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For a competent, flexible and reliable online marketing agency? We look forward to your non-binding inquiry. Contact us And search engines use this fact that certain word fields have to do with each other in their algorithms. So, that means they know that the word repayment rate appears very often in a word about real estate financing. However, it doesn't occur that often in general usage, which is why you can practically understand it with this inverse document frequency. There are tools that automatically evaluate these keywords.

Which means that you enter your keyword on the topic of real estate financing, for example, and you Special Data automatically get a list of specific terms that appear in various constellations on websites about the topic. And to explain that now would go completely beyond the scope. The question is: Does something like this even make sense to use WDF*IDF? Now there are two types. how can I use these tools? One is slavish and if it says “Use the word repayment rate three times.”, then I use the word repayment rate three times here, here, and here and so on. And I basically squeeze my text into this scheme. And the second way is to see the whole thing more as an indication and to approach it with your head.



I prefer the second type and would say “Well, you should definitely use a tool like this to look at what could actually appear in a text on the topic.” Simply to get ideas about what might be missing, thematically. But I wouldn't advise you to do the whole thing slavishly. There are some people, don't get me wrong, who do it excellently, but there are probably / I can count them on these two hands in Germany. It actually only works for information-oriented search queries, where the algorithm also pays close attention to text. That means buying shoes etc. is a rather difficult topic.