Time gain therefore partly depends on the clustering quality. It makes little sense if you spend hours correcting clusters yourself. Time savings and flexibility are therefore not an automatic condition for using a tool. What does automatic keyword clustering Slovenia Phone Numberis good enough? Clusters are data-driven and based on assumptions or instinctive clustering It eliminates errors in clustering, especially if a tool is not language dependent You have a set of clusters and subclusters. In minutes You maximize the number of keywords to rank for No more irrelevant Slovenia Phone Number cluster. Direct insight into user intentions for both individual search terms and (sub)clusters Immediate insight into the visibility.

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Of your domain for both keywords and (sub)clusters Is Slovenia Phone Number always better? This need not be the case. Are you working on a keyword analysis with 200 keywords? Then manual clustering is a good alternative. Although in practice the number of keywords is usually in the thousands for SEO marketers working at SMEs and large companies. It is precisely Slovenia Phone Number at these companies that the existing work processes and the set of SEO tools determine to what extent a new tool is adopted. Companies already work with existing templates in Google Sheets, dashboards and Excel documents for processes such as keyword analysis and content planning. In some cases even with proprietary software.

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A switch to a different or additional method and tool is then not Slovenia Phone Number desirable in all cases. Also, automation does not immediately replace analysis. Automatic clustering ensures that you have more time for gathering insights, drawing up Slovenia Phone Number actions and formulating strategy. Pressing the button, leaning back and waiting: of course that also does not work. Automation boosts your productivity, it doesn’t replace activity. Want to get started with a tool yourself? The following questions will help you determine whether a tool or service that offers automatic clustering is of sufficient quality.

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