Definition of high-frequency requests. Search queries and their frequency

What are LF, MF and HF requests? How to determine which request is high, medium and low frequency? This article is devoted to these and other questions.
Concepts
There are two terms - "frequency" and "frequency", which should not be confused.

Frequency - the frequency of the process for a certain period of time, measured in units. Frequency - a characteristic of the occurrence of a given request among a certain set, measured as a percentage. In the case of search queries, query frequency is the number of times the key phrase is used in search engine, and frequency is a percentage determined by the ratio of word usage to text on the page in question. In this article, we will talk about the concept request frequency.

Requests are of the following types

HF (high-frequency queries) - the most keyword or phrase on a particular topic.
LF (low-frequency queries) - a keyword with a low query frequency.
MF (mid-frequency requests) - a keyword whose request frequency is between LF and HF.

Determine requests for HF, LF and MF

As we wrote earlier, there are services that allow you to view the statistics of certain requests. These, of course, include Yandex Wordstat, and for English words, the KeywordDiscovery service.

Let's say you need to match queries for a duct site. We enter into wordstat word"air ducts" and we see that the number of its views is 113,260 times. For our site, this request is high-frequency, as it reflects the essence of the site's theme and, in comparison with other queries on our topic, has the highest views.

In our case, the lowest frequency query is “sale of air ducts” with a view rate of 163. What then will be the queries of the middle frequency?

In theory, MF is the average frequency value between HF and LF requests. But sometimes it can be difficult to decide in which view interval mid-frequency queries should be considered. Many webmasters "don't bother" with this and take it "by eye". The exact way to determine which request belongs to a particular type is difficult. Even the mathematical formulas presented on some sites cannot unequivocally answer this question, since their compilation is based more on assumptions.

What are the requirements to promote the site?

The answer to this question will give your budget.

RF queries have a clear advantage over other queries - the number of visitors per day. The disadvantage of HF is high competition, so getting into the TOP for them is spending a lot of money. Not all webmasters can afford HF. But even if you manage to promote the site on them, the result achieved will not be long-term.

Advantages of MF and LF Requests

quality target audience;
achieving results in a short time (3 months);
low competition;
small investment.

Disadvantages of promotion on low-frequency requests

To compose a semantic core (SN) and do it absolutely free, you need to: use a wonderful, and most importantly - free, service from the Yandex search engine, 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 looch.

How to use Yandex.Wordstat?

In a special input field, we write phrases or individual words, the frequency of which we want to check and select similar ones. Then we press the button "Pick up".

After the selection, we will see the statistics of queries 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 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 receive this number of impressions when specifying 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 broke" 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 queries only from the specified region.

Why are we not going to select words with the Slovoeb program?

The thing is that this program has recently often been somewhat disappointing and issues 50 requests at once. Also, the requirement to enter captcha appears very often.

What is the program klooch ?

With this free program it is possible to define easily so to speak a khalyavnost of this or that request. More on this will be discussed below.

How to determine the frequency of the request?

There is no absolutely definite indication to determine the frequency of a request! For example, for non-commercial requests, this level is higher than for commercial requests.

Without insisting on anything, it can be defined as follows:

Micro-low-frequency (mLF) — from 0 to 200 requests within a month;
Low-frequency (LF) - from 200 to 1200;
Medium frequency (MF) - from 1500 to 5000;
High frequency (HF) - from 5000 and almost to no limit.

You can also highlight Mega frequency (mHF), but you should not delve into this.

How to determine the competitiveness of the request?

The competitiveness of requests can be determined by formulas, or you can do it “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 - medium competitive (SC);

3) Up to 100,000 - low competitive.
This sorting will never tell you exactly, so we will not take it into account. Competition can also be identified by direct entry into the title of the article - the more entries, the worse for us; by the total number of optimized articles - the fewer such articles, the better; by the number of main pages in the issue - the fewer muzzles, the better; according to the trust of the site from the issuance - a smaller trust is better.

There are many such divisions, we have indicated the main ones. First, we need to define the topic of the request. For example, the topic of our site is games. So, you do not need to take the request "how to train cats", since this request does not fit with our topic. And for search engines, all this is not very good.

For example, let's take the same theme of "games". We enter a general query into Yandex.Wordstat, such as "play ....", ".... finish the game":

After that, we select a rarer request, such as "play racing".
We see the following:

Now we select low frequency request. But, there are also a lot of generalized queries. Therefore, we need to go to the second page and select the query "play racing against zombies." Number of requests per month - 516:

We analyze:

According to the Klooch program, there are no matches in the Title in Yandex. Therefore, you can easily reach the TOP10 or even TOP3. How to determine the freeness of the request now ?!
Let's say there are five matches in the Title - then you can easily reach the top 6. That is, the fewer matches in the Title, the better for us. The situation is similar for the main pages.

Further, we copy all found requests in Excel. But! The frequency of 500 requests per month does not interest us. You need to find the average frequency queries. Let's take a closer look at the example of the request "race to play online makvin".

We analyze:

This is a medium frequency query with a long tail. This request 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 request, for example, "cars play races."

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

The frequency is largely due to the subject and business area, as well as the 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 show per month. The more low frequencies at the start of work, the more traffic there will be.
How to promote low-frequency queries? These are the simplest and most undemanding queries, they do not need to be backed up with links - you just need to create relevant content: write articles, news, product cards that will most meaningfully and accurately answer the user's question.
Traffic for such requests will start to grow immediately, but perhaps slowly: the requests are low-competitive, the results may not be impressive at first, but the more such requests are introduced to the site, the higher its traffic will be in the end.

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

Mid-frequency requests, their concept and features

Mid-frequency queries - how much? Mids are a little more popular than lows. Mid-frequency and low-frequency queries are the basis of website promotion, because there are the most of them. Using both groups of requests, you can achieve optimal attendance at a low investment.

It is more difficult to promote a site on commercial midrange than on informational ones, and this must be taken into account: commercial requests are selling, and the competition for them is higher. For mid-frequency requests, the number of offers corresponds to the level of demand: there are really a lot of sites that are promoted mainly by mid-range. For example, on the Internet, more than one company offers "buy cheap plastic windows", so be prepared that work on the site in this case may take a lot of time.

High-frequency queries, their concept and features

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

High-frequency queries are an arbitrarily wide variety and total number of options: there are not only informational and commercial, but also brand queries, which receive very large traffic. But such requests are extremely highly competitive, so the highest-frequency requests are the most expensive in all respects.

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

How to determine a high-frequency request or not? Use the same Yandex.Wordstat.
How to promote high-frequency queries? Long and expensive. To get to the top of the search results, you will have to work long and hard on the site, impressively investing, including financially. It should be borne in mind that, in particular, the most high-frequency queries (Yandex or Google - it doesn’t matter) are a huge audience flow, including non-target ones, and extremely high competition.

What queries are best to choose for promotion?

What requests - low-frequency, mid- or high-frequency - to collect for search engine optimization your internet site? 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 better to choose for your site depends on the site itself.

If SEO has not been done before, the site is not optimized and you are only 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 mids and lows, take on the highs.

According to the optimization vector, you can also select queries for promotion:

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

Many beginner optimizers have questions about query frequencies. What is LF, MF and HF? How to determine if a request is high-frequency or low-frequency? Does the theme of the site affect the assignment of a request to one of the intervals? And so on. We will try to answer all these questions, as well as to reveal in more detail some points in matters of frequencies.

Definitions

Note that you should not confuse the terms " frequency" and " frequency“! Frequency- this is a characteristic of a periodic process, measured in the number of units for a certain period of time. Frequency is a characteristic of the occurrence of a given object (word) among a certain set and is measured as a percentage. Roughly speaking, for our case, request frequency- this is how many times a month a given key phrase was searched in a search engine, and request frequency(let's say on the page) is the percentage of the content of the query (word) on the page in question. In this article, only the concept of search frequency for a specific key phrase will be considered.

HF (high frequency) requests - the most requested word (words, phrases) in your subject (most popular requests).
LF (low frequency) queries - words and phrases that are requested with low frequency in search engines and related to your subject.
MF (midrange) request - something in between LF and HF (hereinafter there will be an exact quantitative definition).

Competitive request- this is a query for which it is difficult to get into the top of the sickle (the first results in the search engine) due to the competition of sites relevant to this query.
Highly competitive request– a query in which there are a lot of competitors for this key phrase in the sickle.
Low competition request– a query in which internal optimization factors are sufficient for the site to be on the first page of the sickle for a given keyword phrase (word).

Significance of the request- the concept is subjective and is determined by the webmaster (optimizer, site owner) independently, depending on the subject and goals of the site (for more information about significance, see What is the minimum significant frequency of query sampling). The frequency below which requests do not fall into the sample of significant and are not viewed for analysis is called minimum significant sampling rate.

How to determine RF requests for your site

To determine the frequency of search queries in search engines, there are services that provide this information. For example, to search for the frequencies of Russian words, you can use the service provided by the Yandex PS - query statistics. To search for statistics on English words, you can use the KeywordDiscovery service.

Let's say that you have a site for the production of air ducts (for those who are not familiar with the concept of air ducts, you can read here: about air ducts). We enter the phrase “air duct” in wordstat and get a list of relevant queries, where “air duct” is in first place with 16949 impressions per month. But in the right column, we can also see the word “fans”, which is searched much more often (75485 per month), however, fans may not apply to your topic and, therefore, considering the word “fan” in your topic as a high-frequency query would be incorrect. That is, from the entire set of queries, you need to make a selection of the most significant ones (up to the words with the minimum significant frequency, which is determined by the webmaster or optimizer). And already this sample should be divided into HF and LF. Sampling meaningful queries is the definition semantic core (this is what optimizers mean when they say that “the theme of the site affects whether the query is considered high, mid or low”).

Precise definition of boundaries between HF, MF and LF

So you have a selection. Now we need to remember the probability theory and the distribution function. Again, although it is intuitively clear that MF- this is frequency average between HF and LF. However, it can be difficult to determine this average. For example, HF “duct“- 16949 and LF “sale production of air ducts“ – 6 requests/month. What will be the SC then?

If we take the arithmetic mean, then it turns out that among the sample we do not have a midrange at all. To do this, consider the dependence of the sample on the graph (Figure 1.1). It can be seen from the graph that the dependence is logarithmic, since if the abscissa axis (request number) and the ordinate axis (request frequency) are taken on a logarithmic scale, then with some error we will get a linear histogram of request frequencies. This means that the MF will be in the middle of this linear regression.

Figure 1.1 - Graph of the distribution of search queries by frequency (the axes are taken on a logarithmic scale).

Let us introduce the notation
hvh- the maximum value of the frequency of the RF request;
Khnch- the minimum value of the frequency (minimum significant frequency) of the request

Then, it can be argued that

Hsch \u003d / (Hvh - Hnch)

(the square root of the difference between the maximum and minimum frequency)

The above dependence comes from the property of the logarithm log(x)/2 = log(x^0.5) = log(/x).

Often Khnch much less hvh and, therefore, it can be neglected, we get:

Hsch = / Hvh

Now let's check these values on the example “ air ducts“:

hvh = 16949, hvh = 6

Hsch \u003d / (16949-6) \u003d / 16943 ≈ 130

The value 130 will be midrange value. Now it is necessary to determine the interval in which the frequency will be considered average. To do this, we divide the linear interval into 3 equal parts, so each part will have its own frequency range. Deviation value from absolute medium frequency will be approximately equal to 33% .

Midrange Width:

D = log(Xhv)/3 = 3 /log(Xhv) = 1.41;

So the interval from 10 log(Xs) – D/2 before 10 log(Xs) + D/2 will be considered as the midrange. In our case, this

This interval includes keywords, as (information as of March 6, 2008 00:00 Moscow time): air duct cleaning, air ducts price, pvc air ducts, air ducts price, etc. Anything above 646 will be HF, and below 26 - LF. All queries whose search frequency is in the range from 26 to 646 may be called mid-range requests.

Conclusion

The main ratios for determining the interval of medium frequencies are the following:

Xsch.min = 10 log(Xs) – D/2, Xh.max = 10 log(Xs) + D/2
Hsch = / Hvh, D = log(hvh)/3

Note that when determining the MF interval, one should take into account an individual sample for your site and it may not always have a logarithmic dependence. However, the above formulas are suitable for most cases of keywords (tested on several dozen topics). With another characteristic of the behavior of the search frequency key phrases it is necessary to look for a function that describes the frequency distribution.

Hello, dear readers of the blog site. Today I want to talk about site internal linking and its meaning for .

Actually, I have been focusing on internal factors from the very beginning of the existence of the blog, but at first the main motivation for me was simple, but the tasks solved by linking do not end there. A link should be understood as the usual ones, which, as you know, are taken into account. The beauty of internal linking is that you are free to do it the way you want and spend only your time, not money.

LF, MF, HF and NC, SC, VC search queries, reference weight

In fact, not only external links decide the issue of finding your site in the top, but also internal optimization the text that we talked about in the article about, as well as correctly placed links from one page of your resource to another. Why this is so important, we will try to analyze in this article, and I will also show a few linking examples that I use myself.

Before continuing, I want to draw your attention to the fact that links (including internal ones) are taken into account on two scales:

Static weight transmitted by the link (for Google this is determined by a non-toolbar value, and for Yandex by an unknown value)
- the text that stands between the opening and closing tags of the hyperlink, which is called the anchor of the link. Search engines cut out anchors (and internal ones too) leading to this page of your site and file them to the text of this page. Therefore, be very subtle in composing texts, even internal links, so as not to get banned or.

I forgot to mention in the previous article the principles of gradation of search queries that SEOs came up with to simplify the situation. So, they are divided into:

LF (low frequency)- in many commercial topics, we can say that LF fluctuate in the range of 30 - 100 requests per month. This refers to the statistics taken from with empty blanks already sifted out (the request is enclosed in quotation marks and each word is preceded by Exclamation point). For non-commercial topics, the bass range, in my opinion, is wider and may well reach up to 300.
MF (mid-frequency)- from 100 to 1000 (sometimes up to 500) in commercial topics and up to several thousand in non-commercial topics.

HF (high frequency)- anything above the two previously described categories

But that's not all. There is also such a thing as the level of competition in the subject. In this regard, it is customary to divide search queries into:

All these figures for determining the gradation of frequency and competitiveness are purely conditional and will vary from subject to subject. However, this helps to correctly distribute efforts and quickly understand what in question. It is clear that the best option for advancement it turns out to be a midrange or even a high frequency, which at the same time is an NK.

I have this happened extremely rarely for my information requests. But the opposite happened more often. For example, almost all requests from the WordPress theme are LF or maximum MF, however, in terms of competition, almost all of them can be classified as VC or SC.

Promotion through them is troublesome, costly and, if successful, will not bring the desired dividends in the form of a huge flow of visitors. However, this does not stop a number of enthusiasts who built their project only around this topic - honor and praise to them.

The meaning of internal linking, how to link manually

Well, now you are savvy in theory and it's time to voice the benefits that you can get from literate internal linking (keyword "literate"):

First, links to other pages on your site can greatly improve the user experience for visitors, which in turn will lead to . And what will the improvement of the PF entail? That's right, the stability of the growth of your project's positions in search results and a guarantee of a good search relationship.
Secondly, it is possible to purposefully increase the static weight of promoted pages by placing internal links on them from other (best of all similar in subject matter) web pages.
And, thirdly, internal links can be placed on promoted pages not just anyhow, but with the necessary anchors. Thus, for low-frequency queries you create conditions for getting into the Top, and for high-frequency and mid-range queries you give a good impetus for better use of external optimization - obtaining links from other resources, mainly through their purchase, for example, in such services:
1. MiraLinks described
2. GoGetLinks- read about the nuances of working with it
3. GetGoodLinks– description of the possibility of buying links from pages with PR (high static weight)
4. RotaPost — full review exchange opportunities

There is various schemes relinking to promote requests of different frequencies, as well as technical solutions that allow all this to be implemented. We will also talk about this, but I want to give a simple an example of placing internal links to a promoted page. Which pages should be linked from? How to understand it?

Yes, in general, it is best to ask the search about this. Let's say that you want to help some page to get into the top for midrange or high-frequency query by internal linking. How to choose donor pages? Just. Open advanced search (to the right of search string an icon with two horizontal lines) (remember, I wrote about it in an article about that, and ), limit the search only to your resource and enter this same query:

Your promoted page will be in the first place in the search results (if this is not the case, then there is already a reason to think about it), and other pages of your resource will follow in descending order of their relevance to the search query. Those. these are the most relevant pages of your site after the one promoted in the opinion of the search engine itself. Only put down internal links from them to the promoted.

And with what anchors should I put down? It is clear that the request pure form, mentioned in a hundred links, will be a bust. I think you need to follow the logic of diluting anchors when buying external backlinks (we'll talk about this in more detail in the continuation of this series of articles), however, some especially cunning SEOs believe that you can simply take the already existing words in these articles, which the search considered the most relevant of the entire text . Already guessed? That's right, these are the words that will be highlighted in.

Need for invention is cunning. Personally, I use this method of searching for relevant pages for internal linking, but I don’t use highlighted words from snippets. It is possible that I neglect what should be taken into account.

Internal linking schemes, "ring" for WordPress

In order to implement one of the linking schemes, automation methods will be needed. The static weight transmitted by links to certain pages of sites is calculated using the iteration method.

The first pass is carried out and the relative statistical weight for all pages is calculated, and then the second pass is made, already taking into account the received weights, etc. Explaining all this is rather dreary and I will not do this, but nevertheless I will give the calculations that can be applied in practice:

Any page, even one that has just appeared on the Internet, already has unit static weight. Any incoming link to it increases this weight.
Outgoing links, contrary to the popular belief, do not take away the static weight from the page, but they can indirectly affect the total static weight accumulated by the site (too long to explain, but it's true). Therefore, when placing internal links from the page, you should limit your Napoleonic plans. Everything needs a measure.

Optimal from the point of view of increasing the static weight is the "ring" scheme. The simplest example is two pages linking to each other. If one of the links is removed, then the stat weight accumulated by both of them will decrease sharply (at least it was like that before). The ring can include more than two pages - the main thing is that it be closed.

If there are more than one leading links from the web page, then the weight that will be transferred will be divided by the number of outgoing links
The link does not transfer all of the page's static weight, but only a part of it. Which one? No one knows, except for the programmers of Yandex and Google. It used to be thought that ninety percent. Now they say that this value is already less than ten percent. In this regard, although internal linking scheme "ring" and works now, it no longer gives that phenomenal gain that it was before.
Due to the reduced percentage of the stat weight transmitted by link, it will no longer be profitable to buy links to the main page or to sections when promoting, so that the weight flows from them to the target documents. An immeasurably small part will reach the addressee, so it is better to buy backs mainly directly on the promoted pages.
To exclude pages from the linking scheme that do not need to be downloaded, but links to which must be present on almost the entire site (for example, a shopping cart in an online store or a login / registration block), then these links are better close from indexing by search engines in Ajax(read more). This is very easy to do (when you figure it out), despite the awesome name. Create a separate file for the hyperlink and include it in the right place in the template. Elementary.
The main page in any case in the eyes of the search will have priority, therefore, when promoting midrange and high-frequency queries link from main on them will be a prerequisite for internal linking

In doing so, it should be taken into account that end-to-end links(for example, from the menu) are considered by search engines not as a hundred links from different pages, but, most likely, as one or a little more. Therefore, when creating various link blocks, you need to understand that they should not be through, but must change from page to page. In this case, their static and anchor weights will be transferred much more efficiently.

Among other things, this method of linking will improve the indexing of the site and increase its completeness. Sometimes a separate block is written for indexing purposes, where they randomly scroll (after the next page refresh in the browser) links to all pages of the resource so that the search robot can see them.

Personally, to promote my articles, I use a scheme similar to what is commonly called "promotion under low frequency requests":

This scheme is quite often implemented in online stores, putting links to the previous and subsequent lot from the same category in the product card. Optimizers have noticed that such a ring works best within the same section or category. Apparently, search engines break large sites into relatively independent parts, links between which will not be as effective as within a section or category.

And here is a relink like "ring" for pages with articles I have already implemented. Articles from each rubric are linked separately, thus forming several dozen rings. And it all works on the machine and pretty well. Well, my external links mostly lead directly to landing pages with articles. Although with such an internal linking scheme, even without external optimization, low-frequency queries can get into the Top.

idea this method suggested already repeatedly mentioned by me Dimoks (back in 2009), and it was finalized not by the unknown blog admin WP-kama. In general, everything is discussed in detail there, but just in case, here is the code that I added to the file from my theme (they live at /wp-content/themes/):

Function kama_previous_posts_from_cat ($post_num=5, $format = "", $cache = "", $list_tag="li", $echo=true)( global $post, $wpdb; $cache_key = (string) md5(__FUNCTION__ . $post->ID); $cache_flag = __FUNCTION__; if ($cache && $cache_out = wp_cache_get($cache_key, $cache_flag))( if ($echo) return print($cache_out); else return $cache_out; ) $cat = get_the_category($post->ID); $cat_id = (int) $cat->term_id; $same_join = "SELECT ID, post_title, post_date, comment_count, guid FROM $wpdb->posts p LEFT JOIN $wpdb->term_relationships rel ON (p.ID = rel.object_id) LEFT JOIN $wpdb->term_taxonomy tax ON (rel.term_taxonomy_id = tax.term_taxonomy_id)"; $same_and = "AND tax.term_id = "$cat_id" AND tax.taxonomy = " category" AND p.post_status = "publish" AND p.post_type = "post""; $sql = "$same_join WHERE p.ID< {$post->ID) $same_and ORDER BY p.post_date DESC LIMIT $post_num"; $res = $wpdb->get_results($sql); $count_res = count($res); if (!$res || $count_res<$post_num){ $exclude = $post->ID; if ($res) foreach ($res as $id) $exclude .= ",".$id->ID; $post_num = (int) $post_num-$count_res; $sql = "$same_join WHERE p.ID NOT IN ($exclude) AND p.ID != ($post->ID) $same_and ORDER BY p.post_date DESC LIMIT $post_num"; $res2 = $wpdb->get_results($sql); $res = array_merge($res,$res2); ) if (!$res) return false; if ($format) preg_match ("!(date:(.*?))!",$format,$date_m); foreach ($res as $pst)( $x == "li1" ? $x = "li2" : $x = "li1"; $Title = $pst->post_title; $a1 = "ID) .""> "; $a2 = ""; if ($format)( $date = apply_filters("the_time", mysql2date($date_m,$pst->post_date)); $Sformat = str_replace ($date_m, $date, $format); $Sformat = str_replace("( title)", $Title, $Sformat); $Sformat = str_replace("(a)", $a1, $Sformat); $Sformat = str_replace("(/a)", $a2, $Sformat); $Sformat = str_replace("(comments)", (($pst->comment_count==0)?"":$pst->comment_count), $Sformat); ) else $Sformat = $a1.$Title.$a2; $out .= "\n<$list_tag class="$x">($Format)"; ) if ($cache) wp_cache_add($cache_key, $out, $cache_flag); if ($echo) echo $out; else return $out; )

This function allows me to add multiple links at the bottom of each article. Probably, it will not be superfluous for usability, but basically given type internal linking is aimed precisely at increasing the static weight of promoted pages.

In theory, low-frequency requests should themselves get into the Top, but high-frequency and mid-range will have to be helped by additional manual linking (I described its principles a little higher).

Oh yes, I completely forgot. Adding code to functions.php is not enough. You also need to place the call to this function in the right place in your blog template. The single.php file is usually responsible for articles in WordPress, so I added the block header and the function call code to it:

Previous articles from the same category (will open in a new window):

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