Collection of semantics

Compiling a semantic core is the most important and fundamental part of any website promotion. The ability to collect it correctly is a useful skill, and understanding what to do with the information received is already an art.

This article was created for people who do not have professional skills or specialized automated services. Its goal is to form a holistic understanding of the reader about why a semantic core is needed, how to assemble it and what to do with it in the future. There is a lot of material, make tea.

Why do we need a semantic core and how to work with it

Many customers and novice seo-specialists simply do not understand the real significance of the procedure for collecting semantics in the process of SEO promotion . However, with the proper approach to processing data from the kernel, we get a powerful tool for the most diverse tasks. We have tried to highlight the most important areas:

Analytics

The semantic core is an extremely flexible concept. Depending on the level of requirements and the task at hand, it can vary greatly in the final form.

The obligatory minimum is the presence of only a search query.

However, large projects, on which entire groups of SEO specialists, advertisers and other marketers of all stripes work, require much more diligence when collecting the core.

The simplest example of analytics that is available at the semantic core collection level is the analysis of the seasonality of queries. Here is how such an addition to the semantic core looks like:

In this view, we clearly see where the season is in decline (red cells on the left), and in which months the growth begins (yellow and green).

If you need to analyze an array of niche information topics for trend growth, to work with a blog, then an addition in the form of a graph or diagram is perfect:

Here is an example of another version of the extended semantic core:

In the future, perhaps we will write a separate article in which we will analyze the purpose of each individual parameter, but in this topic we will just superficially look at them.

Separately, I would like to dwell on such an important nuance of working with semantics as the belonging of key queries to a commercial or informational segment. I often find articles on the Internet where experts very simply distinguish between keys according to conditional features.

For example, if the query contains words of the type:

• “price”
• “cost”
• “order”
• “buy”

these are necessarily commercial keys that must be used to promote the relevant pages.

If the keywords have an interrogative structure and include the corresponding pronouns, for example:

• “how”
• “why”
• “how much”
• “where”

then they must be regarded as “informational”.

In most cases this is true, but there are extremely ambiguous exceptions. For example:

The query “windows best prices” at first glance seems to be purely commercial, but if you study the search results, you can see that most of the results are aggregator sites.

At the same time, the search phrase “how much does it cost to install windows”will offer us much more targeted search results, despite the presence of a question and a corresponding pronoun.

This is not surprising, since search engines are improving and take into account not only the design of the search query, but also the results that most users have chosen as relevant, with similar access. In this regard, I propose to follow the most proven rule:

If you are not sure about the ownership of the request, just contact the search engine. He knows for sure!

Planning

1. Structure

Having already clustered semantics, we begin to design the site structure. If you have a basic extensive structure, you can try to scale it by creating pages for lower-frequency queries.

Even despite the abundance of low-frequency semantics, it is not always necessary to increase the number of pages to the maximum, at least to preserve the logic in the site architecture.

In our practice, we focus on the indicator of the frequency of the cluster marker request of at least 100, in exact accordance.

Marker keys are queries that most closely match the promoted page or cluster (group) of keywords in the core. Usually, they entail a number of similar variations.

Example:

“Smartphone smartphone xiaomi redmi note 10 pro” – marker request for the corresponding page.

Smartphone smartphone xiaomi redmi note 10 pro price

Smartphone smartphone xiaomi redmi note 10 pro buy

xiaomi redmi note 10 pro smart phone reviews                   these are auxiliary keys

Smartphone smartphone xiaomi redmi note 10 pro Kyiv

Smartphone smartphone xiaomi redmi note 10 pro order

2. Metadata and text content on commercial pages

It is important to remember that when working with metadata in Google, the order in which you write the keys matters.

Based on the semantics of each individual cluster, unique metadata and a task for the copywriter to write text content are compiled.

In this regard, you can make a significant mistake when writing the title, simply by mixing up queries, for example, using the key “bicycles for children” (with a frequency of 400), to the left than “bicycles for children” (with a frequency of 3500)

Writing a technical task for a copywriter is a separate issue. We just have a good article on this subject, I suggest you also read it: https://wedex.com.ua/blog/kak-pravilno-pisat-teksty-dlya-sajtov-v-2021-godu/

3. Returning to seasonality

Having in front of us clear statistics on the dynamics of growth and decline in demand on the Internet for individual services and goods, we will be able to more accurately prioritize contextual advertising, right down to individual pages – when and which pages it is better to focus on.

In some cases, you can try to experiment with metadata, updating some of them in accordance with seasonality.

4. Article planning

As I mentioned above, the requirement for writing informational articles is formed based on the dynamics of frequency on a particular topic.

For example, if a specialist observes a steady increase in interest in a topic from users, like this (frequency over the past 9 months):

How to make a semantic core

The compilation of a semantic core is a rather individual process. You should not think that all SEO specialists strictly follow the same algorithm. On the contrary, everyone works based on their experience, involvement in the project and free time.

In this article, we will omit the options for working through paid automated services, such as KeyCollector, and dwell in more detail on all the nuances of manual assembly, which are usually missed by the authors of similar articles.

Collection of marker requests. Zoom

As indicated above, marker queries (hereinafter referred to as “markers”) are a kind of landmarks for the corresponding groups of underlying key phrases. That is, it is the markers that let us understand the basic outline of semantics.

On the diagram it will look like this:

In yellow, I highlighted the marker requests, and everything else is the subject requests.

Google Ads Keyword Planner is used for manual selection of markers. Here is a sample of its interface:

It is important to note that this tool is more focused on working with search advertising. It is not very suitable for obtaining accurate data on the frequency of requests; rather, it gives an understanding of the “outline” of these values. Google simply does not publish exact information on this parameter.

In addition, the service may miss low-frequency keys that do not appear in existing advertising campaigns, which further complicates the work.

So how do you highlight marker queries? There are many options, but we prefer the most proven – manual. Especially when it comes to unfamiliar topics.

The selection principle is quite simple: we are looking for options that are able to scale the original request, but do not conflict with it at the logical level.

Uploading and studying the semantics of competitors

One of the final chords of core scaling is unloading competitor sites and studying their semantics. This stage should not be ignored, because, often, the resources of competitors from the TOP of search results have a complete list of keyword occurrences. Including those that you might have missed.

For these purposes, we use the paid Serpstat service. It has the most convenient interface and a suitable set of tools for working with the semantics of competitors.

An example of the uploaded semantics by which the site is ranked:

All information can be saved as an Excel spreadsheet, where you can continue working more comfortably.

Query Clustering

Once marker queries have been collected and scaled using search suggestions and competitor semantics, it’s time to cluster them. If you do not ignore the stage of selecting markers, then the process of distributing them into groups will be quite simple.

The easiest way to do clustering is to create a project in Excel and sort using filters. It’s best to even have separate tabs, especially for those groups that might have the same secondary keys (like bike brands). This will greatly facilitate the work with the filter.

One of the most important tasks of clustering is to combine queries according to the logical component, and not just the semantic one.

During clustering, it is useful to immediately determine the type of each individual request. If necessary, you can separate all info-keys and aggregators into separate tabs.

let’s sum it up

The selection of semantics is the stage of work in which you should invest your soul, like nothing else. The information that we get at the output is the most important source of data that can be used to solve completely different problems.

The process of collecting information should not be completely trusted by automated services; at least a manual control check is required.

In complex niches, it is not a sin to resort to regular consultations with customers, especially if the latter are well versed in the issue.

Work hard, gain experience and share it!

Olha Tyshchenko

Editor

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