▷ Multiply the power of netlinking with metamots 2020 -

Metamots, and more generally semantics, are often opposed to netlinking in conversations, as if when we do one, we don’t do the other. But how would the two strategies be incompatible? We will present here an explosive method to strengthen the weight of netlinking with semantics. Well done, this simultaneous use increases the return on investment …

Many of us have found that links made from thematic sites close to ours worked better. The question is, “Why? “, But also:” How does Google detect it and what are its requirements? ”

In fact, for a few years, the juice sent by the links has taken on “colors”.
For a link to be strong, the pages on each side of the link must be in affinity. In other words, the page which makes the link and the page which receives it must have subjects in symbiosis.

Example of likely affinity: a page about classical music and a page about Mozart. On the other hand, the link will not necessarily be strong if it comes from a page that talks about rock music of which Mozart is not, strictly speaking, one of the stars.

With the page that talks about rock music, it will take some gymnastics to make Google swallow that, if so, the pages are well related. So, what should be done and how? Are the pages close enough? And even the page talking about classical music, does poking with words that we imagine, us human, as relevant, will it allow Google to understand what we want it to understand?

Be careful, I say “close to an engine” because when we are human, our intelligence is real and not “imitative” like that of an engine.

What is happening :
Today it seems that a link is processed for 1/3 structurally and 2/3 “semantically”. A semantic juice is therefore 3 times more powerful than a neutral or irrelevant link … This proportion over the years continues to increase in favor of semantics.

Suppose we make an effort on the themes of blogs (or other) that make us links, how do we know if we have hit the nail on the head?

Indeed, for a link to work well today, Google must be able to make a prediction when it sees the link: “I, Google, I think the page behind the link will talk about that”.

Hmm, the “wet finger” version may not work, and / or very partially. As a result, the work is the same, but we are “splashing” about the expected results (“splash”: noise made by a sword stroke in the water).

Let’s take a look at how to help Google’s friend fulfill their predictions without the risk of working for nothing and never getting caught.

To do this, I offer a step-by-step tutorial with metamots and Eureka tools on cocon.se.
It will be understandable by all.

Now let’s go to the tutorial.


We want to position ourselves on “Travel to the USA”. To do this we want to write many articles here and there and make links from these articles to my page “Travel To USA”.

STEP 1 :

We calculate the metamot “Travel to the USA”. Metamot is the signal that must be placed on a page precisely so that Google can appreciate our page at its true value. A metamot consists of 15 “lexies”. The 15 must be placed in our content.

But during this stage, what interests us is to see what exactly are said lexies.

metamot with lexies
Metamot of the phrase “Travel to the USA”

Note in passing that it seems that cities do not count as much as we might have thought when people type “travel to the usa”. There is, however, an interest in national parks and the territory itself. This information may be used in our marketing elsewhere.

With a view to doing things well, we will especially look at the determining lexies. These lexies will play more on the relevance to obtain than the other lexies (even if, in the end, it will be necessary to put them all anyway). But there, even talking about different subjects in the blog articles that will link my page, as much as the subjects revolve around these determining lexies.

We will retain as directions for the subjects of the blog articles: “Travel to the USA” (target), “National Parks” and “American Territory”. We are going to avoid “insurance”, because we would find so many subjects that we would have an extremely tedious sorting job…
We could also find subjects on the “biometric passport”, but that will perhaps make us a lot of sorting, so we will be satisfied with the 3 expressions above for this tutorial.

Note: In practice, let’s always start with two or three word expressions to find subjects, but avoid those of a single word, because the subjects will not be targeted enough.


Let’s go to the Eureka tool on cocoon.se and ask it for subject ideas (fast Eureka will suffice a priori) for each of the expressions selected above: “Travel to the USA”, “National Parks” and “American Territory”.

Here for “Travel to the USA”:

eureka subject request
Looking for topics in Eureka

In the end, with the 3 expressions chosen, Eureka delivers me no less than 400 subjects here. Let’s add accents, maybe make it more French if necessary, because these subjects should also be used to start the TITLE of articles.

If we are extremely ambitious, nothing prevents us from making “normal Eureka” which deliver even more subjects. If there is not enough yet, we can also search around all the lexies and not only around the determining lexies.


Now let’s calculate the metamots of all these subjects … let’s not forget to also add “Travel to the USA”.

It’s time to listen to the works of Claude Debussy, serene and relaxed… Indeed, it will take several hours to see the quantity of metamots to calculate.

My batch of 398 metamots is calculated. Everything that follows is childish.


In the left menu, click on “semantic mesh”.

At this point, it should be noted that out of the 398 metamots calculated, some of these which do not suitably link to any other, are not present in the drop-down list.

Locate the keyword “Travel to the USA” in the list (the list is sorted in alphabetical order).

choice of target expression
Select from the list the expression to “push”

Click on it to select it.


Now, a single operation is necessary to retain only the metamots which naturally “slide” towards our key expression.
Just click on “All In”.

click on all in
Let’s click on the “All In” button

What does “All In” do?
“All In” will choose all the topics that can actually slide to our target page. We can then make a link from these subjects to “Travel to the USA”. What is not in affinity detected by Google is therefore not retained by the tool.

202 articles can link our page
Calculation done, 202 articles can link to our page

With the subjects we chose at the start, only 202 are actually in affinity with “Travel to the USA” … We therefore escaped the writing of 195 articles which would have been made practically for nothing! The ones we are going to write, on the other hand, will be effective.

Save our project (button at the top right).


Now that we have saved our work, we will be able to recover what it takes to contextualize the links in each of the articles. We will place 4 or 5 lexies among those proposed at +/- 15 words away from the link pointing to “Travel to the USA”.

sweets for Google
Let’s place some candies for Google at a short distance from the link

Save this PDF.


Now, so that metamots can “sign” each of our articles, let’s go to “Simulations”. Let’s choose the size of the articles that we think we will write. By then clicking on one of the subjects, the list of lexies to be placed on the page concerned is shown to us.

semantic signature of subjects
15 different lexies to place in each article as well as in the target page: this is the semantic signature of the subjects

To have all the optimization tips in one place, here for 1000 word texts, click on the “PDF 1000” button

lexies and weighting
List of lexies and their weightings according to the size of our articles (here 1000 words)

Save the PDF.


Once the articles are written, we have an “Optimization” space where we can refine the texts and optimize them “Live”.
It is also in this area that we can have ideas for headings if we have launched a search beforehand.
To launch this search, click at the end of the listing on the “Optimization” page.

search for titles
The orange button allows you to launch a search for titles for the whole batch of metamots

Again, this is a fairly long calculation, because the search is launched on all the items in the batch. In addition, the system does not know us and therefore sometimes proposals will be irrelevant. That being said, overall, it is a precious help.

All the headings use the lexies of metamots, that can give us tracks of sub-subjects of our articles.

Once calculated we find them in the optimization area of ​​the subjects.

proposed headings
The proposed headings are at the bottom of the screen, in each optimization of each metamot


The semantics in seo can suit all kinds of situations. It is gradually becoming essential as Google’s maching learning is launched at full speed. So you have to adapt to what he comes to “understand” so as not to work for nothing.

I hope you enjoyed this article and tutorial.
I also started a semantics SEO course on my blog, it is open access.

The metamots and Eureka can be found on cocon.se