Search engine optimization: Difference between revisions

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'''Search engine optimization''' ('''SEO''') is the process of improving the quality and quantity of [[Web traffic|website traffic]] to a [[website]] or a [[web page]] from [[web search engine|search engine]]s.<ref>{{Cite web|url=https://www.webopedia.com/TERM/S/SEO.html|title=SEO – search engine optimization|website=Webopedia|date=December 19, 2001|access-date=May 9, 2019|archive-date=May 9, 2019|archive-url=https://web.archive.org/web/20190509033028/https://www.webopedia.com/TERM/S/SEO.html|url-status=live}}</ref><ref>{{Cite journal |last1=Giomelakis |first1=Dimitrios |last2=Veglis |first2=Andreas |date=2016-04-02 |title=Investigating Search Engine Optimization Factors in Media Websites: The case of Greece |url=http://www.tandfonline.com/doi/full/10.1080/21670811.2015.1046992 |journal=Digital Journalism |language=en |volume=4 |issue=3 |pages=379–400 |doi=10.1080/21670811.2015.1046992 |s2cid=166902013 |issn=2167-0811 |access-date=October 30, 2022 |archive-date=October 30, 2022 |archive-url=https://web.archive.org/web/20221030054324/https://www.tandfonline.com/doi/full/10.1080/21670811.2015.1046992 |url-status=live |url-access=subscription }}</ref> SEO targets unpaid search traffic (usually referred to as "[[Organic search|organic]]" results) rather than direct traffic, referral traffic, [[social media]] traffic, or [[Online advertising|paid traffic]].

Organic search engine traffic originates from a variety of kinds of searches, including [[image search]], [[video search]], [[academic databases and search engines|academic search]],<ref name="aseo">{{cite web|url=https://web.archive.org/web/20110728010319/https://www.sciplore.org/publications/2010-ASEO--preprint.pdf|title=Academic Search Engine Optimization (ASEO): Optimizing Scholarly Literature for Google Scholar and Co.|last1=Beel|first1=Jöran|last2=Gipp|first2=Bela|last3=Wilde|first3=Erik|year=2010|publisher=Journal of Scholarly Publishing|pages=176–190|access-date=April 18, 2010|archive-date=November 18, 2017|archive-url=https://web.archive.org/web/20171118043054/https://www.sciplore.org/publications/2010-ASEO--preprint.pdf}}</ref> news search, industry-specific [[vertical search]] engines, and large language models.

As an [[Internet marketing]] strategy, SEO considers how search engines work, the [[algorithm]]s that dictate search engine results, what people search for, the actual search queries or [[Keyword research|keywords]] typed into search engines, and which search engines are preferred by a target audience. SEO helps websites attract more visitors from a search engine and rank higher within a [[search engine results page]] (SERP), aiming to either convert the visitors or build brand awareness.<ref>Ortiz-Cordova, A. and Jansen, B. J. (2012) [https://faculty.ist.psu.edu/jjansen/academic/jansen_high_revenue_customers_2012.pdf Classifying Web Search Queries in Order to Identify High Revenue Generating Customers]. {{Webarchive|url=https://web.archive.org/web/20160304203905/https://faculty.ist.psu.edu/jjansen/academic/jansen_high_revenue_customers_2012.pdf |date=March 4, 2016 }}. Journal of the American Society for Information Sciences and Technology. 63(7), 1426 – 1441.</ref>

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In 2015, it was reported that [[Google]] was developing and promoting mobile search as a key feature within future products. In response, many brands began to take a different approach to their Internet marketing strategies.<ref>{{Cite web |url=https://www.startupgrind.com/blog/mobile-is-the-internet-for-consumers/ |title="By the Data: For Consumers, Mobile is the Internet" ''Google for Entrepreneurs Startup Grind'' September 20, 2015. |access-date=January 8, 2016 |archive-date=January 6, 2016 |archive-url=https://web.archive.org/web/20160106040341/https://www.startupgrind.com/blog/mobile-is-the-internet-for-consumers/ |url-status=live }}</ref>

In the 2020s, the rise of generative AI tools such as [[ChatGPT]], Claude, Perplexity, and Gemini gave rise to discussion around a newconcept approachvariously calledreferred [[Generativeto as generative engine optimization, answer engine optimization]] or [[artificial intelligence optimization]]. This approach focuses on optimizing content for inclusion in AI-generated answers provided by [[large language models]] (LLMs). This shift has led digital marketers to rethinkdiscuss content formats, authority signals, and how structured data is presented to make content more "promptable".<ref>{{Cite web | title=What is generative engine optimization (GEO)? | url=https://searchengineland.com/what-is-generative-engine-optimization-geo-444418 | archive-url=https://web.archive.org/web/20240729150835/https://searchengineland.com/what-is-generative-engine-optimization-geo-444418 | access-date=2025-07-30 | archive-date=2024-07-29}}</ref> It has also been argued that each of these tactics should be considered as subsets of "search experience optimization," described by [[Ahrefs]] as "optimizing a brand’s presence for non-linear search journeys over multiple platforms, not just Google."<ref>{{cite web |last1=Gavoyannis |first1=Despina |title=SXO Explained: How to Adapt to the New Era of Search |url=https://ahrefs.com/blog/search-experience-optimization/ |website=Ahrefs}}</ref>

==Relationship between Google and SEO industry==

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In 2007, Google announced a campaign against paid links that transfer PageRank.<ref>{{cite web|url=https://www.searchenginejournal.com/8-things-we-learned-about-google-pagerank/5897/|title=8 Things We Learned About Google PageRank|date=October 25, 2007|publisher=www.searchenginejournal.com|access-date=August 17, 2009|archive-date=August 19, 2009|archive-url=https://web.archive.org/web/20090819080745/http://www.searchenginejournal.com/8-things-we-learned-about-google-pagerank/5897/|url-status=live}}</ref> On June 15, 2009, Google disclosed that they had taken measures to mitigate the effects of PageRank sculpting by use of the [[nofollow]] attribute on links. [[Matt Cutts]], a well-known software engineer at Google, announced that Google Bot would no longer treat any no follow links, in the same way, to prevent SEO service providers from using nofollow for PageRank sculpting.<ref>{{cite web|url=https://www.mattcutts.com/blog/pagerank-sculpting/|title=PageRank sculpting|publisher=Matt Cutts|access-date=January 12, 2010|archive-date=January 6, 2010|archive-url=https://web.archive.org/web/20100106120723/http://www.mattcutts.com/blog/pagerank-sculpting/|url-status=live}}</ref> As a result of this change, the usage of nofollow led to evaporation of PageRank. In order to avoid the above, SEO engineers developed alternative techniques that replace nofollowed tags with obfuscated [[JavaScript]] and thus permit PageRank sculpting. Additionally, several solutions have been suggested that include the usage of [[HTML element#Frames|iframe]]s, [[Flash animation|Flash]], and JavaScript.<ref>{{cite web |url=http://searchengineland.com/google-loses-backwards-compatibility-on-paid-link-blocking-pagerank-sculpting-20408 |title=Google Loses "Backwards Compatibility" On Paid Link Blocking & PageRank Sculpting |date=June 3, 2009 |publisher=searchengineland.com |access-date=August 17, 2009 |archive-date=August 14, 2009 |archive-url=https://web.archive.org/web/20090814212229/http://searchengineland.com/google-loses-backwards-compatibility-on-paid-link-blocking-pagerank-sculpting-20408/ |url-status=live }}</ref>

In December 2009, Google announced it would be using the web search history of all its users in order to populate search results.<ref>{{cite web|url=https://googleblog.blogspot.com/2009/12/personalized-search-for-everyone.html|title=Personalized Search for everyone|access-date=December 14, 2009|archive-date=December 8, 2009|archive-url=https://web.archive.org/web/20091208140917/http://googleblog.blogspot.com/2009/12/personalized-search-for-everyone.html|url-status=live}}</ref> On June 8, 2010 a new web indexing system called [[Google Caffeine]] was announced. Designed to allow users to find news results, forum posts, and other content much sooner after publishing than before, Google Caffeine was a change to the way Google updated its index in order to make things show up quicker on Google than before. According to Carrie Grimes, the software engineer who announced Caffeine for Google, "Caffeine provides 50 percent fresher results for web searches than our last index..."<ref>{{cite web |url=httphttps://googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html |title=Our new search index: Caffeine |publisher=Google: Official Blog |access-date=May 10, 2014 |archive-date=June 18, 2010 |archive-url=https://web.archive.org/web/20100618160021/http://googleblog.blogspot.com/2010/06/our-new-search-index-caffeine.html |url-status=live }}</ref> [[Google Instant]], real-time-search, was introduced in late 2010 in an attempt to make search results more timely and relevant. Historically site administrators have spent months or even years optimizing a website to increase search rankings. With the growth in popularity of social media sites and blogs, the leading engines made changes to their algorithms to allow fresh content to rank quickly within the search results.<ref>{{cite web |title=Relevance Meets Real-Time Web |publisher=[[Google Blog]] |url=httphttps://googleblog.blogspot.com/2009/12/relevance-meets-real-time-web.html |access-date=January 4, 2010 |archive-date=April 7, 2019 |archive-url=https://web.archive.org/web/20190407221454/http://googleblog.blogspot.com/2009/12/relevance-meets-real-time-web.html |url-status=live }}</ref>

Google has implemented numerous algorithm updates to improve search quality, including Panda (2011) for content quality, Penguin (2012) for link spam, Hummingbird (2013) for natural language processing, and BERT (2019) for query understanding. These updates reflect the ongoing evolution of search technology and Google's efforts to combat spam while improving user experience.

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* Russia: [[Yandex]] is the leading search engine in Russia. As of December 2023, it accounted for at least 63.8% of the market share.<ref>{{Cite web |title=Most popular search engines in Russia 2023 |url=https://www.statista.com/statistics/1094920/leading-search-engines-by-visits-share-russia/ |access-date=2025-01-06 |website=Statista |language=en}}</ref>

=== The evolution of internationalMultilingual SEO ===

By the early 2000s, businesses recognized that the web and search engines could help them reach global audiences. As a result, the need for multilingual SEO emerged.<ref>{{Cite journal |last1=Arora |first1=Sanjog |last2=Hemrajani |first2=Naveen |date=September 2023 |title=A REVIEW ON: MULTILINGUAL SEARCH TECHNIQUE |url=https://www.researchgate.net/publication/382274152 |journal=International Journal of Applied Engineering & Technology |volume=5 |issue=3 |pages=760–770 |via=ResearchGate}}</ref> In the early years of international SEO development, simple translation was seen as sufficient. However, over time, it became clear that localization and transcreation—adapting content to local language, culture, and emotional resonance—were far more effective than basic translation.<ref>{{Cite web |title=SEO Starter Guide: The Basics {{!}} Google Search Central {{!}} Documentation |url=https://developers.google.com/search/docs/fundamentals/seo-starter-guide |access-date=2025-01-13 |website=Google for Developers |language=en}}</ref>

== Legal precedents ==