Hummingbird is the codename given to a significant algorithm change in Google Search in 2013. Its name was derived from the speed and accuracy of the hummingbird. The change was announced on September 26, 2013, having already been in use for a month. "Hummingbird" places greater emphasis on natural language queries, considering context and meaning over individual keywords. It also looks deeper at content on individual pages of a website, with improved ability to lead users directly to the most appropriate page rather than just a website's homepage.
The upgrade marked the most significant change to Google search in years, with more "human" search interactions and a much heavier focus on conversation and meaning. [1] Thus, web developers and writers were encouraged to optimize their sites with natural writing rather than forced keywords, and make effective use of technical web development for on-site navigation.
Google announced "Hummingbird", a new search algorithm, at a September 2013 press event, [2] having already used the algorithm for approximately one month prior to announcement. [3]
The "Hummingbird" update was the first major update to Google's search algorithm since the 2010 "Caffeine" search architecture upgrade, but even that was limited primarily to improving the indexing of information rather than sorting through information. [3] Amit Singhal, then-search chief at Google, told Search Engine Land that "Hummingbird" was the most dramatic change of the algorithm since 2001, when he first joined Google. [3] [4] Unlike previous search algorithms, which would focus on each individual word in the search query, "Hummingbird" considers the context of the different words together, with the goal that pages matching the meaning do better, rather than pages matching just a few words. [5] The name is derived from the speed and accuracy of the hummingbird. [5]
"Hummingbird" is aimed at making interactions more human, in the sense that the search engine is capable of understanding the concepts and relationships between keywords. [6] It places greater emphasis on page content, making search results more relevant, and looks at the authority of a page, and in some cases the page author, to determine the importance of a website. It uses this information to better lead users to a specific page on a website rather than the standard website homepage. [7]
Search engine optimization changed with the addition of "Hummingbird", with web developers and writers encouraged to use natural language when writing on their websites rather than using forced keywords. They were also advised to make effective use of technical website features, such as page linking, on-page elements including title tags, URL addresses and HTML tags, as well as writing high-quality, relevant content without duplication. [8] While keywords within the query still continue to be important, "Hummingbird" adds more strength to long-tailed keywords, effectively catering to the optimization of content rather than just keywords. [7] The use of synonyms has also been optimized; instead of listing results with exact phrases or keywords, Google shows more theme-related results. [9]
Google Search is a search engine operated by Google. It allows users to search for information on the Internet by entering keywords or phrases. Google Search uses algorithms to analyze and rank websites based on their relevance to the search query. It is the most popular search engine worldwide.
Meta elements are tags used in HTML and XHTML documents to provide structured metadata about a Web page. They are part of a web page's head
section. Multiple Meta elements with different attributes can be used on the same page. Meta elements can be used to specify page description, keywords and any other metadata not provided through the other head
elements and attributes.
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The anchor text, link label or link text is the visible, clickable text in an HTML hyperlink. The term "anchor" was used in older versions of the HTML specification for what is currently referred to as the a element, or <a>
. The HTML specification does not have a specific term for anchor text, but refers to it as "text that the a element wraps around". In XML terms, the anchor text is the content of the element, provided that the content is text.
Keyword stuffing is a search engine optimization (SEO) technique, considered webspam or spamdexing, in which keywords are loaded into a web page's meta tags, visible content, or backlink anchor text in an attempt to gain an unfair rank advantage in search engines. Keyword stuffing may lead to a website being temporarily or permanently banned or penalized on major search engines. The repetition of words in meta tags may explain why many search engines no longer use these tags. Nowadays, search engines focus more on the content that is unique, comprehensive, relevant, and helpful that overall makes the quality better which makes keyword stuffing useless, but it is still practiced by many webmasters.
Search engine marketing (SEM) is a form of Internet marketing that involves the promotion of websites by increasing their visibility in search engine results pages (SERPs) primarily through paid advertising. SEM may incorporate search engine optimization (SEO), which adjusts or rewrites website content and site architecture to achieve a higher ranking in search engine results pages to enhance pay per click (PPC) listings and increase the Call to action (CTA) on the website.
Local search is the use of specialized Internet search engines that allow users to submit geographically constrained searches against a structured database of local business listings. Typical local search queries include not only information about "what" the site visitor is searching for but also "where" information, such as a street address, city name, postal code, or geographic coordinates like latitude and longitude. Examples of local searches include "Hong Kong hotels", "Manhattan restaurants", and "Dublin car rental". Local searches exhibit explicit or implicit local intent. A search that includes a location modifier, such as "Bellevue, WA" or "14th arrondissement", is an explicit local search. A search that references a product or service that is typically consumed locally, such as "restaurant" or "nail salon", is an implicit local search.
The Sandbox effect is a theory about the way Google ranks web pages in its index. It is the subject of much debate—its existence has been written about since 2004, but not confirmed, with several statements to the contrary.
A search engine results page (SERP) is a webpage that is displayed by a search engine in response to a query by a user. The main component of a SERP is the listing of results that are returned by the search engine in response to a keyword query.
Google Images is a search engine owned by Google that allows users to search the World Wide Web for images. It was introduced on July 12, 2001, due to a demand for pictures of the green Versace dress of Jennifer Lopez worn in February 2000. In 2011, reverse image search functionality was added.
In Internet marketing, search advertising is a method of placing online advertisements on web pages that show results from search engine queries. Through the same search-engine advertising services, ads can also be placed on Web pages with other published content.
Keyword research is a practice search engine optimization (SEO) professionals use to find and analyze search terms that users enter into search engines when looking for products, services, or general information. Keywords are related to search queries.
In the field of search engine optimization (SEO), link building describes actions aimed at increasing the number and quality of inbound links to a webpage with the goal of increasing the search engine rankings of that page or website. Briefly, link building is the process of establishing relevant hyperlinks to a website from external sites. Link building can increase the number of high-quality links pointing to a website, in turn increasing the likelihood of the website ranking highly in search engine results. Link building is also a proven marketing tactic for increasing brand awareness.
Google's Google Panda is a major change to the company's search results ranking algorithm that was first released in February 2011. The change aimed to lower the rank of "low-quality sites" or "thin sites", in particular "content farms", and return higher-quality sites near the top of the search results.
Google Penguin was a codename for a Google algorithm update that was first announced on April 24, 2012. The update was aimed at decreasing search engine rankings of websites that violate Google's Webmaster Guidelines by using now declared Grey Hat SEM techniques involved in increasing artificially the ranking of a webpage by manipulating the number of links pointing to the page. Such tactics are commonly described as link schemes. According to Google's John Mueller, as of 2013, Google announced all updates to the Penguin filter to the public.
RankBrain is a machine learning-based search engine algorithm, the use of which was confirmed by Google on 26 October 2015. It helps Google to process search results and provide more relevant search results for users. In a 2015 interview, Google commented that RankBrain was the third most important factor in the ranking algorithm, after with links and content, out of about 200 ranking factors. whose exact functions in the Google algorithm are not fully disclosed. As of 2015, "RankBrain was used for less than 15% of queries." The results show that RankBrain guesses what the other parts of the Google search algorithm will pick as the top result 80% of the time, compared to 70% for human search engineers.
Keyword clustering is a practice search engine optimization (SEO) professionals use to segment target search terms into groups (clusters) relevant to each page of the website. After keyword research, search engine professionals cluster keywords into small groups which they spread across pages of the website to achieve higher rankings in the search engine results (SERP). Keyword clustering is a fully automated process performed by keyword clustering tools.
Local search engine optimization is similar to (national) SEO in that it is also a process affecting the visibility of a website or a web page in a web search engine's unpaid results often referred to as "natural", "organic", or "earned" results. In general, the higher ranked on the search results page and more frequently a site appears in the search results list, the more visitors it will receive from the search engine's users; these visitors can then be converted into customers. Local SEO, however, differs in that it is focused on optimizing a business's online presence so that its web pages will be displayed by search engines when users enter local searches for its products or services. Ranking for local search involves a similar process to general SEO but includes some specific elements to rank a business for local search.