/ Date: 2014-07-30 at 22:35

Hello everyone friends. In this article I will tell you what LF, MF and HF are, how these letters are generally deciphered in the SEO environment and how frequency is generally determined.

The topic of website promotion touches on many important points that every novice webmaster should be familiar with. One of these points is keywords, which are an important component of every website.

Keywords, also called keywords by some webmasters, are words and phrases that users typically type into a search engine to find information on a given topic.

I have mentioned them many times in previous articles, introducing you to the basics of SEO, so it’s time to tell you about keywords ah in more detail, teaching how to work with them.

Why is it important to optimize your articles for KS?

I also talked about how the site should be optimized for key queries. Each site has a lot of pages, this includes the main page, sections of the site, as well as articles posted in these sections, and all of them must be optimized for a certain key.

Let's stop at this point and try to understand why it is so important to optimize all content on the site for certain keywords. I'll try to explain this with a specific example.

Let's say you have a site on a construction topic, on which there is an article “How to build a house from bricks”, optimized for this key. In this article you describe in detail the process of building a house.

Will the user receive an answer to their question? Yes. And now the situation is different. The same article, optimized for the same key, but talking about some company engaged in the construction of brick houses.

Will the user receive an answer to his question in this case? No, and most likely he will immediately close your site, and the reason for this will be an incorrectly selected keyword. And then search engines, noticing that visitors have no interest in this article, will conclude that your article has no place in the TOP, lowering it in the search results.

It is for this reason that you need to wisely select keywords for each article on the site. Therefore, try to write articles for certain key queries and reveal the whole essence of this issue.

Also, you should not optimize an article for several keywords at once, as this will not achieve anything. Select 1-2 key queries, but related to the content of your article, and that will be enough.

What types of key queries exist (LF, MF, HF), how they are deciphered and how they differ from each other.

I also already said that keywords can be classified into low frequency, mid-frequency And high frequency.

High frequency queries (HF) include the most popular queries, which are searched by a large number of users. Let me give you an example. The key phrase “do-it-yourself construction” is a high-frequency search. It does not contain any specifics and is for informational purposes only on this topic.

The keyword “building a house with your own hands” can be classified as a mid-frequency (MF) query. This query is more clarifying, but far fewer people are searching for this query.

If users want to get more specific information, they enter low-frequency questions (LF), for example, the key phrase “building a brick house with your own hands.”

The differences between each of these types of keys are obvious: the lower the frequency of the request, the less competition, and the shorter the key, the higher its frequency.

As for articles, as a rule they are written for low-frequency queries, since the main goal of each article is to give the user specific information on an issue of interest to him.

Mid-frequency keys can be used to optimize sections of a site, since they clarify in more detail what issue the section is devoted to, but still do not provide specifics. Well, high-frequency keys, in turn, can be used for optimization home page by telling search engines and visitors the topic of your site.

And to make it more clear to you, I drew the following diagram for clarity:

How to determine frequency using Wordstat yandex and Allpositions

The next thing I would like to tell you about is determining the frequency of keywords. This is necessary in order to select the most frequent queries for your site. I will tell you how to determine the frequency of keywords using the example of such services as Wordstat yandex and Allpositions.

Let's start with wordstat. I enter the keyword I'm interested in and see the following:

Many beginners believe that the number 38565 is the frequency given key. But this is not so, and Wordstat just uploaded to us general statistics for all keywords in which it appears this phrase. To find out the exact frequency of our request, you need to put it in quotes:

The number 112 is the real frequency of this key. At first glance, it would seem that a high-frequency request in reality turns out to be completely different. This is how you can filter out keywords when composing semantic core.

It will also be possible to sample by region if you are promoting a site in a specific area or city.

Now let's move on to the service Allpositions. In fact, this service is designed to check the position of your site in the PS, but you can also find out the frequency there. First you will need to register.

I will not dwell on this step, since registration is quite simple. After registering and logging in, you will be asked to create a project:

Enter your site's address in the URL field and click add. After this you will need to create a report:

This will not cause you any difficulties. There you will need to once again enter the site address, select the search engines and regions under which the site will be promoted and set the time at which the positions will be checked. After the report is compiled, you need to add the keywords by which the site is promoted:

Enter the keys you collected and add them. After this, you will see this sign in front of you:

In fact, there is another column in which keywords are written, but since I used them from my site, I will not advertise them. Wait a while for the report to update, after which statistics for each keyword will appear in front of you:

So the frequency column displays the frequency of each key.

How to correctly use query languages ​​in Wordstat yandex

And the last thing I would like to talk about is the query languages ​​in Wordstat yandex. I already mentioned one of the query languages ​​above when talking about frequency checking key query in wordstat, so that's where I'll start.

Quotes. They are needed to find out how many times a specific query was entered. Quotes help exclude other queries that contain your keyword. If you need to exclude a word and collect keywords that do not contain it, then this can be done using a minus sign. Note:

These are queries without a minus sign, but here’s how the statistics will change if you add it:

Since there is a minus request, then there is probably a plus request as well? Yes, indeed, there is such a query, and it is intended to ensure that queries with prepositions and conjunctions are taken into account in statistics:

As you can see, in the second case, only those requests that contain the phrase “for home” are displayed.

Another request is Exclamation point"!" It is necessary in order to select all requests that contain the key you need:

And the last of the operators in the query language is for grouping keywords. It is denoted by brackets “()” and a vertical bar “|” inside brackets between words:

That is, we made a request so that wordstat would give us keywords for the queries “home repair” and “house construction”.

So we have looked at everything that is important to know for working with keywords. I hope you find this article useful and that it will become much easier for you to select keywords for your site. Bye everyone and see you soon.

Sincerely Shkarbunenko Sergey

07.09.2018 Reading time: 5 minutes

Search queries and their frequency. How to determine the frequency of a request?

The search query is the query that the user enters into the search:

The frequency is largely explained by the topic and area of ​​business, as well as region, seasonality and search engine.

You can check the frequency using Yandex.Wordstat.

Types of search queries by their frequency

• How to choose low frequency queries? Take everything that Wordstat shows, up to 1 impression per month. The more low frequency at the start of work, the more traffic there will be.
• How to promote low-frequency queries? These are the simplest and most undemanding requests; they do not need to be supported by links - you just need to create relevant content: write articles, news, product cards that will answer the user’s question as meaningfully and accurately as possible.
• Traffic for such queries will begin to grow immediately, but perhaps slowly: the queries are low-competitive, the results may not be impressive at first, but the more such queries are implemented on the site, the higher its traffic will ultimately be.

Highly competitive low-frequency requests do occur, but rarely - mainly in narrow commercial niches with high competition. That is, there are very few people who enter such queries, bringing your site to the top will not be easy, but if a user comes to your site, then most likely he will become a buyer.

Mid-frequency queries, their concept and features

How many mid-frequency queries are there? Midrange is a little more popular than bass. Mid-frequency and low-frequency queries are the basis for website promotion, because there are the most of them. Using both groups of requests, you can achieve optimal traffic with not the largest investments.

It is more difficult to promote a site on a commercial medium than on an informational one, and this must be taken into account: commercial queries are selling ones, and the competition for them is higher. For mid-frequency queries, the number of offers corresponds to the level of demand: there are indeed quite a few sites that are promoted primarily by mid-frequency queries. For example, on the Internet more than one company offers "buy plastic windows inexpensive", so be prepared that working on the site in this case can take quite a lot of time.

High-frequency queries, their concept and features

What queries are considered high-frequency? Those that users enter in search most often - more than 1000 times a month, for example:

High-frequency queries are as wide a variety and total number of options as you like: there are not only informational and commercial queries, but also branded queries, for which there is a very high high traffic. But such queries are extremely highly competitive, so the highest frequency queries are the most expensive in all respects.

Another drawback high frequency queries in Yandex and Google - not the best high conversion: it is not clear what the user wants when entering search bar request "laptop screen". He needs care information, addresses of workshops where it can be repaired or replaced, or some specifications? And the contents of the page may not be what he is looking for at all.

• How to determine whether a high-frequency query is high or not? Use the same Yandex.Wordstat.
• How to promote high-frequency queries? Long and expensive. To get to the top search results, you will have to work long and hard on the site, investing impressively, including financially. It must be taken into account that especially the highest-frequency queries (Yandex or Google - it doesn’t matter) mean a huge flow of audience, including non-targeted ones, and extremely high competition.

What queries are best to choose for promotion?

What requests - low-frequency, medium- or high-frequency - should be collected for search engine optimization your Internet platform? The ideal queries for promotion are low-frequency and highly competitive, but this is rarely a dream come true for the optimizer and the client. Therefore, which queries are best to choose for your site depends on the site itself.

If SEO has not been carried out before, the site is not optimized and you are just at the beginning of the journey, then you need to first take on the low frequencies and work on them, gradually connecting the midrange and high frequencies.

If the site is maximally optimized for midrange and low frequency, take on high frequency.

You can also select queries for promotion based on the optimization vector:

• if the site is developing for demand in a direction or area as a whole, use HF;
• if you need to attract target visitors who are looking for one or more areas of your company’s work - use more MF;
• if you need high conversion and sales growth, focus on low frequencies.

Read carefully this article, schemes and cases for promoting HF (high-frequency) queries at minimal cost you will not find even in paid courses!

All those who read my article know very well that promoting high-frequency queries is very difficult, and sometimes simply impossible, due to simply huge competition and expected high costs.

In reality, this is not so, SEO specialists have long ago solved strange riddles using the search engine algorithm, and almost each of them can compose a text that will quickly appear in the TOP!

I offer you a scheme for promoting HF requests at virtually no cost.

Background:

A little over a year ago I was promoting one resource furniture theme. In the work of an SEO, an important role is played by the analysis of competitors, who very often suggest how and what can be promoted.

I got my hands on one blog on that topic, but with 25,000 visitors per day, and this, I tell you, is a huge figure for not the most popular content on the network, among other things this blog had just under 1000 pages in the index.

The analysis showed that 80% of blog traffic comes from search engines, while query analysis showed that a fairly large number of high-frequency queries and great amount The midrange is in the TOP.

My suggestions are that this effect achieved with the help of link promotion, quickly dissipated. The number of links over the entire life of the blog at that time was about 150, and all the links were of a natural nature, totaling 60 points.

The number of comments on the blog (reactions) was incredibly small: for 1000 articles there are about 300 comments (check yours on this moment, you will see this at least twice as much).

But there was one feature in this blog - it was an unusual and unique (at that time for me) formation of text in the articles, which lifted the veil of secrecy.

The text was structured in such a way that it consisted of several thematic articles in one, and key phrases were used in decreasing order. But each keyword was used within its own block.

Schematically it can be represented like this:

IN in this case:

1. title - unique title with HF request,

2. — unique (different from title) with HF request,

3. - a unique MF request complementing the HF,

4. — LF requests complementing the midrange (about 6 were used

   headers),

5. description for images - text from keywords located in close proximity to the picture (also a key phrase).

Thus, each keyword satisfied the search query in its conditional block. That is, HF, MF and LF queries were relevant.

Some notes:

• All headings were built according to the title principle of 40-70 characters,
• key phrases were thematic to HF,
• the picture itself and the description of the picture were in one shingle:

  description

An example of such a scheme is my article about, in which, in addition to the HF query, a complementary LF query “how to compose relevant text” is used, which in turn also satisfies search queries.

In output it looks like this:

Instead of the title of the article, use

title. This scheme allows you to make 6-8 queries in an article relevant, each of which will bring users to you.

There is only one question left to answer: how can LF queries help promote HF queries?

Simple math! Let's say that our article uses:

• 1 HF request - 30 people per day,
• 1 MF request - 10 people per day,
• 6 low-frequency requests for 2 people per day.

It's no secret that promoting low frequency queries in a number of topics is a simple task. In fact, to get TOP positions you don’t need to do anything, write articles and get traffic.

Let me remind you that a furniture-related blog is not the most popular topic; as a result, low-competition low-frequency queries bring users to the site without promotion.

We multiply 6 by 2, we get 12, behavioral factors and traffic are higher than those of competitors’ average requests, as a result of which the average requests on the analyzed blog grow.

TOP positions of MF queries + LF queries give 22 users per day, slightly lower than the HF queries of competitors.

This lack of numbers was supplemented by image search, which (quite popular in the furniture industry) brought in 2-4 users per day.

This scheme was strengthened by internal reference factors. Although there were no external links to the blog from third-party resources, competent linking was built. There were about 30-50 anchor links for each article. All anchors contained direct and indirect key phrases: most of the high-frequency queries, a smaller part of the mid-range queries, and not a large part of the low-frequency keywords.

So, with the help of several low-frequency queries, mid-rangers were raised, which in turn promoted high-frequency queries within one article. And let me tell you, no investments.

But since this scheme for promoting HF queries was known to me for a long time, I decided to complicate the task by excluding all instructions for search engines from the experimental page. This page is excluded from the general structure of the blog and does not have internal links, title, description or any headings. But it is promoted based on three key phrases.

For the purity of the experiment, I cannot give you a link, but I will tell you how to find this page. In the blog sidebar, in the search, type the word “SEO specialist”, and you will find her.

The experiment is already 80% completed, and soon I will publish findings on how to promote content by breaking the basic rules of search engines. Or maybe some of the readers have already guessed about my means of promoting this page?

Every day, millions of users enter certain search queries into search engines. Some queries are entered by users more often, others less frequently, and others very rarely. That is why search queries are usually divided into high-frequency, mid-frequency and low-frequency. In this article we will consider only low-frequency queries, because... the other two will have separate articles.

To begin with, it is worth noting that there is no rule that queries with a frequency of 0-100 are low-frequency, 100-1000 are mid-frequency, 1000+ are high-frequency. No. It all depends on the specific niche.

Example one. We have collected several hundred keys on the topic “vacation in Halkidiki”.

Of course, not all requests made it onto the screen. However, even this is enough to understand the meaning. The very last one (which was partially included in the frame) has a frequency of 1009, and everything that remains behind the frame has a frequency of 670 or less. Those. in this case we have only one high-frequency key, then we have 2 pronounced ranges of mid-frequency and low-frequency keys.

In this case, we have 1 request with a frequency of 14914, it definitely falls into the high-frequency ones. Behind it is a request with a frequency of 4519. Considering that the third and lower requests have a frequency of 2736 and below, the second one would be more correctly classified as mid-frequency. Those. in this case, the range of mid frequencies is 4519-1009, and low frequencies are 670 or less.

To show even more clearly that this division is conditional, let’s select a few more keys on the topic “bitcoins”. We did not collect all requests; we collected only the 500 most high-frequency ones.

And this is already enough to understand that in this niche there are completely different rules for grouping requests into high-frequency, mid-frequency and low-frequency. In this case, the first 5 should be classified as high-frequency requests (i.e., with a frequency of 90,000 and above), as mid-frequency - 32,000-75,000 (note that between 75,000 and 90,000 there is a huge gap that is not filled with requests at all, i.e. there is quite a clear boundary), and to low frequencies - 29000 and below (between 29000 and 32000 there is also the same “gap”).

Now let's look at the queries in more detail. To do this, let’s return to “tourist” queries and consider only 2 of them:

• hotels Chalkidiki Greece (frequency 4519);
• Chalkidiki hotels 4 stars all inclusive with sandy beach and swimming pool (frequency 14);

Notice how the second query:

• longer than the first;
• more specifically the first one.

Such long queries are rarely entered, which is why the frequency is low, BUT... Let's count how many shorter queries can be made from it:

• 4 star hotels in Chalkidiki (618);
• Chalkidiki hotels 4 stars all inclusive (frequency - 217);
• 4 hotels in Chalkidiki with sandy beach (frequency - 339);
• 4 star hotels in Chalkidiki with a swimming pool (frequency - 118);
• 4 star hotels in Chalkidiki with a sandy beach and swimming pool (frequency - 69);

etc., you can easily make up another 10-15 pieces.

Those. By “sharpening” the page for this low-frequency driver, we automatically advance through the other three, which have a better frequency.

So, we found out two patterns:

• the more accurately the user expresses his desires in the search query, the lower the frequency;
• the lower the frequency (of course, within the niche) - the more accurately the user expressed his desires.

Therefore, it is much easier for the search engine to provide the user with the information he is interested in. This means a very high percentage of targeted relevant traffic and a low failure rate.

A low-frequency request always consists of a main request (in our case, “Chalkidiki hotels”) and a “tail”, which contains all the wishes (we have highlighted them in red).

What queries are considered low-frequency?

After low-frequency queries, one more type of queries can be distinguished - ultra-low-frequency ones. Their frequency is even lower, and their tail is even longer.

However, both of them have a number of advantages:

• their variations and range are growing in breadth;
• it is on them that it is easiest to promote pages;
• It is much easier to attract targeted traffic using them (often even more traffic is attracted from LF than from HF and even MF);
• lower competition compared to high-frequency and mid-frequency;
• It is precisely according to LF that the greatest probability of converting traffic into the target action is greatest;
• the number of low frequencies is always greater than that of midrange and high frequency combined; therefore, much more content is generated under low frequency than under midrange and high frequency combined;
• significantly save money on promotion;
• the list of low frequency queries is regularly updated, which gives the site owner a very great prospects on attracting targeted traffic;
• no super knowledge is required to promote low-frequency queries.

From all of the above, it becomes obvious that the maximum conversion will come from traffic attracted by low-frequency queries (including ultra-low-frequency queries).

Selection of low-frequency queries in Yandex

To begin with, we will try to answer the question “Who needs to master the methodology for selecting low-frequency queries?” In theory, there should be a long list with items like “organizations with a wide range of services,” “online stores,” etc. But they can all be combined into one point:

Anyone who has a website and is interested in promoting it.

Naturally, now we smoothly move on to the technology itself. More precisely, for now, to the tools with which the selection is implemented.

• Pastukhov's keyword database;
• Keiso service.
• MOAB Base;
• Bukvariks;
• Wordstat.Yandex.Ru, SlovoEB and/or Keycollector;

However, the most important tool is... You!

Now let's briefly talk about Wordstat.Yandex, because... it is the most popular, and also clearly shows the simplicity of the procedure.

Wordstat.Yandex is a large database of Yandex queries. It contains hundreds of billions of user requests, and for each of them you can see the dynamics of changes in frequency, find out how often they enter this request in a specific region, as well as from which devices (in percentage terms) the request occurs.

As you can see, the screenshot is full of requests whose frequency is 20 or less. Therefore, there is nothing difficult at all in collecting suitable NPs. Well, if you add the Wordstat.Assistant extension to your browser, the collection will be simplified several times, because When you click on “+”, the phrase will automatically be added to the list on the left, i.e. You don’t need to select everything and delete unnecessary items, or copy-paste the necessary queries one by one.

Another important point- using the operator “!” you can find out in which case they are most often asked for. For example, instead of “low-frequency query,” you can type “!low-frequency!query” or “!low-frequency!queries” to see which of the two options is the most frequently requested (frequencies are 112 and 499, respectively).

Promotion for low-frequency queries in Yandex and Google

Without exaggeration, low-frequency queries can be called “self-promoting”, because They are the easiest way to get into the TOP 10 of Yandex and Google. All that is required of you:

• the content must correspond to the request and cover the topic as widely as possible;
• The presence of photographs, tables and other infographics is highly welcome;
• the site must have good internal optimization;
• inter-page linking must be competent;
• The site should have easy navigation.

If you follow these points, you can safely expect low-frequency traffic somewhere in a few months after publication (if the site is created from scratch; but if the site already has at least some traffic, then the traffic will be received in a shorter time).

Let us remember that in most cases, competition for low-frequency requests is either minimal or completely absent. This means that there is no need to buy links to such pages.

Now let's look at one important point regarding the content preparation itself. If the “one request = one page” principle worked before, now it cannot be called 100% working. Today, another principle is most relevant: “one page = one group of requests.” Naturally, the page must match every request. Those. We write a separate text for each request, and then combine everything into one big “footcloth”.

Well, now a few words about exceptions to this rule. We will be talking, as you may have guessed, about commercial requests for “hot” goods. And right away specific example- request “smartphone apple iPhone x 64” (frequency - 125). It would seem that within this niche this is definitely a low-frequency request. However, the entire TOP 100 (both in Yandex and Google) is filled with pages “Buy a smartphone Apple iPhone X 64 GB in the online store...” This is exactly the case when it will be difficult to break through even with a low-frequency request due to fierce competition. The picture is approximately the same with such niches as rental of vehicles (especially special equipment), specialized industrial services, b2b, etc. Therefore, analysis of the niche, TOPs and competitors is strictly required.

Now a few words about the balance between high-frequency, mid-range and low-frequency requests (relative to the total volume of pages on the site).

You have already learned that you mainly need to promote specifically low-frequency queries, because... it’s cheaper, more efficient, and most importantly, a high percentage of truly targeted traffic. However, not all users can formulate their desires in words, since they themselves do not know exactly what they want.

And immediately a concrete example. You are searching for the query “how to create a business card website yourself for free.” The request is quite specific, right? However, users under another query (for example, “how to quickly create a website yourself for free”) may not know that a business card website is one thing, an online store is completely different, a blog is a third, a news portal is a fourth, etc. . In such cases, it is much more correct to prepare several articles on the topic free creation site (separately for an online store, separately for a blog, etc.), then create separate page, which will tell you that a website can be created for free, provide a list of directions, and then make mutual links between these pages approximately according to this scheme:

Firstly, internal linking will never be superfluous. Secondly, this will give the user the opportunity to more accurately determine their desires. Those. Instead of leaving the site, the user will select one of the items that interest him.

Those. the semantic core should consist not only of low frequencies, but also of midrange and high frequencies in approximately the following proportions:

• Low-frequency queries - 55-85% of the semantic core;
• Mid-frequency queries - 10-30% of the semantic core;
• High-frequency queries - 5-15% of the semantic core.

And that’s all, actually.

Keywords that are included in the semantic core of any project have, from which the priority of their promotion or use in their materials may change. One of these characteristics is the frequency of the request.

What is search frequency?

Query frequency is the number of times the user entered a given query in a line search engine for a certain period of time. One of the most popular and available services to check the frequency of search queries is the Yandex service - Yandex.Wordstat (wordstat.yandex.ru). Accordingly, the more frequent queries we use in our materials and articles, the more traffic we will receive. However, not everything is so simple and first you need to understand the types of frequency queries and their application.

Types of request frequencies

In SEO, it is customary to classify queries by their frequency. It is believed that the higher the request frequency, the more traffic it will bring(if you look purely at the numbers).

The frequency types are as follows:

High frequency requests, also known as HF requests.

Mid-frequency requests, also known as mid-range requests.

Low-frequency queries, also known as low-frequency queries.

This classification is used by SEO specialists in their work. For example, when communicating with colleagues, in order to identify traffic potential and difficulty in promoting a particular group of requests.

Request frequency as a relative value

Frequency is not an absolute value. She reflects user demand for certain goods or services in a specific niche. It turns out that if you take all the queries in the topic “laptops” and sort them by frequency, then the first place will be a single-word query with a frequency of 5,295,645 impressions per month (relatively speaking). If we're talking about about the “cat food” niche, then the upper threshold there can be much lower, about 249,968 impressions per month.

It follows from this that we will assign a type to a request based on the upper threshold of frequency in the topic. As a result, we will have 3 groups, for each of which a frequency threshold will be assigned for phrases that are included in this group.

For example, for the topic “children’s trampoline” the boundaries will be as follows:

• HF - everything above 20,000 impressions per month
• MF - from 3,000 impressions per month
• LF - up to 3,000 impressions per month

You shouldn’t get too attached to boundaries and spend a lot of time classifying requests by type, because... This segmentation is rather arbitrary and has no practical value.

High Frequency Queries (HF)

High-frequency queries (HF) are queries that have the highest frequencies among all queries in our chosen niche. As mentioned above, a high-frequency request can be either with a frequency of 5,295,645 impressions or with a frequency of 27,811 impressions, as can be seen from the example below. In some topics, for example, a request less than 5,000 is no longer high-frequency.

Almost alwayshigh frequency queries are marker requests, one-word, or so-called.

An example of such queries could be “computer”, “car”, “apartment” and other general queries.

Photo 1: An example of a super-HF request for a niche with stable, heated demand.
Photo 2: According to statistics, cars are the second most popular topic of discussion among men.

An example of narrower, but high-frequency queries could be the following phrase (only if our niche is express weight loss courses):

Photo 3: Losing weight, losing excess weight is perhaps the most pressing problem for women. The frequency of the request indicates that there is a clear demand for this topic.

The request is not one-word, but the semantic meaning or intention of the user is clear from it, unlike the request “car”, when it is unknown whether to show him a site for car repair, washing or sale.

The advantage of high-frequency queries is the potential for large traffic. The difficulty is that there is unrealistic competition in high-frequency queries and getting to the top for them takes a lot of time and effort.

Important! Do not try to promote a young resource exclusively for HF requests; it will be much more profitable to focus on promoting mid-range and low-frequency requests for rapid growth of the project.

As practice shows, high-frequency queries make up no more than 5% of the semantic core of the project. There are cases when one general (HF) request covers 50% of the frequency of all other phrases from the kernel. This is a normal situation.

We can understand the relative difficulty in promoting one or another key phrase evaluating its competition index. You can create the index yourself by analyzing the results, or you can use the Mutagen service, which will calculate the index using its own formula. For example, if we see that according to Mutagen the competition for a phrase is 25, then we will not move forward on it soon and it is better to focus on other, less competitive phrases.

Mid-frequency requests (MF)

Mid-frequency requests (MF) are a group of requests that follow HF requests. For different topics, mid-range requests can start from either 1,000 or 50,000 impressions per month.

Mid-frequency queries are usually (but not always!) less competitive than high-frequency queries. In them it is possible to find queries with a longer “tail” and less competition. In addition, the MF request in most cases contains more words. This way, it’s easier for us to understand the intention of the user who entered this request and show him an article with a solution to his problem or offer him a product.

Photo 4: Such queries make up about 10% of the semantic core of the project.

It is easier to promote mid-range requests than high-frequency ones (for the most part) and it can take less effort and time. However, in this case, it will also be important to look at the competitiveness of requests in order to build the right strategy for promoting documents (pages) on the site.

Low frequency queries (LF)

Low-frequency queries are queries whose frequency is less than 1000 or 100. It is this type of queries that is most interesting SEO specialists and semantics, because they can make up 80-90% of the entire semantic core.

Why are there more such requests? It's simple. Many people, when they drive in search query in a line, for example, Yandex, they know in advance what they need.

Interesting fact! People learn to work with search. According to a study conducted by Yandex, in 2016 people entered 30% more 7-word phrases than in 2015. Thus, the “tail” of requests will continue to grow, and the user will refine his request more and more.

Example. There are 2 people - Petya and Masha, both want to buy a multicooker. Petya is an amateur in this matter and doesn’t know what types of multicookers there are, so he wants to see everything possible options. Therefore, his request may look like a high-frequency one - “multi-cookers”.

Photo 5: As a first step, Petya decides to just see what he has to deal with.

Masha consulted with her friends and knows what product to buy. Therefore, her request may look like this: “multi-cooker polaris pmc 0347ad”.

Photo 6: Masha found out everything from her friends a long time ago and immediately went to compare prices.

Moreover, in this case, there may be several options for writing a request - “polaris multicooker”, “polaris pmc multicooker”, “buy polaris multicooker” and so on. If we assume that every person tries to find the multicooker model they are interested in, then there will be at least 100 requests.

In some topics, queries may appear due to a lack of knowledge or names of any things, diseases, or products. Differences in knowledge, vocabulary, and experience of people who enter queries into the search bar generate a large number of low frequency queries.

For example, one user enters a query: “How to grow a money tree?”, and the second user, who has great knowledge, will write “How to grow a fat plant?”. Essentially, these requests are about the same thing, but the second request will have lower competition and frequency than the first.

Competition for low-frequency queries is usually small and moving up to 95% of them is not difficult.

Under no circumstances should low-frequency requests be ignored. There are often cases when a large number of low-frequency requests make up 80% of the project’s traffic due to quantity, while HF and MF requests are the remaining 20%.

One more characteristic feature LF queries are the “long tail” of a query - that is, a query from large quantity words For example:

Photo 7: And also + free + no registration + no SMS.

Having assembled groups of similar low-frequency queries led by the 1st marker

Photo 8: Tails “do-it-yourself” and “at home” - these are twin brothers. Usually, if you see one in a request, sooner or later you will find the second one :).

We will receive a full-fledged group of requests and will be able to write good material, which will advance according to low-frequency requests and gradually, increasing the confidence of the project and document, will rise to the TOP also according to high-frequency requests.

Results

We looked at the main types of HF, MF and LF requests. To summarize the main part, the following recommendations can be highlighted:

You should not focus on HF requests. If our core consists primarily of high-frequency queries, then difficulties will arise with its implementation and promotion. It is better to supplement it with midrange and bass and then implement it. In this case, it will be much easier to promote the project.

If we want to advance in HF requests, it is better to first assess the competition of each of them in order to better understand where the result will be faster.

Don't ignore low frequency requests. It is they, due to the quantity and total frequency, that help to cover all the semantics and desires of users and, as a result, receive traffic to the site.

Before introducing a nuclear system, it should be analyzed for the number of high frequencies, mid frequencies and low frequencies - this will help determine how complete the core is in front of us. If HF requests are 50%, midrange - 30%, and low frequency - 20%, then there is a potential for expansion of the frequency spectrum at the expense of midrange and low frequency. .