SEO compilation of a semantic core. Semantic core! Engine in blog promotion! Manual method of competition analysis

In our article, we explained what a semantic core is and gave general recommendations on how to compose it.

It's time to look at this process in detail, creating a semantic core for your site step by step. Stock up on pencils and paper, and most importantly, time. And join...

We create a semantic core for the site

As an example, let's take the site http://promo.economsklad.ru/.

The company's field of activity: warehouse services in Moscow.

The site was developed by specialists of our website service, and the semantic core of the site was developed in stages in 6 steps:

Step 1. Compile a primary list of keywords.

After conducting a survey of several potential clients, studying three sites close to our topic and using our own brains, we compiled a simple list of keywords that, in our opinion, reflect the content of our site: warehouse complex, warehouse rental, storage services, logistics, storage space rental, warm and cold warehouses.

Task 1: Review competitors' websites, consult with colleagues, brainstorm and write down all the words that, in your opinion, describe YOUR site.

Step 2. Expanding the list.

Let's use the service http://wordstat.yandex.ru/. In the search line, enter each of the words from the primary list one by one:

We copy the refined queries from the left column into an Excel table, look through the associative queries from the right column, select among them those that are relevant to our site, and also enter them into the table.

After analyzing the phrase “Warehouse rental,” we received a list of 474 refined and 2 associative queries.

Having carried out a similar analysis of the remaining words from the primary list, we received a total of 4,698 refined and associative queries that were entered by real users in the past month.

Task 2: Collect a complete list of queries on your site by running each of the words in your primary list through Yandex.Wordstat query statistics.

Step 3. Stripping

First, we remove all phrases with a frequency of impressions below 50: “ how much does it cost to rent a warehouse?" - 45 views, " Warehouse rental 200 m" - 35 impressions, etc.

Secondly, we remove phrases that are not related to our site, for example, “ Warehouse rental in St. Petersburg" or " Warehouse rental in Yekaterinburg", since our warehouse is located in Moscow.

Also, the phrase “ warehouse lease agreement download“- this sample may be present on our website, but there is no point in actively promoting this request, since the person who is looking for a sample contract is unlikely to become a client. Most likely, he has already found a warehouse or is the owner of the warehouse himself.

Once you remove all unnecessary queries, the list will be significantly reduced. In our case with “warehouse rental,” out of 474 refined queries, only 46 relevant to the site remained.

And when we cleaned the full list of refined queries (4,698 phrases), we received the Semantic Core of the site, consisting of 174 key queries.

Task 3: Clean up the previously created list of refined queries, excluding from it low-frequency keywords with less than 50 impressions and phrases that are not related to your site.

Step 4. Revision

Since you can use 3-5 different keywords on each page, we won’t need all 174 queries.

Considering that the site itself is small (maximum 4 pages), we select 20 from the full list, which, in our opinion, most accurately describe the company’s services.

Here they are: warehouse rental in Moscow, warehouse space rental, warehouse and logistics, customs services, safekeeping warehouse, warehouse logistics, logistics services, office and warehouse rental, safekeeping of goods and so on….

These keyword phrases include low-frequency, mid-frequency, and high-frequency queries.

Please note that this list is significantly different from the primary one taken from your head. And it is definitely more accurate and efficient.

Task 4: Reduce the list of remaining words to 50, leaving only those that, in your experience and opinion, are most optimal for your site. Don't forget that the final list should contain queries of varying frequencies.

Conclusion

Your semantic core is ready, now is the time to put it into practice:

review the texts on your site, maybe they should be rewritten.
write several articles on your topic using selected key phrases, post the articles on the site, and after search engines index them, register in article directories. Read “One unusual approach to article promotion.”
pay attention to search advertising. Now that you have a semantic core, the effect of advertising will be much higher.

We've released a new book, Social Media Content Marketing: How to Get Inside Your Followers' Heads and Make Them Fall in Love with Your Brand.

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 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

According to 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.

Company activities

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:

There is always a danger of choosing ineffective queries that provide a minimum number of visitors.
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.
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!

03.08.2018 Reading time: 5 minutes

What is the semantic core?

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

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

Why do you need a semantic core of a website and how to use it?

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

Here is the semantic core - an example of how it was compiled in a company website for a construction company website:

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

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

Types of Keywords

There are several parameters by which key queries are classified.

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

Collecting keyword frequency helps you find out what users are asking for most often. But a high-frequency query is not necessarily a highly competitive query, and composing semantics with high frequency and low competitiveness is one of the main aspects in working with the semantic core.

By type:
- geo-dependent and non-geo-dependent – promotions tied to the region and not;
- informational – from them the user receives some information. Keys of this type are usually used in articles - for example, reviews or useful tips;
- branded – contain the name of the promoted brand;
- transactional – implying an action from the user (buy, download, order) and so on.
Other types are those that are difficult to classify as any type: for example, a “profiled beam” key. By typing such a query into a search engine, the user can mean anything: purchasing timber, properties, comparisons with other materials, etc.
From the experience of our company, we can say that it is very difficult to promote any website based on such requests - as a rule, they are high-frequency and highly competitive, and this is not only difficult to optimize, but also expensive for the client.

How to collect a semantic core for a website?

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

The process of compiling a semantic core

The collected queries are not yet a semantic core; here we still need to separate the wheat from the chaff so that all queries are relevant to the client’s services.

To create a semantic core, queries need to be clustered (divided into blocks according to the logic of service provision). This can be done using programs (for example, KeyAssort or TopSite) - especially if the semantics are voluminous. Or manually evaluate and iterate through the entire list and remove unsuitable queries.

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

A ready-made semantic core is a yellow brick path to the content plan, blog articles, texts for product cards, company news, and so on. This is a table of audience needs that you can satisfy using your website.

Distribute the keys across pages.
Use keywords in meta tags , <description>, <h>(especially in the first level H1 heading).</li> <li>Insert keys into texts for pages. This is one of the white hat optimization methods, but it is important not to overdo it: overspam can result in search engine filters.</li> <li>Save the remaining search queries and those that do not fit into any section under the title “What else to write about.” You can use them for informational articles in the future.</li> <li>And remember: you need to focus on the requests and interests of users, so trying to cram all the keys into one text is pointless</li> </ul><h2>Collecting a semantic core for a website: main mistakes</h2> <ul><li>Refusal of highly competitive keys. Yes, perhaps, to the top upon request “buy profiled timber” you won’t get it (and it won’t stop you from successfully selling your services), but you still need to include it in your texts.</li> <li>Refusal of low frequencies. This is wrong for the same reason as rejecting highly competitive requests.</li> <li>Creating pages for requests and for the sake of requests. "Buy profiled timber" And “order profiled timber”- are essentially the same thing, there is no point in breaking them up into separate pages.</li> <li>Absolute and unconditional trust in the software. You can’t do without SEO programs, but manual analysis and data verification are necessary. And no program can yet assess the industry, the level of competition and distribute keys without errors.</li> <li>Keys are our everything. No, our everything is a convenient, understandable website and useful content. Any text needs keys, but if the text is bad, then the keys will not save you.</li> </ul> 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: <ol><li>We are faced with a task or problem;</li> <li>We formulate in our heads how we can find its solution through a search;</li> <li>We enter a request into Yandex or Google. Besides us, other people do the same;</li> <li>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.</li> </ol><h2>Is it necessary to select key phrases or can you do without it?</h2> 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. <h2>Classification of search queries</h2> Let's look at 3 types of parameters by which keywords are evaluated. By frequency: <ul><li>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.</li> <li>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.</li> <li>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.</li> <li>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.</li> </ul> By competitiveness: <ul><li>Highly competitive (HC);</li> <li>Medium-concrete (SC);</li> <li>Low competitive (NC);</li> </ul>According to need: <ul><li>Navigational. Express the user’s desire to find a specific Internet resource or information on it;</li> <li>Informational. Characterized by the need to obtain information as a response to a request;</li> <li>Transactional. Directly related to the desire to make a purchase;</li> <li>Vague or general. Those for which it is difficult to accurately determine the intent.</li> <li>Geo-dependent and geo-independent. Reflect the need to search for information or complete a transaction in your city or without regional reference.</li> </ul> <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/002-geo-i-ne-geo.png' width="100%" loading=lazy loading=lazy> Depending on the type of site, you can give the following recommendations when selecting key phrases for the semantic core. <ol><li>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.</li> <li>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.</li> </ol><h2>How to correctly compose a large semantic core - step-by-step instructions</h2> 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. <h3>Search for basic phrases</h3> 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. <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/003-wordstat-znakomstvo.png' height="620" width="618" loading=lazy loading=lazy> 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). <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/004-kavichki.png' height="143" width="307" loading=lazy loading=lazy> 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/005-voskl-znak.png' height="114" width="304" loading=lazy loading=lazy> 3) “!... !... !...” - quotation marks and an exclamation mark 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. <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/006-kavichki-voskl-znak.png' height="133" width="296" loading=lazy loading=lazy> 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. <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/007-plus.png' height="304" width="305" loading=lazy loading=lazy> 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/008-minus.png' height="131" width="297" loading=lazy loading=lazy> 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/009-skobki-slesh.png' height="140" width="300" loading=lazy loading=lazy> <blockquote>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. </blockquote> <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/assistant-010.png' width="100%" loading=lazy loading=lazy> Let's say we decide to make our blog using SEO. Let’s choose 7 basic phrases for it: <ul><li>semantic core;</li> <li>optimization;</li> <li>copywriting;</li> <li>promotion;</li> <li>monetization;</li> <li>Direct</li> </ul> <h3>Search for synonyms</h3> 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: <ul><li>Brainstorming;</li> <li>Right column of Yandex Wordstat;</li> <li>Queries typed in Cyrillic;</li> <li>Special terms, abbreviations, slang expressions from the topic;</li> <li>Yandex and Google blocks - search together with the “query name”;</li> <li>Snippets of competitors.</li> </ul>As a result of all actions for the selected topic, we get the following list of phrases: <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/011-spisok-fraz.png' width="100%" loading=lazy loading=lazy> <h3>Basic Query Expansion</h3> 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 Sloboeb, 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/012-kak-snjat-chastotky.png' width="100%" loading=lazy loading=lazy> 2) Let's parse the left column of Yandex Wordstat using the added words to get all the queries from our topic. <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/013-parsing-levoy-kolonki.png' width="100%" loading=lazy loading=lazy> 3) As a result, we got 3374 phrases. Let's take the exact frequency from them, as in point 1. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/014-rezultat-parsinga.png' width="100%" loading=lazy loading=lazy> 4) Let’s check if there are any keys with zero base frequency in the list. <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/015-nastoika-filtra.png' width="100%" loading=lazy loading=lazy> If there is, delete it and move on to the next step. <h3>Negative words</h3> 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. <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/016-minus-slova.png' width="100%" loading=lazy loading=lazy> 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. <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/018-analiz-grupp.png' width="100%" loading=lazy loading=lazy> After we have compiled a list of stop words, we apply them to our project and move on to collecting search tips. <h3>Parsing hints</h3> 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.” <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/018-parsing-podskazok.png' width="100%" loading=lazy loading=lazy> 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/019-rezultat-sbora-podskazok.png' width="100%" loading=lazy loading=lazy> <h3>Determination of base and exact frequencies for all phrases</h3> 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: <ul><li>repetitions of words</li> <li>keys with other symbols;</li> <li>duplicate phrases (via the “Implicit Duplicates Analysis” tool)</li> </ul> <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/020-nastroika-filtrov.png' width="100%" loading=lazy loading=lazy> For the remaining phrases, we will determine the exact and base frequency. A) for phrases up to 7 words: <ul><li>Select through the filter “Phrase consists of no more than 7 words”</li> <li>Open the “Collect from Yandex.Direct” window by clicking on the “D” icon;</li> <li>If necessary, indicate the region;</li> <li>Select the guaranteed impressions mode;</li> <li>Set the collection period to 1 month and check the boxes for the required frequency types;</li> <li>Click “Get data”.</li> </ul> <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/021-sbor-cherez-direct.png' width="100%" loading=lazy loading=lazy> b) for phrases of 8 words or more: <ul><li>Set the filter for the “Phrase” column – “consists of at least 8 words”;</li> <li>If you need to promote in a specific city, indicate the region below;</li> <li>Click on the magnifying glass and select “Collect all types of frequencies.”</li> </ul> <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/022-sbor-chastotok-ot8.png' width="100%" loading=lazy loading=lazy> <h3>Cleaning keywords from garbage</h3> 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/023-chistka-cherez-analiz-grupp.png' width="100%" loading=lazy loading=lazy> 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”. <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/024-spisok-stop-slov.png' width="100%" loading=lazy loading=lazy> 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. <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/025-formula-rasheta-pusishek.png' width="100%" loading=lazy loading=lazy> 4. We calculate KEY 1 and delete those phrases for which this parameter is 100 or more. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/026-proizvodim-otsenku.png' width="100%" loading=lazy loading=lazy> The remaining keys need to be grouped by landing pages. <h3>Clustering</h3> 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. <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/027-interfeis-madgento.png' width="100%" loading=lazy loading=lazy> The essence of clustering keys using this method is to combine into groups those phrases that have Yandex Top 10: <ul><li>shared URLs with each other (Hard)</li> <li>with the most frequent request in the group (Soft).</li> </ul>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: <ul><li>Soft with a threshold of 3-4 and then cleaning by hand;</li> <li>Hard on 3, and then combining clusters according to the meaning.</li> </ul>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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/028-sobiraem-dannie-po-proekty.png' width="100%" loading=lazy loading=lazy> <h3>Competition Check</h3> 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. <blockquote>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. </blockquote> How to check competition on a request: a) manually, by entering the appropriate phrase in the service itself or through mass tasks; <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/029-servis-mutagen.png' width="100%" loading=lazy loading=lazy> b) in batch mode through the Key Collector program. <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/030-rabota-s-mutagenom-v-collectore.png' width="100%" loading=lazy loading=lazy> <h3>Topic selection and grouping</h3> 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; <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/031-import-gruppa-klich.png' width="100%" loading=lazy loading=lazy> 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; <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/032-scpomogat-insrumeti.png' width="100%" loading=lazy loading=lazy> <blockquote>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. </blockquote> 7) After grouping the keys, we get a list of promising topics for articles and semantics for them. <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/033-posle-gruppirovki.png' width="100%" loading=lazy loading=lazy> <h3>Removing requests for another content type</h3> 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 up everything unnecessary; if we cannot accurately determine the intent of the request, we compare the results or use the following tools: <ul><li>Commercialization check from Pixel Tools (free, but with a daily check limit);</li> <li>Just-Magic service, clustering with a checkmark to check the commerciality of the request (paid, cost depends on the tariff)</li> </ul>After this we move on to the last stage. <h3>Phrases optimization</h3> 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: <ul><li>Let's sort the keywords in Excel or Key Collector alphabetically from A to Z;</li> <li>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);</li> <li>We delete keywords with less than 7 impressions per month, which do not carry new meanings and do not contain unique synonyms.</li> </ul>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. <h2>Final checklist</h2> <ol><li>We select the main high-frequency queries that set the topic;</li> <li>We look for synonyms for them using the left and right columns of Wordstat, competitor sites and their snippets;</li> <li>We expand the received queries by parsing the left column of Wordstat;</li> <li>We prepare a list of stop words and apply them to the resulting phrases;</li> <li>Parsing Yandex and Google tips;</li> <li>We remove the base and precise frequencies;</li> <li>Expanding the list of negative keywords. We clean from garbage and requests for pacifiers</li> <li>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.</li> <li>We import the data into Key Collector and determine the competition of 3-4 phrases for each cluster with a unique intent;</li> <li>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).</li> <li>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.</li> <li>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.</li> </ol><h2>What to do with the SEO core after its creation</h2> 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. <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/034-sbor-LSI.png' width="100%" loading=lazy loading=lazy> <h2>An alternative method for selecting key phrases using competitor analysis services</h2> 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: <ul><li>by parsing the main keys;</li> <li>based on competitor analysis.</li> </ul>Each of them can be implemented at a simple or more complex level. Let's look at all the options. <h3>Without using programs</h3> 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: <ul><li>Keys.so service for competitor analysis – 1500 rub. Using promo code “altblog” - 15% discount;</li> <li>Mutagen. Checking the competitiveness of requests - 30 kopecks, collecting basic and exact frequencies - 2 kopecks per check;</li> <li>Bookvarix - free version or business account - 995 rub. (now with a discount of 695 RUR)</li> </ul>Option 1. Selecting a topic by parsing basic phrases: <ol><li>We select the main keys from the topic in a broad sense, using brainstorming and the left and right columns of Yandex Wordstat;</li> <li>Next, we look for synonyms for them, using the methods discussed earlier;</li> <li>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”;</li> <li>We indicate in the filter: “!Exact!frequency” from 50, Number of words from 3;</li> <li>We upload the entire list to Excel;</li> <li>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;</li> <li>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;</li> <li>The name of the future landing page has been decided, all that remains is to select key phrases for it;</li> <li>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);</li> <li>We insert them sequentially into keys.so and upload all the key phrases for them;</li> <li>We combine them in Excel and remove duplicates;</li> <li>The service data alone is not enough, so we need to expand it. Let's use Bukvarix again;</li> <li>The resulting list is sent for clustering to the “Kulakov Clusterer”;</li> <li>We select groups of requests that are suitable for the landing page, focusing on intent;</li> <li>We remove the base and exact frequency through Mutagen in the “Mass Tasks” mode;</li> <li>We upload a list with updated data on the number of impressions in Excel. We remove zeros for both types of frequencies;</li> <li>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;</li> <li>We delete requests for other types of content;</li> <li>We leave phrases that reveal the main intention as fully as possible and in different words;</li> <li>We repeat all the same steps in steps 8-19 for the remaining topics.</li> </ol>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 that you 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. <h3>Using Key Collector or Sloboeb</h3> 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: <ul><li>Kay Collector program – 1800 rubles;</li> <li>all the same services as in the previous method.</li> </ul>"Advanced - 1" <ol><li>We parse the left and right columns of Yandex for the entire list of phrases;</li> <li>We remove the exact and basic frequency through Key Collector;</li> <li>We calculate the indicator key 1;</li> <li>We delete queries from zero and with key 1 > 100;</li> <li>Next, we do everything the same as in paragraphs 18-19 of option 1.</li> </ol>"Advanced - 2" <ol><li>We do steps 1-5, as in option 2;</li> <li>We collect keys for each URL in keys.so;</li> <li>Removing duplicates in Key Collector;</li> <li>We repeat Points 1-4, as in the “Advanced -1” method.</li> </ol>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) <img src='https://i2.wp.com/altblog.ru/wp-content/uploads/Screenshot_classic.png' width="100%" loading=lazy loading=lazy> B) <img src='https://i0.wp.com/altblog.ru/wp-content/uploads/Screenshot_servis.png' width="100%" loading=lazy loading=lazy> IN) <img src='https://i1.wp.com/altblog.ru/wp-content/uploads/Screenshot_prodv.png' width="100%" loading=lazy loading=lazy> 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. <h2>3 common mistakes when creating a semantic core</h2> 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. In the top they stood according to 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. <h2>How much money do you need to start?</h2> 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. <h2>Should you trust the development of the kernel to a “pro” or is it better to figure it out and do it yourself?</h2> 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: <ul><li>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.</li> <li>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.</li> </ul>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! <h2>Why is it so important to fully develop semantics?</h2> 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: <ul><li>meet a person who seems to be okay, but doesn’t catch you, or, having understood yourself, build a harmonious relationship with the one you need;</li> <li>do a job you don’t like or find something you love and make it your profession;</li> <li>renting space for a store in a non-traffic area or waiting until it becomes available is a suitable option;</li> <li>take on the team not the best sales manager, but the one who showed himself best at today’s interview.</li> </ul>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: <ul><li>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 experimentally that the alternative method allows you to collect 51% more;</li> <li>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.</li> </ul>b) for commercial projects: <ul><li>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;</li> <li>Low conversion. Specific requests are better converted into sales. Saving on family kernel, we lose the most conversion keys;</li> <li>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.</li> </ul>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 Semantic core(SY) - a list of queries that bring people to the site. It is advisable to compose it before creating and promoting the site in order to fully determine the topic and direction of development. It helps promote the site and is considered the basis of promotion in search engines. In the article I will tell you in detail how to create a semantic core with your own hands, programs for selecting words and all the basic information about creating a semantic core. Semantic core– a list of keywords that characterize the theme of the site. Therefore, it is important to create not a “hodgepodge” site, but to choose one specific direction - a site about making money, about children, about beauty or health, etc. This list does not consist of 3-10 keywords (as for an article), but of tens or hundreds of key queries (KZ). In addition, you should immediately choose phrases that will help you get into the TOP10. The resulting key phrases must be included in headings, subheadings, in the text and linked. When purchasing links (if you use this promotion method), use these KZ. First, it’s worth understanding the basics and concepts. All requests are divided into high-frequency (HF), mid-frequency (MF) and low-frequency (LF). They are distinguished by how often people type these phrases in searches. There are no strict numerical values to classify one short circuit as LF and another as HF. But you can roughly draw up the following boundaries: <ul><li>Low frequency up to 700 per month (usually consists of 5 or more words);</li> <li>Mid-frequency from 1000 to 2000 per month (3-5 words);</li> <li>High frequency above 2000 per month (1-2 words).</li> </ul>But you shouldn’t rely only on these numbers, because they vary greatly depending on the topic. In addition, when choosing keys, it is worth taking into account competition - how many people are already using this key. You can see approximate competition on the Mutagen website. The requests themselves can be divided into three groups: <ol><li>Primary requests characterize the site in general. For example, for my website: making money at home, making money on the Internet, working on the Internet.</li> <li>Basic queries are included in the semantic core and are worth promoting the site on. For example: making money on the Internet without investments, working on the Internet for mothers.</li> <li>Helper Queries or associative, i.e. similar in meaning to the main ones. For example, who to work on while on maternity leave, part-time work for a mother on maternity leave.</li> </ol><h2>We create a semantic core with our own hands online</h2> wordstat.yandex.ru the most accessible way to create syntax. This site shows how many times a month people enter a particular phrase (key query) into a search. The work is quite simple - in the main field, enter a primary query that characterizes the site as a whole or the desired page/section of the site. For example, “earning money on the Internet.” On the left you will receive a list of main requests (earn money on the Internet without investments) and auxiliary ones (earn money online, additional income). <img src='https://i2.wp.com/xn--80aaacq2clcmx7kf.xn--p1ai/wp-content/uploads/2015/08/Sostavlyaem-semanticheskoe-yadro-onlayn.jpg' align="center" width="100%" loading=lazy loading=lazy> Keep in mind that these numbers show how many times a given request was encountered, but not specifically in this form. So, for example, people were not looking for “earning money without investments”, but “making money on the Internet without investments”, “earning money without investments”, etc. To understand how many times people searched for a specific phrase, you need to put it in quotation marks and put an exclamation point at the beginning: “!earn money without investments.” The value has become several times smaller, but now you know the exact frequency, i.e. How many people type this particular phrase into a search? <img src='https://i2.wp.com/xn--80aaacq2clcmx7kf.xn--p1ai/wp-content/uploads/2015/08/konkretnyiy-zapros.jpg' align="center" width="100%" loading=lazy loading=lazy> The selection of key queries for Google (Google.Adwords) and Rambler (Rambler.Adstat) occurs in a similar way. Other search engines are too small to match queries to them. But you must admit that manually selecting all these requests is very difficult, tedious and time-consuming. Therefore, it is better to use programs. <h2>Compiling a semantic core: programs</h2> <img src='https://i2.wp.com/xn--80aaacq2clcmx7kf.xn--p1ai/wp-content/uploads/2015/08/slovoeb.jpg' align="center" width="100%" loading=lazy loading=lazy> <ol><li>On the top panel, click on the gear and go to settings. There are a lot of things you can customize here, but now go to the last tab of Yandex.Direct;</li> <li>Enter your Yandex username and password (create an additional account, as it may be banned);</li> <li>Click create a new project, name it and save it;</li> <li>Click on “Batch collection of words from the left column of Yandex Wordstat”;</li> <li>Enter the initial request and a couple of main ones, then click Start collecting;</li> <li>Browse through the results and tick all the ones that are not suitable for you, then right-click and Delete selected lines;</li> <li>Click “Collect frequencies from the Yandex.Wordstat service” - Collect frequencies “!”.</li> <li>Focus specifically on the column “Frequency “!” - this is the specific number of requests for this particular phrase (per month). You can filter in ascending order and immediately discard all faults with a frequency below 30 - that’s only 1 request per day.</li> <li>Export data to Excel - click the corresponding icon on the top panel.</li> </ol>– paid program (about 1700 rubles). Professional SEO specialists work with him. If you just want to pick up SYNOPSIS for a small blog and that’s it, you shouldn’t pay that kind of money for the program, it’s better to use Slovoeb. Most often, it is purchased by experienced bloggers with many sites or web writers involved in SEO articles. <img src='https://i1.wp.com/xn--80aaacq2clcmx7kf.xn--p1ai/wp-content/uploads/2015/08/Key-Sollector.png' align="center" width="100%" loading=lazy loading=lazy> Working with the program is very simple: <ol><li>Start a new project;</li> <li>Select region Russia + CIS (or other);</li> <li>Enter your search query and click on the Yandex.Wordstat button (1 button highlighted in green);</li> <li>Browse the options and choose the ones that suit you;</li> <li>Transfer suitable requests to buttons 2 and 3, highlighted in green on the screen;</li> <li>Get the correct keys.</li> </ol>The program itself is quite easy to use + there are instructions on the Internet. If desired, you can buy and use. <h2>We create a semantic core with our own hands</h2> Use the above methods to select suitable keywords. You shouldn’t immediately dial 2000, you can limit yourself to 200 requests, and then develop it. Sit down and think about what keys you can use and make a complete list. You need to type keys for the first page and for several more articles. Weed out words and queries for which you do not plan to advance. I often come across requests like “work from home in Perm” or in other cities, so I immediately throw them out. Evaluate right away - what do people want to get from this request and can you provide it? Remove highly competitive queries for which you will not be able to break into the TOP10. If in doubt, check the Mutagen website for the level of competition. Well, or manually evaluate the results - popular queries are immediately visible. Distribute requests across the site. Mid-frequency queries go to the main page, group low-frequency ones by meaning and use them in articles or sections. Use them as keywords in articles (1 mid-frequency main one, a couple of low-frequency ones in the article and subheadings, and dilute them throughout the text with auxiliary ones). Enter on average 1-2 keys per 2000 characters, no more often. Some people don’t create a strategic language and still achieve success. But it’s better to know how to create a semantic core with your own hands; word selection programs will do this almost automatically (words). And then it will be much easier for you to develop and write articles. <script>document.write("<img style='display:none;' src='//counter.yadro.ru/hit;artfast_after?t44.1;r"+ escape(document.referrer)+((typeof(screen)=="undefined")?"": ";s"+screen.width+"*"+screen.height+"*"+(screen.colorDepth? screen.colorDepth:screen.pixelDepth))+";u"+escape(document.URL)+";h"+escape(document.title.substring(0,150))+ ";"+Math.random()+ "border='0' width='1' height='1' loading=lazy loading=lazy>");</script> </article> <div class="tags"></div> <script type="text/javascript" src="//yandex.st/share/share.js" charset="utf-8"></script> <div class="yashare-auto-init" data-yashareL10n="ru" data-yashareQuickServices="vkontakte,facebook,twitter,odnoklassniki,moimir,gplus" data-yashareTheme="counter" ></div> <div id="venus-269"></div> </div> <div class="seealso"> Read more: <ul> <li> <div> <a href='https://periscopes.ru/en/mozilla-thunderbird-skachat-besplatno-russkaya-versiya-ustanovka-i-nastroika-pochtovogo.html' title='Installing and configuring the Mozilla Thunderbird email client'> <noindex><img width="640" height="426" src="/uploads/c93f8dd10a215b1bf860747e9d5f063b.jpg" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="Installing and configuring the Mozilla Thunderbird email client" sizes="(max-width: 640px) 100vw, 640px" / loading=lazy loading=lazy></noindex> </a> </div> <noindex>2024-08-03 01:08:19</noindex> <div><a href='https://periscopes.ru/en/mozilla-thunderbird-skachat-besplatno-russkaya-versiya-ustanovka-i-nastroika-pochtovogo.html' title='Installing and configuring the Mozilla Thunderbird email client'>Installing and configuring the Mozilla Thunderbird email client</a></div> </li> <li> <div> <a href='https://periscopes.ru/en/vodopad-khon-samyi-shirokii-vodopad-v-mire-chto-privezti-iz-etoi.html' title='What to bring from this country'> <noindex><img width="640" height="426" src="/uploads/e35795e6fdaecbece41e56f636245cbe.jpg" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="What to bring from this country" sizes="(max-width: 640px) 100vw, 640px" / loading=lazy loading=lazy></noindex> </a> </div> <noindex>2024-08-01 01:08:07</noindex> <div><a href='https://periscopes.ru/en/vodopad-khon-samyi-shirokii-vodopad-v-mire-chto-privezti-iz-etoi.html' title='What to bring from this country'>What to bring from this country</a></div> </li> <li> <div> <a href='https://periscopes.ru/en/virtualnaya-mashina-android-dlya-windows-7-luchshie-emulyatory-androida-na-pk.html' title='The best Android emulators on PC'> <noindex><img width="640" height="426" src="/uploads/e7ab8a02c72dfcb5310df3a4d1346afc.jpg" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="The best Android emulators on PC" sizes="(max-width: 640px) 100vw, 640px" / loading=lazy loading=lazy></noindex> </a> </div> <noindex>2024-07-31 01:07:19</noindex> <div><a href='https://periscopes.ru/en/virtualnaya-mashina-android-dlya-windows-7-luchshie-emulyatory-androida-na-pk.html' title='The best Android emulators on PC'>The best Android emulators on PC</a></div> </li> <li> <div> <a href='https://periscopes.ru/en/skolko-stoit-alcatel-one-touch-pop-c5-alcatel-onetouch-pop-c5---tehnicheskie-harakteristiki.html' title='Alcatel OneTouch Pop C5 - 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