Semantic search is a method by which the algorithms of search engines such as Google can draw conclusions about the user’s intentions or objectives. To do this, they place the components of the query in context with one another and analyze the relationships between words, parts of sentences and, if necessary, entire sentences. In this way, the user ideally finds what he was looking for more quickly.
To understand what Semantic Search is exactly, it is best to look at it in comparison to “regular” search. In the latter, search engine algorithms crawl a website for specific keywords. Among other things, depending on how often a certain keyword is present, the website is assigned a certain relevance to a certain search term. This type of search is therefore primarily oriented towards the website, the user’s intention is largely left out of the equation.
The great advantage of this method is that Google and Co. have comparatively little effort with the search algorithms. Since each search term “only” has to be set in relation to certain keywords, such algorithms are quite easy to develop. The disadvantage, however, is that the search can hardly be personalized – if a user from Berlin enters the search term “Bayern München”, he will receive the same SERP (Search Engine Result Page) as a user from Hamburg. Whether the user was looking for sightseeing tips for Munich, a map for the next match of the soccer club or a route description to the Bavarian capital, the engine cannot recognize.
Of course, Semantic Search is also not a crystal ball that can magically recognize exactly what the user is looking for. But by correctly evaluating the search term, Semantic Search is much more likely to give the user the information he wanted. If we take the example from above a step further, the order of the words – first “Bayern” and then “München” – would indicate that the user is looking for information about a soccer club.
In principle, Semantic Search works better the longer the user’s search query is, because more words mean more information that can be put in relation to each other. In the case of a query such as “Germany”, even Semantic Search is largely powerless, because it is hardly possible to draw any closer conclusions about the user’s intention on the basis of a single word. In such a case, a search engine like Google will usually present general information about the search term. If, on the other hand, the search query were “Eiffel Tower how high”, Semantic Search would easily be able to identify the user’s request. In addition, Semantic Search can “iron out” typos and spelling errors.
The Semantic Search is therefore able to deliver suitable results or the searched content much faster, especially for more complex queries.
Semantic Search at Google
As the top dog among search engines, Google naturally also has a special role to play when it comes to semantic search. Google introduced the first algorithms for semantic search in 2013 with the Hummingbird update. This was followed in 2015 by RankBrain, a further improvement of Semantic Search. The basic principle is unchanged in RankBrain compared to semantic search. It attempts to establish relationships between words and groups of words. In addition, however, this algorithm can also infer the meaning of unknown words. This makes RankBrain a kind of “Semantic Search 2.0” – and Google is obviously very well positioned in this area.
However, it is difficult to make absolute statements about this or about how Google compares to the competition. Although Google was unusually open with RankBrain, the exact functioning of the algorithms and the decisive search criteria have remained a secret both with RankBrain and the Hummingbird update.
Semantic Search and SEO
If the criteria for the composition of the SERPs are changed, this is of course also important for search engine optimization. After all, the aim here is to design a page in such a way that users find it as well as possible via Google and Co.
If the rules according to which a website is evaluated change, this not only makes experts sit up and take notice. However, the extent to which semantic search is already having an impact on classic SEO and online marketing measures is a matter of some dispute among experts. Admittedly, there is no question that the methods will have to be changed. However, many experts assume that the development in the field of Semantic Search is so slow that there is enough time to adapt the SEO measures that have been effective so far. Moreover, Semantic Search has not yet displaced normal keyword search – and the latter is ideally suited for many SEO measures, as it normally always provides different users with the same results for a given query. This significantly reduces the effort required for search engine optimization.
However, there are also voices that are already advocating a stronger focus of SEO on semantic search. For these experts, semantic search is the future of Google and Co. – and this future has already begun with Hummingbird, RankBrain and similar algorithms. Accordingly, they consider it necessary to develop new strategies as soon as possible, with which content and websites also land on the top positions of the SERP in a semantic search.
However, regardless of the importance of semantic search, there are many other ways to do SEO that work for both semantic and keyword search. These include, for example, optimizing the website structure, navigation and loading times. In addition, the ranking of a website can probably also be positively influenced via backlinks and activities on social media channels.
Particular importance is attached to high-quality content, which Google and other search engines are also increasingly able to evaluate. If a website has a high level of information content and an equally high level of relevance to the topic being discussed, it will perform well in both semantic and keyword searches. The reason for this is as simple as it is obvious: the keywords used ensure that the page ranks in keyword searches, while the content offers a broad field of information that will answer many of a user’s questions about the page’s topic. So the adage often quoted in online marketing, “content is king,” will continue to apply in Semantic Search.
Semantic search is a promising basis for the further development of search engines. By analyzing the search query, the engine can draw conclusions and thus provide the user with the content he is looking for more quickly. At the moment, this method is still in its infancy, but it will become increasingly important for Google and Co. – and thus also for online marketing and search engine optimization. There are already some optimization methods that are still effective in a semantic search – content in particular plays an important role here – but SEO experts will have to develop new approaches for the future. Because this is the only way that companies will continue to be able to actively influence the positioning of their websites within the SERPs in the future.
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