No, this is great. But what will usually happen is that we will discover that although. We rank for these keywords, we do not do so options. Or that we rank correctly for the main keyword. F but not for the other keywords. In that case, we can create new pages that focus on the secondary keywords and correct the content of the one that was already ranking so that it focuses only on one of those terms.
1.3 Fragmentation
Fragmentation can be done in content and pages with a lot of information, where it also happens that the content is divid into blocks or does not give us the possibility of creating separations into different topics.
The technique is conceptually very simple
But technically it can pose a challenge in some scenarios. It is bas on transforming a URL into several, fragmenting the original content into several pieces and assigning each fragment to a different URL. URL to be left with only the most important linkedIn data content and to lead each separate fragment to new URLs (with new keywords). We will thus gain more URLs and keywords on our site , but (and this is important) in exchange for removing content from our URLs.
Of course, the content and authority of the page must accompany this:
The first is because it must. A allow this separation and have sufficient text volume so that no fragment can be consider thin content (empty or irrelevant content).
Authority, because when losing content, it will be necessary. S to continue positioning the original URL and it will also have. S to transmit it to the new the influence of ai on content also URLs with the text fragments extract to position them.
A classic practical example would be content divid into tabs
She user sees a piece of content and, by clicking on the tabs. S can view other parts of the content that are hidden on initial loading. In this scenario, what tg data prevents you from making each tab a different URL by betting on keywords in detail? Technically it is possible, but remember that each URL will have less content.