Low frequency. What are low-frequency and mid-frequency queries?
/ 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 covers a lot important points, which 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 several times in previous articles, introducing you to the basics of SEO, so it’s time to tell you about keywords in more detail, teaching you 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 according to 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
HF MF LF and VK SK NK
Yes, yes, these incomprehensible letters from the title will be the topic of this chapter :-)
Three key questions when compiling the semantic core of a site are frequency, competition and conversion.
Request frequency determines how many times during a month people search for a given phrase. The higher the frequency, the more visitors we will get when we get to the TOP.
Competitiveness of the request determines with whom we will have to compete for a place in the search results.
Conversion answers the question - what percentage of visitors using a given phrase will become buyers, i.e. will bring us some kind of financial return.
Traditionally, queries are divided into high-, mid- and low-frequency. And they are designated by the letters HF MF LF.
The competition is similar. VK SK NK denote high-, medium- and low-competitive requests, respectively.
Very roughly, the frequency of requests can be divided into the following gradations:
High frequency – more than 10,000 requests per month
Mid-frequency – from 1000 to 10,000
Low frequency – less than 1000 hits per month
Frequency of queries in the semantic core . Frequency and level of competition are related nonlinearly. Those. in most cases, a higher frequency query is in turn more competitive, but not always. The opposite is also true. There are low-frequency, but very selling queries, for which there is a real battle in the TOP.
At first glance, high-frequency queries seem to be the most delicious. Wow, we’ll get to the top for the request “air conditioners” - life will begin!
In fact, such keywords often become a trap that inexperienced webmasters fall into. The advantages of such requests are obvious - a large influx of visitors. Let's consider the disadvantages:
High-frequency queries tend to be very vague and unclear. I have already given an example with air conditioners - it is not clear what exactly a person is looking for using the word “air conditioners”. Accordingly, conversion and financial returns will be very low.
The TOP for HF queries is often filled with such “monsters” that it is almost impossible for a young site to compete with them.
In any case, it may take two years to get into the top ten for very frequent and competitive queries. Therefore, even if you have every opportunity to “push aside” your competitors, expect that this will not happen right away.
As a result, an attempt to immediately focus on very high-frequency requests can lead to a “waste” of the promotion budget without achieving any results.
However, I’ll tell you one little secret about how to use HF requests even for a young site just below.
Mid-frequency requests. These are the ones most commercial sites should target. As a rule, they are more specific and provide good conversion. The competition is also strong, other resources will be about your level.
Low frequency queries. This is where the fun begins. In SEO there is such a term as “long tail” or “long trail” of requests.
Beginners will be surprised, but 70-80% of visitors come to the site precisely for low-frequency and ultra-low-frequency queries. It’s even surprising sometimes how people formulate their thoughts. Phrases like " rent a one-room apartment in Alushta on Lenin Street 28 near the market with parking” meet once every five years, but their diversity is so great that they make up the lion’s share of traffic.
It is unrealistic to specifically optimize a website for such requests, and it is not necessary. But in the process of moving through the midrange frequencies, the “long train” will tighten itself.
And here I go to VK HF requests. Let’s take “site promotion” - a very popular request and for me definitely thematic. But firstly, it is geo-dependent, and I have a site “without a regional reference”, secondly, it is somewhat blurry, and thirdly, the TOP is filled with mega, simply mega-promoted companies. Ingate, Ashmanov, BdBd, etc. They have been promoting for 20 years, and I can’t even imagine what kind of budgets they have “inflated” to sit firmly in the TOP 10.
There are truths and miracles, for example old version This textbook has been consistently ranked 1st in Yandex.Moscow for many years for the query “site optimization.” Not a penny was invested in promoting this request, and the page “pushed out” much stronger competitors. But this is rather an exception.
So, I won’t try to get to the top using the phrase “website promotion”. But I will certainly use the words “promotion”, “promotion”, “optimization” in the textbook. And with this I will collect that same “long trail” of search queries. Here's some advice for you - use high-frequency keywords in your texts, but don't make them your main goal.
Assessment of possible traffic. Google and Yandex have their own keyword selection services that allow you to view query statistics. They allow us to estimate the approximate traffic that our site will receive when it reaches a particular place in the TOP.
First of all, I present a table of CTR (click-through rate) depending on the place in the TOP.
Position CTR
1 place 30%
2nd place 20%
3rd place 12%
4th place 9%
5th place 8%
6th place 5%
7th place 5%
8th place 4%
9th place 4%
10th place 5%
As you can see, even at best, only a third of visitors go to the first site in the search results! At first glance this is disheartening. You take a certain target phrase, look at the competition, estimate the financial costs... and then count the number of possible visitors and all you can do is cry :-)
But not everything is so sad. Let’s take a phrase with a popularity of 1000 queries per month according to Yandex statistics (Google has its own service, but I’m more accustomed and more convenient to work with Yandex, and its data is enough).
Let's calculate the flow of visitors for the 5th place. Achieving TOP-1 is unpredictable; for some requests, the site ranks easily, but for others, even if you push with a bulldozer, nothing comes of it. We will consider 5th place as good, real result.
1000 requests * 8% = 80 visitors per month. It doesn't seem to be so great. But there is also Google. Its popularity is slightly inferior to Yandex, but for a rough forecast I simply multiply the resulting figure by two. Let's round up and get 150 visitors. Well, then the most important thing - remember what I said about the “long train”. Traffic for our specific keyword, which we have chosen and diligently promoted, will be only 20% of the total visits. We multiply 150 by 5 and get a traffic forecast of 750 people per month.
The accuracy of the estimate is plus or minus a kilometer, but you get the idea. CTR is frighteningly low, but the “long trail” is surprisingly long.
My book was published in paper version. If this tutorial turned out to be useful for you, then you can thank me not only morally, but also in quite tangible ways.
To do this you need to go to
Queries for website promotion are keywords or phrases by which Internet users search for information about specific products, services, etc. All search queries are divided into three types: low-frequency, mid-frequency and high-frequency. In addition, there is an additional category “long tail”.
Low frequency queries
These are the keywords for which Internet users search for information no more than 1,000 times a month. The search takes place using special search engines, the most famous of which are Yandex and Google.Examples of low-frequency queries are “buy spare parts in Moscow inexpensively” and “Lenta Style dress model 1068.”
By creating a page for low-frequency keywords, you will attract your first audience to the site. And in two months (or maybe less) your site will be in the TOP 10 search engines for the queries you promote.
Mid-frequency requests
Queries that are more popular. They are entered into search engines from 1,000 to 10,000 times a month.An example of mid-frequency queries is “asus monitors”.
Promotion using keywords in this category must begin when you have already taken at least some positions in the search for low frequency words.
To promote according to middle requests, it is necessary to carry out internal linking between the pages of the site, as well as purchase external links on third-party Internet resources. At the same time, it is important that third-party sites have a good reputation and trust, and that the links do not look like outright spam.
High frequency queries
Keywords in this category are the most popular among Internet users. This group includes queries that appear on search pages more than 10,000 times a month.An example of an RF request is “Apple”.
To be in the top for this type of words, you will need patience, attention and hard work. It can take six months or more to get into the top ten sites for HF queries.
Before you start promoting high frequency queries, you should have a strong foothold in mid- and low-frequency words. Internal linking must be in perfect condition, and the external reference mass on verified sites should increase steadily. In addition, you will have to become familiar with concepts such as " behavioral factors" and "promotion through articles."
A long tail
Queries for which users search for information even less often than for low-frequency ones.Long tail example - Alcatel phone one touch reviews.Promotion of such keywords often happens on its own. And if not, then they should pay attention. After all, if a user goes to the site based on such a request, the probability of purchasing a product or service is 99%.
To compose a semantic core (SC) and do it absolutely free, you need to: use the wonderful, and most importantly - free, service from search engine Yandex, which is called Yandex Wordstat. This service is available at wordstat.yandex.ru. In addition to the specified service, we will also use a free program klooch.
How to use Yandex.Wordstat?
In the special input field we write phrases or individual words, the frequency of which we want to check and select similar ones. Then click on the button "Pick up".
After selection, we will see statistics of requests in the specified search engine, which will include the phrase or word we specified. In addition, there we will see other queries that were indicated by people using the words we specified. Phrases and words will be in the column on the left, and other queries will be on the right.
Some numbers will be displayed next to each request. They give some preliminary forecast of the number of impressions per month. And perhaps we will get this number of impressions when we specify this query as keywords or a word. Let’s say a certain number next to the word “laptop” will indicate the number of impressions with the word “laptop” for all queries, such as: “compare laptop”, “buy a laptop”, “laptop is broken” and so on..
You can also specify “All regions” and then the selection of words and phrases will come from “the whole world”. Or you can specify a specific region or regions and the selection will match requests only from the specified region.
Why don't we select words using the Slovoeb program?
The thing is that this program Lately Often it’s not much fun and issues 50 requests at once. Also, the requirement to enter a captcha appears very often.
What is the program klooch ?
With this free program you can easily determine the freeness of a particular request, so to speak. This will be discussed in more detail below.
How to determine the frequency of a request?
There is no absolutely definite indication to determine the frequency of a request! For example, this level is higher for non-commercial requests than for commercial requests.
Without insisting on anything, we can define it like this:
Micro-low frequency (MLF) - from 0 to 200 requests within a month;
Low frequency (LF) - from 200 to 1200;
Mid frequency (MF) - from 1500 to 5000;
High frequency (HF) - from 5000 to almost no limit.
You can also highlight Mega Frequency (mHF), but it’s not worth going deeper into this.
How to determine the competitiveness of a request?
The competitiveness of requests can be determined using formulas, or it can be done “by eye”. For example, you can see the number of documents that appear in the search results for a specific query:
1) Results from a million or more - highly competitive (VC);
2) From 100,000 to 1 million - moderately competitive (MC);
3) Up to 100,000 - low competitive.
This sorting will never tell you exactly, so we won’t take it into account. Competition can also be determined by its direct occurrence in the title of the article - the more occurrences, the worse for us; in terms of the total number of optimized articles - the fewer such articles, the better; by the number of main pages in the results - the fewer faces, the better; according to the site trust from the search results - a smaller trust is better.
There are many such divisions; we have indicated the main ones. First, we need to determine the topic of the request. For example, the topic of our site is games. So, there is no need to take the request “how to train cats”, since this request is not compatible with our topic. And all this is not very good for search engines.
For example, let’s take the same theme of “games”. We enter a general query into Yandex.Wordstat, such as “play in....”, “.... finish the game":
After that, we select a more rare query, such as “play racing.”
We see the following:
Now we select a low-frequency request. But there are also a lot of generalized queries here. Therefore, we need to go to the second page and select the request “play racing against zombies.” Number of requests per month - 516:
We carry out the analysis:
According to the Klooch program, there are no matches in Title in Yandex. Therefore, you can easily reach the TOP10 or even the TOP3. How can we now determine if a request is free?
Let's say there are five matches in the Title - then you can easily reach the top6. That is, the fewer coincidences there are in the Title, the better for us. The situation is similar for main pages.
Next, copy all found queries into Excel. But! A frequency of 500 requests per month does not interest us. We need to find medium-frequency queries. Let's take a closer look at the example of the request “racing play online maquin”.
We carry out the analysis:
This is a mid-frequency query with a long tail. This request is low competitive. There are few pages in the search results for this query. It can also be included in the semantic core.
Now it’s time to find a free high-frequency query, for example, “cars play racing.”
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 this request into the search engine string 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 that they potentially high 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 queries (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 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. .