Behind every search query there is an intention, and the better the intention is understood, the better the search query can be answered and a separate page can be optimized for it. That is not always possible, because language is often ambiguous, and from a search query of few words or even only one word it is not always clear what exactly is meant. If you are looking for “credit”, you may need a consumer loan, but you may also need a real estate loan. It is even more difficult with so-called hompgraphs, words that are written in the same way but have different meanings. “Apache” is a tank, an Indian or even a web server. By the way, new search queries are entered into Google every day, search queries that Google has never seen before.
In the past, if users often entered only one keyword, the average number of words entered per search grew over time as users started using search engines. Of course, this doesn’t mean that there aren’t still one-word searches, quite the opposite. However, the proportion of search queries that consist of more than one word has increased. Some patterns, on the other hand, have remained the same, so only a fraction of users (well below 1 percent) use advanced search or use Boolean operators.
The different intentions on a topic will later be used to create keyword clusters. So visitors of a website can have the intention to apply for a job at the company or to inform themselves about a product of the company. If a user only searches for the name of the company, neither of the two intentions can be clearly identified.
Intentions play a role not only in search queries, but also in voice UIs and AI applications. If a linguistic utterance is made, a program must identify the intention behind the linguistic utterance. In this respect, search engines and the new generation of bots are not so far apart.
Next section: Head- and Long-Tail-Keywords