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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 (such as keywords, a business category, or the name of a consumer product) 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. [1] 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.
Local searches on Google Search typically return organic results prefaced with a 'local 3-pack', a list of three local results. More local results can be obtained by clicking on “more places” under the 3-pack. The list of results one obtains is also called the Local Finder. [2]
Search engines and directories are primarily supported by advertising from businesses that wish to be prominently featured when users search for specific products and services in specific locations. Google for instance, has developed local inventory ads and features ads in the local pack. [3] Local search advertising can be highly effective because it allows ads to be targeted very precisely to the search terms and location provided by the user.
Local search is the natural evolution of traditional offline advertising, typically distributed by newspaper publishers and TV and radio broadcasters, to the Web. Historically, consumers relied on local newspapers and local TV and radio stations to find local products and services. With the advent of the Web, consumers are increasingly using search engines to find these local products and services online. In recent years, the number of local searches online has grown rapidly while off-line information searches, such as print Yellow Page lookups, have declined. [4] As a natural consequence of this shift in consumer behavior, local product, and service providers are slowly shifting their advertising investments from traditional off-line media to local search engines.
One can search for local information via search engines. These often return local search results from directories [5] and maps. Google for instance, will present results from its directory (called Google Business Profile) in Google Maps and also in the search engine results pages [6] in the form of a local pack. One can also look for local information by searching Apple Maps [7] Search engines offer local businesses the possibility to upload their business data to their respective local search databases. [8]
Other local search engines adjunct to major web search portals include general Windows Live Local, Yahoo! Local, and ask.com's AskCity. Yahoo!, for example, separates its local search engine features into Yahoo! Local and Yahoo! Maps, the former being focused on business data and correlating it with web data, the latter focused primarily on the map features (e.g. directions, larger map, navigation).
Local search, like ordinary search, can be applied in two ways. As John Battelle coined it in his book "The Search," search can be either recovery search or discovery search.
This perfect search also has perfect recall – it knows what you’ve seen, and can discern between a journey of discovery – where you want to find something new – and recovery – where you want to find something you’ve seen before.
This applies especially to local searches. Recovery search implies, for example, that a consumer knows who she is looking for (i.e., Main Street Pizza Parlor) but she does not know where they are, or needs their phone number. Discovery search implies that the searcher knows, for example, what she wants but not who she needs it from (i.e., pizza on Main Street in Springfield).
In February 2012, Google announced that they made 40 changes to their search algorithm, including one codenamed "Venice" which Google states will improve local search results by "relying more on the ranking of (Google's) main search results as a signal", [9] meaning local search will now rely more on organic SERPs (Search Engine Result Pages).
Google can show a business's information in mobile or desktop google search results, or/and in mobile and desktop google maps results. [10] Local search results displayed by google often include a local pack, that currently displays three listings. [11]
Major search engines have algorithms that determine which local businesses rank in local search. Primary factors that impact a local business's chance of appearing in local search are proper categorization in business directories, a business's name, address, and phone number (NAP) being crawlable on the website, and citations (mentions of the small business on other relevant websites like a chamber of commerce website). [12]
In 2016, a study [13] using statistical analysis assessed how and why businesses ranked in the local packs and identified positive correlations between local rankings and 100+ ranking factors. Although the study can’t replicate Google’s algorithm, it did deliver several interesting findings:
On December 2021's Vicinity Update[ citation needed ], Google announced on Twitter announced that it had updated its local search algorithm which "involved a rebalancing of various factors we consider in generating local search results." [14] It placed more importance on proximity as a ranking factor and decreased the significance of adding keywords in a business name on Google Business Profile.[ citation needed ]
Traditional local media companies, including newspaper publishers and television and radio broadcasters, are starting to add local search to their local websites to attract their share of local search traffic and advertising revenues in the markets they serve. These local media companies either develop their own technology or license "private label" or "white label" local search solutions from third-party local search solution providers. In either case, local media companies base their solution on business listing databases developed in-house or licensed from a third-party data publisher.
Local search that incorporates internal or external social signals could be considered social local search-driven. The first site to incorporate this type of search was Explore To Yellow Pages. Explore To uses Facebook Likes as one of the signals to increase the ranking of listings where other factors may be equal or almost equal. Typical ranking signals in local searches, such as keyword relevancy and distance from centroid can, therefore, be layered with these social signals to give a better crowdsourced experience for users. More recently, social media sites Facebook, Foursquare, LocalMate and Zappenin have become more directly involved in local search by updating their mobile apps with features to help people discover new businesses to visit.
Several providers experimented with providing local search for mobile devices, but on March 5, 2020, Google was the first to announce mobile-first indexing by default shifting the focus of optimization from desktop to mobile. [15] Some of these are location aware. In the United States, Google previously operated an experimental voice-based locative service (1-800-GOOG-411) but terminated the service in November, 2010. Many mobile web portals require the subscriber to download a small Java application, however, the recently added .mobi top-level domain has given impetus to the development of mobile-targeted search sites are based upon a standard mobile-specific XML protocol that all modern mobile browsers understand. The advantage of mobile responsive website development is that no software needs to be downloaded and installed, plus these sites may be designed to simultaneously provide conventional content to traditional PC users using automatic browser detection.
Electronic publishers (such as businesses or individuals) who would like information such as their name, address, phone number, website, business description and business hours to appear on local search engines have several options. The most reliable way to include accurate local business information is to start claiming business listings through Google's, Yahoo!'s, or Bings's respective local business centers.
Business listing information can also be distributed via the traditional Yellow Pages, electronic Yellow Page-style data aggregators, and search engine optimization services. Some search engines will pick up on web pages that contain regular street addresses displayed in machine-readable text (rather than a picture of text, which is more difficult to interpret). Web pages can also use geotagging techniques.
On May 30, 2012 Google launched Google+ Local, a simple way to discover and share local information featuring Zagat scores and recommendations from the people you trust on Google+. [16]
On June 11, 2014 Google launched Google Business Profile [17] [18] [19] which replaced Google+ Local. Google Business Profile has more features and connects with AdWords to make an all-in-one small business online management center.
Reviews on Google Business Profile can be written by anyone regardless of whether they have actually had experience with the business. It's not uncommon for less honorable "reputation management" companies to post fraudulent negative reviews and then call the business offering to remove the fake reviews for a fee. Google has a posted policy that states all reviews "should accurately represent the location in question. Where contributions distort the truth, we will remove content." In reality, the Google Business Profile support staff almost never removes fraudulent reviews and appears to be more interested in encouraging business owners to spend money on Adwords than in actually ensuring the accuracy of the Google Business Profile information.
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.
Spamdexing is the deliberate manipulation of search engine indexes. It involves a number of methods, such as link building and repeating related and/or unrelated phrases, to manipulate the relevance or prominence of resources indexed in a manner inconsistent with the purpose of the indexing system.
Search engine optimization (SEO) is the process of improving the quality and quantity of website traffic to a website or a web page from search engines. SEO targets unpaid traffic rather than direct traffic or paid traffic. Unpaid traffic may originate from different kinds of searches, including image search, video search, academic search, news search, and industry-specific vertical search engines.
Relative to some web resource, a backlink is a link from some other website to that web resource. A web resource may be a website, web page, or web directory.
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.
Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines. Released in beta in November 2004, the Google Scholar index includes peer-reviewed online academic journals and books, conference papers, theses and dissertations, preprints, abstracts, technical reports, and other scholarly literature, including court opinions and patents.
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.
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 is a software system that provides hyperlinks to web pages and other relevant information on the Web in response to a user's query. The user inputs a query within a web browser or a mobile app, and the search results are often a list of hyperlinks, accompanied by textual summaries and images. Users also have the option of limiting the search to a specific type of results, such as images, videos, or news.
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 Personalized Search is a personalized search feature of Google Search, introduced in 2004. All searches on Google Search are associated with a browser cookie record. When a user performs a search, the search results are not only based on the relevance of each web page to the search term, but also on which websites the user visited through previous search results. This provides a more personalized experience that can increase the relevance of the search results for the particular user. Such filtering may also have side effects, such as the creation of a filter bubble.
Facebook Graph Search was a semantic search engine that Facebook introduced in March 2013. It was designed to give answers to user natural language queries rather than a list of links. The name refers to the social graph nature of Facebook, which maps the relationships among users. The Graph Search feature combined the big data acquired from its over one billion users and external data into a search engine providing user-specific search results. In a presentation headed by Facebook CEO Mark Zuckerberg, it was announced that the Graph Search algorithm finds information from within a user's network of friends. Microsoft's Bing search engine provided additional results. In July it was made available to all users using the U.S. English version of Facebook. After being made less publicly visible starting December 2014, the original Graph Search was almost entirely deprecated in June 2019.
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.
Google Search, offered by Google, is the most widely used search engine on the World Wide Web as of 2023, with over eight billion searches a day. This page covers key events in the history of Google's search service.
Google Pigeon is the code name given to one of Google's local search algorithm updates. This update was released on July 24, 2014. It is aimed to increase the ranking of local listings in a search.
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.
The domain authority of a website describes its relevance for a specific subject area or industry. Domain Authority is a search engine ranking score developed by Moz. This relevance has a direct impact on its ranking by search engines, trying to assess domain authority through automated analytic algorithms. The relevance of domain authority on website-listing in the Search Engine Results Page (SERPs) of search engines led to the birth of a whole industry of Black-Hat SEO providers, trying to feign an increased level of domain authority. The ranking by major search engines, e.g., Google’s PageRank is agnostic of specific industry or subject areas and assesses a website in the context of the totality of websites on the Internet. The results on the SERP page set the PageRank in the context of a specific keyword. In a less competitive subject area, even websites with a low PageRank can achieve high visibility in search engines, as the highest ranked sites that match specific search words are positioned on the first positions in the SERPs.
User intent, otherwise known as query intent or search intent, is the identification and categorization of what a user online intended or wanted to find when they typed their search terms into an online web search engine for the purpose of search engine optimisation or conversion rate optimisation. Examples of user intent are fact-checking, comparison shopping or navigating to other websites.
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.
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