Users also often search for summer men's sneakers

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e. cluster them. Based on this, create an effective site structure that will fully meet the requirements of search engines and users. After collecting a complete semantic core in your niche, we divide it into clusters based on the level of coincidence of certain conditions, similarity in the meaning of words.



For a large semantic core, various clusterizers are used, for example, Serpstat , Cluster Army , Umbrella , but it can also be done "by hand". For example, for Indonesia Phone Number List the query "men's sneakers", we see that users often search for men's winter sneakers: we see that users are often looking for winter men's sneakers Looking at our semantic core, we can see that users are also frequently searching for men's summer sneakers: 



There is also an inquiry about autumn men's sneakers: autumn men's sneakers Let's see the number of inquiries about spring men's sneakers: spring men's sneakers And we also pay attention to inquiries about demi-season men's sneakers: inquiries about demi-season men's sneakers Based on the received data, we can form a category structure for the site of men's sneakers: winter, summer, autumn, spring, demi-season.