How To Increase The Text Relevance Of Site Pages: Serpstat Text Analytics Tool

Text analytics is linked to the clustering tool that serves for the selection of keywords that you can place on one page. Text analytics is intended for their analysis. Clustering not only breaks keywords into groups but also selects a page (URL) of a domain for a particular cluster, to use text analytics on it later.

Before considering how to work with Text Analytics, you need to understand how to set up the tool. As I wrote above, Clustering and Text Analytics are two mutually reinforcing on page SEO analysis tools. Therefore, to begin analyzing the texts on the page, you must first cluster the queries. Read more about how to do this.

As a result of the clustering, we get a set of ready semantics for individual URLs. You can also edit groups of keywords manually, delete, move or add phrases. To do this, click on the icon in the upper right corner of the cluster.

When the cluster is ready, you can start conducting Text Analytics. To do this, press the TA button in the upper right corner.

Text analytics is carried out based on the:

That is, if you specify a target URL, Serpstat will analyze the page content and give recommendations on the use of keywords, based on the content of top competitors.

To set a landing page for a cluster, click Add URL in the upper left corner.

If the target URL was not specified, the recommendations of the service would be based on the analysis of a group of competitors from the top 15 by phrase. However, some reports, for example, Body Text will not be available.

It is not necessary that the page contains all the words from the key phrase for the page to rank by it. It is vital to ensure that the words from the query are included in the page content. For example, a user enters the search query buy Acer 310x laptop into a search engine. We have a page on our site where we sell such laptop.

For a search engine, it is not necessary that the page has this exact wording. The search engine understands that if our page is called Acer 310x laptop, or even Acer 310x, and there is a Buy button on it, then this page is relevant to the user's request.

Keyword relevance column shows how each of these phrases corresponds to the page.

There are two main indicators:

But the first question that arises: is the indicator that we get good or bad? To do this, we derive a scale where we show the relevance, based on the competitor analysis. This is the average value indicated by the green area.

If we approach the minimum value, it means that the words from the query are too far apart in the text on the page, or are seldom used.

If we see that the indicator is approaching the maximum, then this indicates spam. You can remove some of the repeated words, or distribute them less often in the text.

It is important to pay attention, which words are most significant for the topic to rank better. Then include them in the Title and H1, as these tags directly affect whether the page will be ranked by the desired requests.

Words in Text Analytics are arranged in order of importance for the topic. The best option would be to add them exactly in the same order that Serpstat offers. However, we should not forget about the logic: the contents of the Title should be clear and readable. We take into account that Title is limited in the number of words and symbols, therefore we try to add the most important keywords in the visible part — the first 60 characters.

The same goes with the recommendations for H1.

Also, at the very bottom of the report, you'll see a summary of the errors on the page and recommendations for correcting them. These issues can negatively affect both textual relevance and ranking in general. If you want to improve the position of the page, mind their early correction.

Besides the fact that Serpstat has a lot of reports to select and expand the semantics, Text Analytics is an excellent tool for this. It shows ready-made recommendations for words that should be included in the text. Thus, we increase the number of all keywords for which a user can find your site.

I have already described the basic variants of using Text Analytics reports to increase the text relevance of site pages. But what if there is no text yet? Write! And write well.

To give a good reference to a copywriter, you can also use Text Analytics. To do this, you need to collect data from the reports Title, H1, Body, which I mentioned in the previous two paragraphs.

The Body Text report will also be useful: you will see text analysis on a given page (works only if you set the URL).

The Serpstat algorithm gives recommendations for reducing or increasing the amount of text. This is an important ranking factor, so its volume should be optimal to avoid low relevance or spam, and to add keywords to the content organically.

Use Text Analytics data to make up the technical assignment to the copywriter. Specify:

I remind you that Serpstat Text Analytics works on unique algorithms that select only keywords relevant to the topic. This allows you to automate the work of SEO-specialists when working with keywords.