Jul 16, 2022
In General Discussion
Nayak, Google, 2021 According to Google, search engines buy email database are not yet able to solve very complex searches in one go. Often the models do not 'understand' the context or user needs behind a search query. This results buy email database in multiple searches before the user need is met. “ People issue eight queries on average for complex tasks ….” ( Nayak, Google, 2021 ) With MUM, Google comes closer to providing buy email database immediate answers to complex issues. For example, consider the “next query you're going to type in”. Google actually wants buy email database to show the answer to your 3rd question with your first search. Latent needs thus become even more apparent, already during the user's search. It is therefore essential for Google's models to understand what buy email database someone's intention is. And which keywords have the same intention and information needs. Why is semantic keyword clustering relevant? Two (or more) apparently unrelated buy email database searches can therefore respond to the same information need and intention of the searcher. How does this work in practice? Take the buy email database following example: Searches 1 and 2 “Arabica coffee beans” “Robusta coffee beans” At first glance, the keywords hide the following intentions and information needs. Informative buy email database intent : information about what Arabica / Robusta coffee beans are (and where you can possibly buy it) Commercial / transactional intent : Chances are that Google Ads and Shopping campaigns will be shown If you were to manually group these keywords just by syntax or underlying buy email database meaning, a possible cluster name could be "types of coffee beans".