What is request frequency? Types of search query frequencies or why one-word position does not guarantee receiving traffic

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If Yandex's Wordstat worked not only with its own keyword database, then it would have no price. You could do everything in one window and enjoy life. But these are all dreams, so today we’ll figure out how to view statistics in Google. Moreover, we will work immediately with Keyword Planner, and with Trends, and even a little with Analytics. In general, let's go through everything that might be useful at once.

Why do you need Google search query statistics?

For three things:

Website optimization.
Launching a campaign in Google AdWords.
Forecasts and analytics.

To achieve these goals, we will need three tools: Google Keyword Planner, Trends and Analytics. In the first, we collect the semantic core for the site and advertising campaign, in the second, we track the dynamics of popularity, and in the third, we evaluate the effectiveness of everything else.

Example: we have an online store for bicycle products. First, we collect queries by topic in order to optimize the site - for this you need a Keyword Planner. Then, we use Trends and look at which months there is a peak in demand - this is necessary to launch an advertising campaign in AdWords. And finally, we track the effectiveness of SEO and context in Google Analytics: we look at how much traffic came from search and context and count the conversion.

Let's look at each service separately.

How to View Search Query Statistics in Google Keyword Planner

It’s easy to get started - go to AdWords and select “ ” in the “Tools” menu. In the menu that opens, you need to select what we will collect: the number of requests or their dynamics over a certain period of time. Right now we just want to see how many people want to buy a bike.

We are interested in all of Russia, so we’ll add “used” as a negative keyword. Click “Get results” and see this page:

In Russia, this request is searched a lot - from 10 to 100 thousand times a month. Its competition is also high, but there is one caveat: it is not “search” competition that is shown, but “advertising” competition: for this request, many contextual ads are shown, competition in organic search results can sometimes be lower.

Just below, Google displays statistics on similar search queries. For example, people search for “bicycle shop” not so often (1-10 thousand impressions per month), but at the same time it has low competition - the recommended bid is only 14.1 rubles. This keyword can be used both to optimize the store's home page and to display contextual ads.

Additionally, you can set parameters for selecting keywords: level of competition, negative keywords, recommended bid, topic or percentage of impressions received. This will help make a more accurate selection of the target audience, filter out unnecessary requests or impressions/clicks at an unreasonably high price. For example, we know that residents of the Krasnodar region willingly buy from us and we want to launch contextual advertising in this region. To do this, we set the desired region and filter out unnecessary queries using negative keywords - we are not interested in those who are looking for used bicycles. Next, we look at the recommended bid and select queries that will recoup the costs of the campaign.

By default, all queries are displayed in phrase matching. This means that the number of queries in Google Keyword Planner is shown for all query forms similar to the given one. Impressions for queries diluted with additional words or slightly changed word forms are taken into account. For example, instead of the request “buy a bicycle,” “buy bicycles” or “buy a bicycle inexpensively” are taken into account.

How statistics and search query history in Google Trends can help

Using this service you can:

Monitor seasonal increases in demand.
Analyze any niche or popularity of a product.
Assess in which region people most often search for what you sell.

In the bike store example, the first function is most interesting - with its help you can find out when it’s time to launch the context, discounts, promotions and everything else. Example:

The graph tells us that we need to prepare the sleigh in winter - the rise in demand begins as early as February. Plus, below there is a map of Russia, which indicates the popularity of the request in each region. She says that the most hardcore cycling fans live in the Kostroma region - where the popularity of the request is 100%. Speaking of the latter, it is shown as a percentage of the maximum number of requests. If the greatest demand for bicycles was in May (conditionally 1000 requests), then this value is taken as 100%. And this is the main disadvantage of the service - you will have to calculate the specific number yourself. Well, it’s also impossible to check several requests at once, so Trends is only suitable for point analysis, or to form a general idea of demand surges.

Now imagine that our store is going to sell skateboards. Let's see how exposed they are and where most skaters live. We checked Keyword Planner in advance - everything is OK with it. We enter the request “buy a skateboard” into Google Trends and look. The picture is similar to the previous one - the demand for boards begins to grow in February, reaches a peak in June and gradually decreases until October. At the same time, most skaters live in Moscow and St. Petersburg (logical). However, the curve does not fluctuate as much as in the case of bicycles - increases in demand are gradual, and the overall level never falls below 20% of the peak. If such indicators are sufficient, then we can safely launch skateboards and spare parts for them.

In a commercial sense, Trends are especially useful if you are introducing a new product to the market, say, a new model of equipment that has not yet gained much popularity. In this case, no one really knows about it one hundred percent and therefore does not search for it. But with the help of the tool, you can track whether the popularity of this product is growing over time. If there are positive dynamics, then it makes sense to invest in it, because over time more people will want to buy it.

Keyword Planner has similar features. If you start an advertising campaign, an icon with a graph appears to the left of the number of requests. There you can also see the frequency dynamics of queries, but it’s easier to work with Trends.

Search query statistics in Google Analytics

Everything is simple here - you can track which keywords people use to visit your site most often. This will help if you are assessing the effectiveness of SEO or expanding the existing semantic core - a key phrase may be discovered that you did not initially take into account.

How to view statistics on the number of key queries in Google through third-party services

The choice is not limited to Google’s own tools; you can use any of dozens of third-party services to select keywords - they are good because they show a specific number of queries, instead of a range, as the native search engine tools do. Almost all of them are quite successful in collecting statistics, but the problem is that almost all such tools are paid. Let's take KeyCollector as an example - it works with a bunch of keyword databases, collects data from both Google and Yandex and can do a lot of other useful things, but it costs at least 1,200 rubles apiece (if you buy 10 licenses at once). There is no point in buying a program if you do not collect three semantic cores per day.

Results

We figured out how to look at statistics on the number of key queries in Google. The easiest option is to use the search engine's own tool, Google Keyword Planner. It helps you find out how often people search for queries on your topic, collect similar keywords, assess the competitiveness of queries, and immediately create a semantic core for an advertising campaign in AdWords. You can also get useful statistics on key queries in Google Trends. The tool helps track seasonality of demand and plan advertising campaigns. If you know that bicycles are bought from February to March, then you need to advertise your store during this “hot” period.

One of the most popular modules in Rush Analytics is the Yandex Wordstat parser, and this is no coincidence. When collecting the semantic core, it is necessary to know exactly the frequency of the collected queries in order to correctly prioritize promotion and get rid of “garbage” and null queries. Often the task is to break through several tens of thousands of requests for frequency in Yandex, but this is not an entirely simple task for self-written Wordstat parsers and desktop programs, and here’s why:

Yandex Wordstat has good protection against parsing, for example, banning IP addresses from which parsing is carried out and throwing out captcha in response to requests from bots. To effectively collect data from Wordstat, you need an effective algorithm for connecting IP addresses and other tricks
To parse a large amount of data using desktop programs, you will need many IP addresses (proxies), which Yandex easily bans if the connection algorithm is not optimal, and proxies are not a cheap pleasure
Also, for parsing you will need to automatically enter a large number of captchas (for example, connecting Antigate for this task). This factor, if the parsing algorithm is not optimal, can make the parsing itself unprofitable, since the cost of the captcha will be prohibitively high
Most desktop programs do not have protection against data loss during collection. So, for example, having collected half the data and spent money on it, if the parser fails, you risk not only not receiving the remaining data, but also losing the data already collected

Parsing Yandex Wordstat in Rush Analytics

Taking into account all the difficulties that may arise when parsing Wordstat, we made our Wordstat parser as fast, convenient and resistant to the maximum number of problems associated with parsing:

No proxies or captcha! You no longer need to think about banning your proxies or the huge number of captchas that Yandex issues. Just create a project, upload keywords and wait for the finished result file
High parsing speed. Our algorithms use the optimal IP address connection scheme and other tricks to make the parsing speed phenomenally high - you won’t even notice how your project is completed!
Data security. By creating a project in our parser, you can be sure that it will be successfully completed and available for download at any time and from anywhere in the world - all data is stored in the cloud!
Support for all Yandex regions. Many users have a need to determine the frequency of queries in Yandex not only for the Moscow or Russia region, but also for others, including Ukraine and Belarus. In Rush Analytics, you can determine the frequency of requests for any region that Yandex currently supports.

Collection of all frequencies. Using our parser you can collect all frequencies: search query, “search query”, “!search! query”.

Collecting the left column of Wordstat. In addition to checking the frequency of queries, it is possible to collect keywords from the left column of Wordstat with adjustable parsing depth from one page to collecting all pages in the left column.

Collecting the right column of Wordstat. Collection of keywords from the right column of Wordstat is available.

If you need high-speed collection of Yandex Wordstat frequencies, Rush Analytics is the best solution, especially if you need to collect large amounts of data. For users who need to collect more than 100,000 requests per month, individual conditions are provided, just write to our support at

It's no secret that most articles on the Internet are written with specific keywords in mind. Their use serves several purposes, the most important of which is promoting the resource on the World Wide Web, striving for the first lines in search engine results, and attracting a large number of visitors, mainly the target audience. However, before you write an article aimed at solving these problems, you need to know which keywords to use. In order to help copywriters and website owners solve this issue, there are special services. One of the most popular and authoritative is “Yandex Query Frequency”, or Wordstat.yandex. We will tell you how to use this tool with the greatest efficiency in this article.

What is Wordstat?

Most webmasters in our country use the frequency of Yandex search queries to select keywords. What is this tool? This is a service that combines various kinds of word forms entered by users into the search bar. A person who is interested in the statistics of any request can enter any word here and find out the total number of its impressions on the Internet. In addition, all key phrases in which this word was used and the frequency of queries for each of them will be presented.

Information is provided on a specific word/phrase, its derivatives (in a different case, number, order, etc.), as well as on associative queries. That is, those that were used along with the word/phrase you are interested in. In order to see them, you need to go to the “What else were people looking for when looking for...” tab. This function allows you to significantly expand the semantic core of the site (a set of words that have a specific topic and are used for writing articles and promoting on the Internet).

Structure of Wordstat.yandex

The resource is a line for entering words with tabs located under it. The first is called "According to the words." Here you can check the frequency of requests in Yandex for specific words or phrases. Tracking this data for a certain period (say, a month or a week) is also quite simple - you just need to use the “Impression History” section and select the desired period of time. You will be presented with a graph of changes in the frequency of displays of certain words/phrases.

In order to narrow the search area, there is a “By Regions” tab. Using it, you can find out the frequency of requests in Yandex for the same words, but in a specific city/region. In addition, for the purpose of specification, SEO optimizers use so-called operators. Let's see what it is and what they are like.

Operators of "Yandex.Wordstat"

Let's say that for some keyword we are interested in a specific word form and its query frequency. Yandex statistics gives us this phrase in different combinations. To fix it in the desired form, use the "quote" operator. Here's what it gives us (for the query "best bars"):

there were: the best bars in the world, in the best Moscow bars, etc.;
became: the best bars, the best bars, the best bars, etc.

Let's take a brief look at other existing operators:

"Exclamation mark" - used to obtain the exact meaning of keywords, placed before each word. For example, the !best!bars.
The minus operator excludes certain words from queries. For example, the best bars in Moscow.
Operator "plus" - with its help, the frequency of Yandex queries can take into account prepositions and conjunctions in order to show the results of queries only using them. For example, + what to wash windows with.
"Brackets" and "forward slash" - allow you to group several keywords in one query. For example, travel packages (buy | price | last minute). As a result, you will be able to obtain information simultaneously for the following queries: “Where to buy tours”, “Price of trips to Egypt”, “Last minute trips for May”, etc.

Operators are actually very useful and have a significant impact on the results obtained. So, for example, for the keyword “Buy a tea store,” the frequency of Yandex requests without an operator will be 2080 per month, and with the use of “Buy!Tea Store” - only 67. To select keywords, be sure to take these nuances into account, otherwise you risk stumbling upon for a large number of “dummy phrases”.

In addition to Wordstat.yandex, there is another popular statistics service - Google Adwords. The frequency of Yandex queries may differ from the data obtained using the Google tool. Each of these systems has its own user audience and, therefore, its own indicators. Therefore, to get the best results, it is recommended to check requests using both services, which are currently the largest ones used in our country.

Conclusion

In this article, we talked about what the Yandex query frequency is, how to find it out for specific words and phrases, and how to get the most accurate and useful data on them. The correct selection of keywords is very important for promoting on the Internet and attracting visitors to your resource. That is why services such as Yandex.Wordstat are very popular among SEO optimizers, copywriters, advertisers and website owners.

I think this guide was as detailed as possible, BUT… There is one simple thing that can greatly help you when using the semantic core, and today I will tell you one secret)

When compiling the semantic core, we took into account such important points as screening out inappropriate keys, determining the cost of each of them, and much more. And today I offer you determine the full frequency of each request, depending on the place in the TOP. I think that this article will be really interesting and will help you answer the question - how to determine the competitiveness of a request)

When promoting your website, it is also important to know the main ones that are used to bring the resource to a leading position. And I tell you how to promote commercial and information requests.

The theory of determining the frequency of requests

First, a little theory. When compiling the semantic core, we determined only the exact number of impressions in Yandex using the operator “!...”. But this operator only shows the number of impressions directly in Yandex. The real number of transitions can only be found out by analyzing the transitions from all search engines.

Search engine statistics are as follows:

Yandex - 52.4%
Google - 33.7%
Search.Mail.ru — 6.6%

Continuing the list further does not make the slightest sense, because... for the most part, we only need the first number, namely - 52.4% total traffic generated by the Yandex search engine. I think now determining the competitiveness of each request and the total traffic generated by it will not be the slightest difficulty. In order not to complicate the calculations and not get ugly numbers, just any frequency is enough multiply by 2. Now the semantic core for the main page of my blog will look like this:

The calculations used the simplest formula:

=PRODUCT(C2,2)

Now we see exactly how much traffic each of the keys we use brings, that is, we see the full frequency of requests. But that's not all! Now, let's determine how much traffic each individual request will bring if our site is in a certain TOP. This manipulation is not at all difficult to implement. To do this, we just need to know the distribution of traffic by position in the SERP. And the picture looks like this:

1st position - 50%;
2nd position - 21%;
3rd position - 15%;
4th position - 6%;
5th position - 3%;
6th position - 3%;
7th position - 0.6%;
8th position - 0.2%;
9th position - 1%;
10th position - 0.2%

This data is more than enough for us!

We are finalizing the semantic core

It's time to finalize our core and put an end to it. Everything is done in Excel and done simply. We add two more fields to our table, as shown in the image:

In the TOP field you will simply need to enter the desired number from 1 to 10. For each line of the field Traffic by TOP we use the formula:

IF(F2=1,PRODUCT(D2,0.5),IF(F2=2,PRODUCT(D2,0.21),IF(F2=3,PRODUCT(D2,0.15),IF(F2=4 ;PRODUCT(D2,0.06);IF(F2=5,PRODUCT(D2,0.03);IF(F2=6,PRODUCT(D2,0.03);IF(F2=7,PRODUCT(D2, 0.006);PRODUCT(D2;0.004))))))))

It is enough to insert the formula only in line E2. And just copy it to all other lines, for which you need to select cell E2 with the formula already inserted, move the cursor to the lower right corner of the cell and when an even crosshair appears, drag the formula to all the necessary cells. It's quite simple, so I won't go into detail.

Now we can enter any required TOP and see the exact traffic for a given request in the selected top. I think this improvement will be really useful for you.

The modification we made today is not at all complicated, but it makes our core much more visual. And next time we will make another innovation in the semantic core and bring it to the most visual form, adding a little automation. The improvements that we will make next time will allow us to create a convenient environment where it will be enough to enter a few parameters, and it will do a lot of painstaking work for us, don’t miss it!

Hello, dear readers of the blog site. Today there will probably be a rather boring article about working with search query statistics from Yandex, Google and Rambler. Well, what could be interesting in analyzing the frequency or number of questions entered by users into search engines?

Therefore, it turns out that if you write articles yourself, then your project is simply doomed to success and high traffic, the lion’s share of which will be provided by transitions from Yandex and Google (search traffic). But, unfortunately, in the real world this is far from the case and everything is to blame for the notorious search query statistics, damn it.

Why bother with search query statistics?

The fact is that the statistics of queries from Yandex, Google or Rambler (Wordstat is usually the most popular) can negate all your attempts to attract users from search engines by writing interesting, absolutely unique articles, but blindly optimized for randomly selected queries.

This is exactly what happened with most of the articles on my blog site, when I finally decided to conduct a full analysis of all the keywords that may be related to my blog in Yandex statistics.

The results disappointed me for the most part, although there were some successful articles that could attract visitors from a huge number of keywords at once, often with a very high frequency. But let’s still begin to deal with the problem of accounting for statistics on search queries from Yandex and, to a lesser extent, Google (well, although this system can probably already be classified as the living dead).

The problem is that by working blindly (without preliminary drafting at least for the article that you are writing at the moment), you can seriously miss and optimizing the text of the article and internal linking (link anchors from other pages of your site to the promoted page) are not at all for those search queries that can bring you a large number of visitors.

It’s very easy to miss the intuitive selection of promising queries, but then it will be very disappointing to see in the statistics of Yandex or Google that they turned out to be dummies (i.e., search engine users extremely rarely use this particular combination of keywords in their questions).

No, of course, if all webmasters were in the same conditions and no one had the opportunity to view and analyze statistics in the same Yandex, then there probably wouldn’t be such a problem. But the statistics of requests from search engine users is available to everyone without restrictions, and by not using it, you are simply putting yourself in unfavorable conditions.

You should not listen to the “trolls” who shout that you have lowered your SDL (project for people) to the level of GS (a project for making money, designed for a short life cycle) by first compiling a small semantic core for a future article, using online services for this statistics of Yandex or Google and Rambler search queries.

This is due to envy or their “troll” nature. But you shouldn’t spam the text of the article with keywords - in this case, you can ruin everything.

Let me first provide factual information, and only then will I pour water on the matter your experience working with search query statistics, mostly Yandex (I don’t know how to write briefly, so there will be a lot of letters; sorry, but it seemed to me that this was all important). So, the facts. Why do you think search engines like Yandex, Google or Rambler give you the opportunity to delve into their statistics?

After all, optimizers (Seo specialists) have always been on the other side of the barricades in relation to search engines. Do you know why? There is no place for any principled considerations or ideologies. Everything is banally simple and, as one would expect, comes down to money, because optimizers take away from search part of their main source of income from contextual advertising. A large number of potential Direct or Adwords clients receive visitors to their projects using the services of optimizers (SEO specialists).

Therefore, it looks very strange that Yandex and Google give optimizers (you and me) access to search query statistics. The answer here is again tied to the main way search engines make money - contextual advertising. The fact is that context advertisers need this information to compile the most or Google Adwords. It is thanks to them that this request statistics is available to us too, and it would be a sin not to use it in our personal (selfish) interests.

Yandex, Google and Rambler statistics services

In my unprofessional opinion, there are three or even four main sources for obtaining direct (there are services that collect data from these services automatically - they parse them) statistics of search queries:

How to work with Yandex query statistics

I am not a professional SEO specialist, so for me to understand the overall picture and compile a semantic core, Yandex statistics are quite enough, although it is possible that when promoting a project using very high-frequency phrases, it would make sense to clarify the data in Rambler or Google services, but I do not need this.

A little theory. Search queries and keywords very often confused with each other, so I’ll try to clarify. A search query is a set of words that any user types in the search bar. There are sets of words that are searched very often (high-frequency queries or HF), there are less popular combinations of words (mid-frequency or MF), and, of course, there are rarely found sets of words (low-frequency or LF).

I don’t draw a clear line between these queries based on the frequency of their displays, but it is usually considered that if a set of words has a frequency of over 10,000 impressions per month, then it is high-frequency. If a phrase has a frequency of less than 1,000 impressions per month, then it is low frequency, but mid frequency lies somewhere in the middle. But these figures are more than arbitrary and strongly depend on the topic.

It is clear that it is best to choose more frequent queries for the future semantic core, because if you get on the first page of search results, you will receive a very large influx of visitors. But it will most likely be very difficult to advance in HF or MF, because there will probably be a lot of other webmasters as smart as you.

Therefore, when selecting search queries for the future semantic core, both for the site as a whole and for a separate article, you should correctly calculate your strengths - otherwise you may not get a single visitor at all via HF, because you won’t be able to get even close to the Top 10 (first page of results).

True, there will not always be many people willing to promote themselves for high-frequency and mid-frequency queries. There are cases when the competition in HF and MF is quite low and everyone has a chance to make it. Here you need to look and analyze those sites that are in the Top for your chosen query. If there are not very trusted resources there, then you can try to fight.

When we come directly to optimization, this is where we talk about , which essentially represent individual words from the queries you have chosen, for which you will try to advance and get to the Top (the first ten sites in the search results).

Very often, the dozen search queries selected (as a semantic core) for a given specific article may consist of only a few keywords, which you will need to use N number of times in the text of the article and be sure to include them in the Title. Moreover, at the beginning of the Title, include the words of the more frequent request and then in descending order. For example, the semantic core of this article can be said to consist of:

I checked the frequency according to Yandex statistics, enclosing the given words and phrases in quotation marks to weed out obvious dummies. Those. I started by typing something like “query statistics” and got a bunch of possible options with these words, as well as a bunch of associative queries in the right column. I checked each of the proposed options for the actual frequency of impressions by enclosing them in quotes and as a result I received the list given just above.

As you can see, with all the richness of phrases from the semantic core of the article, there are not so many keywords for which I should optimize the text. Now you just need to create the correct Title for the page with the article, so that at the beginning there are keys from the most frequent request, and use each keyword in the article from one to two percent of the total number of words in the article.

Be careful not to spam the text and increase the density of keys to 3 percent or more - it is possible to exclude the article from . It is better to use keywords in different word forms (do not try to cram only direct occurrences into the text), in accordance with the logic of your narrative. I once mentioned that online service where you can conduct articles on the density of occurrence of keys.

As you can see, this article seems to have everything in order, except that the frequency of the first word (I am not citing it so as not to further increase the density of its occurrence) should be reduced. You can ignore the nausea indicator, because... it is calculated there as the square root of the most frequently used word, which means that the larger the text, the higher the nausea will be, which is not logical. And in general, nausea has already sunk into oblivion.

Let's summarize again. After you have sketched out on a piece of paper those queries (analysis of statistics in Yandex usually takes a few minutes) from which you expect to receive an influx of visitors, you will need to isolate keywords from this semantic core of the article and be sure to use them in the Title of the promoted page (which the higher the frequency, the closer to the beginning of the Title tag) and use keywords selected from the semantic core in the text of the article with frequency from 1 to 2 percent of their total number.

I admit that I started writing articles taking into account Yandex query statistics only a little less than a year ago, and doing it with my eyes completely open only about a month ago. And the reason for this is not laziness at all (I don’t have a lot of it), but rather some inertia (not flexibility) in relation to something new. Well, like, I’ve always done this and will continue in the same spirit.

But sometimes you need to take a breath, look around and understand whether you are moving in the right direction. It is precisely the use of Wordstat to analyze your project that allows you to look around and change the direction of movement if necessary. For the last couple of weeks, I have been trying to extract from Yandex statistics all the options that may be relevant to my blog.

I do this manually, which is quite tedious, but I gradually develop an understanding of the overall picture of this entire kitchen (my eyes open). The brain is already melting, but the analysis is addictive and gradually reveals obvious mistakes, and also allows determine the topics of future articles, because what users most often type in search engines is what interests them most. And keeping up with the wishes of future readers is, in my opinion, a direct path to the successful development of the project.

By the way, when analyzing your project using Yandex query statistics, you may need to find out whether your site already has any positions for the word or phrase you are interested in. To do this, I use the capabilities of the program, which I already wrote about, but forgot to mention the possibility of determining the visibility of a site by the keys you need using this wonderful program.

You will need to go to the “Selection” tab of the Site Auditor program, enter the words you are interested in in the “Check” area and click on the arrow located on the right. You will be redirected to the “Site Visibility” tab, where you will need to enter the URL of your resource and click on the “Check” button.

As a result, you will see the position of your site for the keyword of interest in the Yandex and Google search engines. If no positions appear, it means your project ranks below fiftieth in the search results.

Good luck to you! See you soon on the pages of the blog site

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