One of the main ways in which the Hummingbird update helps improve the relevance of search results for long-tail keywords is by taking into account the overall context and meaning of the search query. This is achieved through the use of natural language processing, which allows Google to understand the intent behind a search query and return results that are more closely aligned with what the user is looking for.
For example, consider a search query such as "best restaurants in New York City with outdoor seating." Prior to the Hummingbird update, Google's search algorithm might have returned results based on the individual words in the query, rather than the overall context. This could have resulted in a mix of results that included restaurants with outdoor seating, as well as other types of businesses or websites that simply happened to include the words "best," "restaurants," "New York City," and "outdoor seating."
With the Hummingbird update, however, Google is able to understand that the user is looking for specific types of restaurants in a specific location, with a specific feature (outdoor seating). This allows the search algorithm to return more relevant results, such as a list of top-rated restaurants in New York City that offer outdoor seating.
Another way in which the Hummingbird update helps improve the relevance of search results for long-tail keywords is through the use of "semantic search." Semantic search refers to the ability of a search engine to understand the meaning and relationships between words and concepts, rather than simply matching words within a query to words on a webpage.
For example, consider a search query such as "What is the capital of France?" Prior to the Hummingbird update, Google's search algorithm might have returned results based on the individual words in the query, such as websites that included the words "capital" and "France." However, with semantic search, Google is able to understand that the user is looking for the specific name of the capital city of France, rather than general information about capitals or France. This allows the search algorithm to return more relevant results, such as a list of websites that specifically mention the capital city of France as "Paris."
Overall, the Hummingbird update has helped improve the relevance of search results for long-tail keywords by taking into account the overall context and meaning of the search query, as well as the relationships between words and concepts. This has allowed Google to return more relevant and accurate results to users, particularly for long-tail keywords that are more specific and less commonly searched for.
While the Hummingbird update has certainly made a significant impact on the relevance of search results for long-tail keywords, it is important to note that Google's search algorithm is constantly evolving and improving. As such, it is likely that future updates will continue to refine and improve the relevance of search results for long-tail keywords, as well as other types of queries. So, it can be said that the Hummingbird update has helped improve the relevance of search results for long-tail keywords, but it is not the only factor in determining the relevance of search results.