposite of the user's intentions. A simple example: users are planning to buy or sell a car.

Now look at the request “buy cake with delivery.” It consists of a body, a specifier and a tail. The latter does not change, but details the user's intention or information need. Look at the examples:

Buy cake online.
Buy a cake in Tula with delivery.
Buy homemade cake in Orel.

In each case, the person’s intention to purchase the cake is clear. And the tail of the key phrase details this need.

Knowledge of the anatomy of search phrases allows you to derive a conditional formula for selecting keys for the semantic core. You must define core terms related to your business, product, and user needs. For example, customers of a confectionery company are interested in cakes, pastries, cookies, pastries, cupcakes and other confectionery products.

After that, you need to find the tails and qualifiers that the project's audience uses with the base terms. With tail phrases, you simultaneously increase your reach and reduce core competition.

Long tail or long tail is a term that defines a strategy for promoting a resource for low-frequency key queries. It consists of using the maximum number of keys with a low level of competition. Promotion through low frequencies ensures high efficiency of marketing campaigns. This is due to the following factors:

Promotion using low-frequency keywords requires less effort compared to promotion using high-frequency competitive queries.
Working with long-tail queries is guaranteed to bring results, although marketers cannot always accurately predict which keywords will generate traffic. When working with high-frequency queries, decent marketers cannot guarantee results.
Low-frequency drivers provide higher specificity of results to user needs.

For large sites, the semantic core can contain tens of thousands of queries, and it is almost impossible to select and correctly group them manually.

Services for compiling a semantic core

There are quite a lot of tools for selecting keywords. You can build the core using paid or free services and programs. Choose a specific tool depending on the tasks you face.

Key Collector

You cannot do without this tool if you are engaged in Internet marketing professionally, develop several sites, or form the core of a large site. Here is a list of the main tasks that the program solves:

Selection of keywords. Key Collector collects requests through Yandex's Wordstat.
Parsing search suggestions.
Cutting off inappropriate search phrases using stop words.
Filtering requests by frequency.
Finding implicit duplicate queries.
Determination of seasonal requests.
Collecting statistics from third party services and platforms: Liveinternet.ru, Metrica, Google Analytics, Google AdWords, Direct, Vkontakte and others.
Search relevant to the request pages.
Clustering of search queries.

Key Collector- a multifunctional tool that automates the operations necessary to build a semantic core. The program is paid. You can do everything Key Collector can do with alternative free tools. But for this you will have to use several services and programs.

SlovoEB

This is a free tool from the creators of Key Collector. The program collects keywords through Wordstat, determines the frequency of queries, and parses search suggestions.

To use the program, enter the login and password for your Direct account in the settings. Do not use your main account, as Yandex may block it for automatic requests.

Create a new project. On the Data tab, select the Add Phrases option. Indicate the search phrases that the project's audience is likely to use to find information about products.

In the “Collect keywords and statistics” menu section, select the desired option and run the program. For example, determine the frequency of key phrases.

The tool allows you to select keywords, as well as automatically perform some tasks related to analyzing and grouping queries.

Keyword selection service Yandex Wordstat

To see which phrases the page is shown for in Yandex results, in the Yandex.Webmaster panel you need to open the “Search Queries” tab -> "Latest requests".

We see phrases that were clicked on or the site snippet was shown in the TOP 50 of Yandex over the last 7 days.

To view data only for the page that interests us, we need to use filters.

The possibilities for searching for additional phrases in Yandex.Webmaster are not limited to this.

Go to the “Search Queries” tab -> "Recommended queries."

There may not be many phrases here, but you can find additional phrases, for which the promoted page does not fall into the TOP 50.

Query history

The big disadvantage of visibility analysis in Yandex.Webmaster, of course, is that the data is available only for the last 7 days. To get around this limitation a little, you can try to supplement the list using the “Search Queries” tab -> "Request History".

Here you will need to select " Popular queries».

You will receive a list of the most popular phrases for the last 3 months.

To get phrases from Google Search Console, go to the “Search Traffic” tab -> "Analysis of search queries." Next, select “Impressions”, “CTR”, “Clicks”. This will allow you to see more information, which can be useful when analyzing phrases.

By default, the tab displays data for 28 days, but you can expand the range to 90 days. You can also choose the desired country.

As a result, we get a list of requests similar to that shown in the screenshot.

New version of Search Console

Google already made some tools available new version panels. To view requests for a page, go to the “Status” tab - > "Efficiency".

In the new version, the filters are located differently, but the filtering logic remains the same. I think there is no point in dwelling on this issue. From significant differences It is worth noting the possibility of data analysis for more a long period, and not just 90 days. Significant advantage, when compared with Yandex.Webmaster (only 7 days).

Competitive website analysis services

Competitors' websites are a great source of keyword ideas. If you are interested specific page, you can manually determine the search phrases for which it is optimized. To find the main clues, it is usually enough to read the material or check the contents keywords meta tag in the page code. You can also use semantic text analysis services, for example, Istio or Advego.

If you need to analyze the entire site, use comprehensive competitive analysis services:

You can use other tools to collect keywords. Here are some examples: Google Trends, WordTracker, WordStream, Ubersuggest, Topvisor. But don’t rush to master all the services and programs at once. If you are creating a semantic core for your own small website, use free tool, for example, the Yandex keyword selection service or Google planner.

How to choose keywords for the semantic core

The process of selecting key phrases is combined into several stages:

First, you will identify the basic keywords with which the audience searches for your product or business.
The second stage is devoted to expanding the semantic core.
In the third step, you will remove inappropriate search phrases.

Defining base keys

List common search phrases related to your business and products in a spreadsheet or write down on paper. Gather your colleagues and brainstorm. Record all proposed ideas without discussion.

Your list will look something like this:

Most of the keys you've written down are high in frequency and low in specificity. To get mid- and low-frequency search phrases with high specificity, you need to expand the core as much as possible.

Expanding the semantic core

You will solve this problem using keyword research tools such as Wordstat. If your business has a regional link, select the appropriate region in the settings.

Using the key phrase selection service, you need to analyze all the keys recorded at the previous stage.

Copy the phrases from the left column of Wordstat and paste them into the table. Pay attention to the right column of Wordstat. In it, Yandex offers phrases that people used along with the main request. Depending on the content, you can immediately select the appropriate keywords from the right column or copy the entire list. In the second case, unsuitable requests will be eliminated at the next stage.

And the result of this stage of work will be a list of search phrases for each basic key that you obtained using brainstorming. The lists may contain hundreds or thousands of queries.

Removing inappropriate search phrases

This is the most labor-intensive stage of working with the kernel. You need to manually remove inappropriate search phrases from the kernel.

Do not use frequency, competition or other purely “SEO” metrics as a criterion for evaluating keys. Do you know why old-school SEOs consider certain search phrases to be trash? For example, take the key “diet cake”. The Wordstat service predicts 3 impressions per month for it in the Cherepovets region.

To promote pages for specific keywords, old-school SEOs bought or rented links. By the way, some experts still use this approach. It is clear that search phrases with low frequency in most cases do not recoup the funds spent on buying links.

Now look at the phrase “diet cakes” through the eyes of an ordinary marketer. Some representatives of the confectionery company's target audience are really interested in such products. Therefore, the key can and should be included in the semantic core. If the confectionery prepares the corresponding products, the phrase will be useful in the product descriptions section. If for some reason the company does not work with diet cakes, the key can be used as a content idea for the information section.

What phrases can be safely excluded from the list? Here are examples:

Keys mentioning competing brands.
Keys mentioning goods or services that you do not sell and do not plan to sell.
Keys that include the words “inexpensive”, “cheap”, “at a discount”. If you are not dumping, cut off cheap lovers so as not to spoil behavioral metrics.
Duplicate keys. For example, of the three keys “custom cakes for a birthday”, “custom cakes for a birthday” and “custom cakes for a birthday”, it is enough to leave the first one.
Keys that mention inappropriate regions or addresses. For example, if you serve residents of the Northern district of Cherepovets, the key “custom cakes industrial district” does not suit you.
Phrases entered with errors or typos. Search engines understand that the user is looking for croissants, even if he enters the key “croissants” into the search bar.

After removing inappropriate phrases, you received a list of queries for the base key “custom cakes”. The same lists need to be compiled for other basic keys obtained during the brainstorming stage. After that, move on to grouping key phrases.

How to group keywords and build a relevance map

Search phrases with which users find or will find your site are combined into semantic clusters, this process is called search query clustering. These are closely related groups of queries. For example, the semantic cluster “Cake” includes all key phrases associated with this word: cake recipes, order a cake, photos of cakes, wedding cake, etc.

Semantic cluster- this is a group of queries united in meaning. It is a multi-level structure. Within the first-order cluster “Cake” there are second-order clusters “Cake Recipes”, “Ordering Cakes”, “Photos of Cakes”. Within the second-order cluster “Cake Recipes”, it is theoretically possible to distinguish a third order of clustering: “Recipes for cakes with mastic”, “Recipes for sponge cakes”, “Recipes for shortbread cakes”. The number of levels in a cluster depends on the breadth of the topic. In practice, in most topics, it is enough to identify business-specific second-order clusters within first-order clusters.

Theoretically, a semantic cluster can have many levels.
In practice, you will have to work with clusters of the first and second levels

You identified most of the first level clusters during brainstorming when you wrote down basic key phrases. To do this, it is enough to understand your own business, as well as look at the site diagram that you drew up before starting work on the semantic core.

It is very important to correctly perform clustering at the second level. Here, search phrases are modified using qualifiers to indicate user intent. A simple example is the “cake recipes” and “custom cakes” clusters. The first search phrases are used by people who need information. The keys of the second cluster are used by clients who want to buy a cake.

You defined the search phrases for the “custom cakes” cluster with using Wordstat and manual screening. They must be distributed between the pages of the “Cakes” section.

For example, in the cluster there are search queries “custom football cakes” and “custom football cakes”.

If the company’s assortment includes a corresponding product, you need to create a corresponding page in the “Mastic Cakes” section. Add it to the site structure: indicate the name, URL and search phrases with frequency.

Use Keyword Research or similar tools to see what other search terms potential customers are using to find football-themed cakes. Add relevant pages to your list of keywords.

In the list of cluster search phrases, mark the distributed keys in a way convenient for you. Distribute the remaining search phrases.

If necessary, change the site structure: create new sections and categories. For example, the page “custom cakes for PAW Patrol” should be included in the “Children’s Cakes” section. At the same time, it can be included in the “Mastic Cakes” section.

Please note two things. First, the cluster may not have suitable phrases for the page you are planning to create. This can happen by various reasons. For example, these include imperfection of tools for collecting search phrases or their incorrect use, as well as low popularity of the product.

The absence of a suitable key in the cluster is not a reason to refuse to create a page and sell a product. For example, imagine that a confectionery company sells children's cakes featuring characters from the cartoon Peppa Pig. If the list does not include the relevant keywords, clarify the needs of your audience using Wordstat or another service. In most cases, suitable requests will be found.

Secondly, even after removing unnecessary keys, search phrases may remain in the cluster that are not suitable for the created and planned pages. They can be ignored or used in another cluster. For example, if for some reason a confectionery shop fundamentally does not sell Napoleon cake, the corresponding key phrases can be used in the “Recipes” section.

Clustering search queries

Search queries can be grouped manually, using Excel programs or Google Sheets, or automated, using special applications and services.

Clustering allows you to understand how requests can be distributed across website pages for the fastest and fastest effective promotion.

Automatic clustering or grouping of search queries of the semantic core is carried out based on the analysis of sites included in the TOP 10 search engine results Google systems and Yandex.

How automatic request grouping works: for each request, the results among the TOP 10 sites are viewed. If there are matches among at least 4-6 of them, then requests can be grouped to be placed on one page.

Automatic grouping is the fastest and effective method combining keywords to form a site structure that is almost ready for use.

If it is not correct, from the point of view of search engine statistics, to form a site structure and distribute queries among its pages, it will, alas, be impossible to successfully promote pages to the TOP!

Applications and services for automatic grouping of search queries

Among the services that automate the grouping of keywords, it is worth highlighting:

Key Collector.
Rush Analytics.
TopVisor.

After all the keys have been distributed, you will receive a list of existing and planned site pages indicating the URL, search phrases and frequency. What to do with them next?

What to do with the semantic core

A table with a semantic core should become a road map and the main source of ideas when forming:

Look: you have a list with pre-titled pages and search phrases. They determine the needs of the audience. When drawing up a content plan, you just need to clarify the name of the page or publication. Include your main search query. This is not always the most popular key. In addition to popularity, the query in the title should best reflect the need of the page's audience.

Use the remaining search phrases as an answer to the question “what to write about.” Remember, you don’t have to enter all the search phrases into the information material or in the product description. Content should cover the topic and answer user questions. Please note again: you need to focus on information needs, and not on search phrases and their inclusion in the text.

Semantic core for online stores

The specificity of the preparation and clustering of semantics lies in the presence of four very important, for subsequent, groups of pages:

Home page.
Pages of sections and subsections of the catalog.
Product card pages.
Blog article pages.

We have already talked above about different types search queries: informational, transactional, commercial, navigational. For pages of sections and products of an online store, transactional ones are primarily of interest, i.e. queries using which search engine users want to see sites where they can make a purchase.

You need to start forming a core with a list of products that you already sell or plan to sell.

For online stores:

as " body»requests will be made product names;
as " specifiers" phrases: " buy», « price», « sale», « order», « photo», « description», «

Many web publications and publications talk about the importance of the semantic core.

Similar texts are available on our website “What to Do.” At the same time, only the general theoretical part of the issue is often mentioned, while the practice remains unclear.

All experienced webmasters insist that it is necessary to create a basis for promotion, but only a few clearly explain how to use it in practice. To remove the veil of secrecy from this issue, we decided to highlight the practical side of using the semantic core.

Why do you need a semantic core?

This is, first of all, the basis and plan for further filling and promoting the site. The semantic basis, divided according to the structure of the web resource, are pointers on the way to the systematic and targeted development of the site.

If you have such a foundation, you don't have to think about the topic of each next article, you just need to follow the bullet points. With the core, website promotion moves much faster. And promotion gains clarity and transparency.

How to use the semantic core in practice

To begin with, it is worth understanding how the semantic basis is generally compiled. Essentially, this is a list of key phrases for your future project, supplemented by the frequency of each request.

Collecting such information is not difficult using the Yandex Wordstat service:

http://wordstat.yandex.ru/

or any other special service or program. The procedure will be as follows...

How to create a semantic core in practice

1. Collect in single file(Exel, Notepad, Word) all requests according to your key topic, taken from statistical data. This should also include phrases “out of the blue”, that is, logically acceptable phrases, morphological variants (as you yourself would search for your topic) and even variants with typos!

2. List semantic queries sorted by frequency. From requests from maximum frequency– for queries with a minimum of popularity.

3. All junk queries that do not correspond to the theme or focus of your site are removed and cleared from the semantic basis. For example, if you tell people about washing machines for free, but don't sell them, you don't need to use words like:

"buy"
"wholesale"
"delivery"
"order"
"cheap"
“video” (if there are no videos on the site)…

Meaning: do not mislead users! Otherwise, your site will receive a huge number of failures, which will affect its rankings. And this is important!

4. When the main list is cleared of unnecessary phrases and queries and includes a sufficient number of items, you can use the semantic core in practice.

IMPORTANT: a semantic list can never be considered completely ready and complete. In any topic, you will have to update and supplement the core with new phrases and queries, periodically monitoring innovations and changes.

IMPORTANT: the number of articles on the future site will depend on the number of items in the list. Consequently, this will also affect the volumes required content, on the working hours of the author of the articles, on the duration of filling the resource.

Imposing a semantic core on the site structure

In order for the entire list received to make sense, you need to distribute requests (depending on frequency) across the site structure. It is difficult to give specific numbers here, since the scale and frequency difference can be quite significant for different projects.

If, for example, you take a query with a millionth frequency as a basis, even a phrase with 10,000 queries will seem mediocre.

On the other hand, when your main request is 10,000 frequency, the average frequency will be about 5,000 requests per month. Those. a certain relativity is taken into account:

“HF – CP – LF” or “Maximum – Middle – Minimum”

But in any case (even visually) you need to divide the entire core into 3 categories:

high-frequency queries (HF - short phrases with maximum frequency);
low-frequency queries (LF - rarely requested phrases and word combinations with low frequency);
mid-frequency queries (MF) - all average queries that are in the middle of your list.

The next step is to support 1 or more (maximum 3) requests for the main page. These phrases should be as high frequency. High frequencies are placed on the main page!

Next, from the general logic of the semantic core, it is worth highlighting several main key phrases from which sections (categories) of the site will be created. Here you could also use high-frequency queries with a lower frequency than the main one, or better - mid-frequency queries.

Low-frequency remaining phrases are sorted into categories (under created sections and categories) and turned into topics for future publications on the site. But it's easier to understand with an example.

EXAMPLE

A clear example of using the semantic core in practice:

1. Main page (HF) – high frequency request- "website promotion".

2. Section pages (SP) – “custom website promotion”, “ independent promotion", "site promotion with articles", "site promotion with links". Or simply (if adapted for the menu):

Section No. 1 - “to order”
Section No. 2 – “on your own”
Section No. 3 – “ article promotion»
Section No. 4 – “link promotion”

All this is very similar to the data structure on your computer: logical drive (main) - folders (partitions) - files (articles).

3. Pages of articles and publications (NP) – “ fast promotion website for free”, “cheap promotion to order”, “how to promote a site with articles”, “promotion of a project on the Internet to order”, “inexpensive website promotion with links”, etc.

In this list you will have the largest number of diverse phrases and phrases that you will need to create further publications site.

How to use a ready-made semantic core in practice

Using a query list is internal optimization content. The secret is to optimize (adjust) each page of a web resource to the corresponding core item. That is, in fact, you take a key phrase and write the most relevant article and page for it. A special service will help you assess the relevance, available at the following link:

To have at least some guidelines in your SEO work, it is better to first check the relevance of sites from the TOP search results for specific queries.

For example, if you are writing text on the low-frequency phrase “inexpensive website promotion with links,” then first simply enter it in the search and evaluate the TOP 5 sites in the search results using the relevance assessment service.

If the service showed that sites from the TOP 5 for the query “inexpensive website promotion with links” have a relevance of 18% to 30%, then you need to focus on the same percentages. Better yet, create unique text with keywords and relevance of approximately 35-50%. Slightly ahead of competitors at this stage, you will lay a good foundation for further advancement.

IMPORTANT: the use of the semantic core in practice implies that one phrase corresponds to one unique page resource. The maximum here is 2 requests per article.

The more fully the semantic core is revealed, the more informative your project will be. But if you are not ready for long work and thousands of new articles, there is no need to take on broad thematic niches. Even a narrow specialized area, developed 100%, will bring more traffic than an unfinished large website.

For example, you could take as the basis of the site not the high-frequency key “site promotion” (where there is enormous competition), but a phrase with a lower frequency and narrower specialization - “article site promotion” or “link promotion”, but reveal this topic to the maximum in all articles on the virtual platform! The effect will be higher.

Useful information for the future

Further use of your semantic core in practice will consist only of:

adjust and update the list;
write optimized texts with high relevance and uniqueness;
publish articles on the website (1 request – 1 article);
increase the usefulness of the material (edit ready-made texts);
improve the quality of articles and the site as a whole, monitor competitors;
mark in the kernel list those queries that have already been used;
complement optimization with other internal and external factors(links, usability, design, usefulness, videos, online tools help).

Note: The above is a very simplified version of the events. In fact, based on the kernel, sublevels, deep nesting structures, and branches into forums, blogs, and chats can be created. But the principle will always be the same.

PRESENT: useful tool to collect the kernel in the Mozilla FireFox browser -

The semantic core is a scary name that SEOs came up with to denote a rather simple thing. We just need to pick key queries, on 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 the usual excel file, which lists the 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 very 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 site 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, and preferably 2-3 times a week, in order to gain more traffic and quickly.

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, “smm,” into the search field, and Yandex immediately gave me a dozen hints about what else might be of interest 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 SY, you should be able to Text Document, which will contain 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 free analogue- 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 numbers.

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 issues exact value— what level of competition does this request have?

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 make mass verification in Mutagen. After this, all we have to do is look through the list and take those requests that have many requests and low level 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 out these additional words into 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 your article, and then you will receive additional traffic also on them. 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 by and large specialists in compiling a semantic core will only give you steps 1 - 3 from our scheme. 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-NK, which you can write to 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 not to fall into " 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 free program Word fucker, you only need her.
Here are the five steps of compiling the NL: 1 - Selection of basic keys; 2 - Parsing basic keys; 3 - Collection of exact frequency for requests; 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 (extract from personal experience in 10 years =)

See you later!

Yours Dmitry Novoselov

Relevance map is a plan for website content optimization, compiled on the basis of queries from the semantic core. Simpler and clearer? This is a table where for each page the queries for which it will be optimized are entered.

This document will help in the work of everyone involved in promoting your website: SEO specialist, copywriter, targetologist (advertising), marketer. Or just for you, if you are a multi-armed SEO god and do everything on your own.

2. How to create a relevance map?

Rules for drawing up a relevance map:

1. Requests. In the relevance map, for each page you need to select 3-5 queries from the list of keywords for which we will optimize the page. For the main one - HF and MF requests, for internal ones - emphasis on MF and LF. If you have us, you can skip this point, since we select the keys page by page. If you did it yourself, we check which pages are already relevant to the keywords from the point of view of search engines. I'll tell you 2 ways to do this:

– Manual check. Enter each query into the search bar, and in the advanced settings specify the site address and region. The first answer in the search results is the page that, in the opinion of the search robot, answers the query better than others on your site. If you agree with this, then we enter the page and keys in one line. If not, make a note that the page needs to be corrected.

– Automatic check. Find relevant pages using special services eg Key Collector, Majento.

2. Tags. Well-developed Title, Description and H1. We add the keywords that we chose for the page to the tags. We don’t forget to use tags and the rules for compiling them.

3. Pictures. If there are drawings on the pages, we also work on alt attribute for the img tag.

As a result, if you do everything correctly, you will get a table like this:

This is the relevance map. Next, systematic work on optimization: place tags on the site, adjust texts taking into account the selected keys, work on the link profile. And here he is TOP. Just one big request: in pursuit of the top, do not forget about the users. The site should be convenient and understandable. We'll talk about this more in future letters.

3. Will there be materials to help?

Time to read the article is 5 minutes, including a coffee break. But drawing up a relevance map, I believe, will take you 1-2 days. Yep, with a break for lunch.