•Google makes 400 updates to its algorithm each year, so even if there isn’t a widely-publicized released update with a catchy name, Google is constantly tailoring.
•There were over three years between the “Big Daddy” update (2006) and “Caffeine” (2009). Before that there were many major updates on a yearly basis. 2003 saw four separate ones, while there were two each in 2004, 5, and 6
•There were over three years between the “Big Daddy” update (2006) and “Caffeine” (2009). Before that there were many major updates on a yearly basis. 2003 saw four separate ones, while there were two each in 2004, 5, and 6
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Boston Update (March 2003) – The Boston update focused on incoming links and unique content. The result was that many webmasters reported a drop in backlinks and a corresponding drop in PageRank.
Cassandra Update (April 2003) – This update focused on domain name relevance. The idea was that companies should choose a name that reflects their domain name.
Dominic Update (May 2003) – This update was named after the pizza restaurant in Boston that was visited often by PubCon attendees. The update focused on making the search process theme based, and linking a data center to a particular search. The update made it clear that each data center was meant to do different things.
Esmerelda Update (June 2003) – The third in a series of updates that gave preference to pages that gave more specific information to a visitor. The update revealed that internal pages within a website may have better relevance for the Dominic update, which seemed to give the homepage preference to even searches that were aimed at a specific query. Users reported that spam was considerably less than after the Dominic and Cassandra updates.
Florida Update (November 2003) – The update reflected Google’s shift from simple filters to an attempt to understand contextually the scope of the search and potential search results. The update cleaned up spam with simple linking and other features that gave more weight to well optimized and cleanly linked sites. Webmasters welcomed the update and it showed that Google was giving top priority to the searchers’ interests. The update was an attempt to encourage white hat websites, which adhered to the quality requirements.
Austin Update (January 2004) – The update focused on a practice called Google Bombing, where people manipulated the system to produce misleading results. The focus shifted to sites with minimal keyword density and good internal linking. Relevant links were given more weight in that sites that linked to other sites in a similar industry did better in the search results.
Brandy Update (February 2004) – Google placed more emphasis on words like trust, authority and reputation. Update showed that providing relevant information is the key. There was greater importance placed on the quality of content on a website. Google also stressed the importance of Latent Semantic Indexing.
Allegra Update (February 2005) – This was an attempt by Google to identify spam sites that still managed to rank high in the search results. Google asked users to give feedback about sites that actually deserved higher rankings but did not receive them. Users complained that their sites disappeared from the search results and that some spam sites still ranked well.
Bourbon Update (May 2005) – Google launched this update in response to spam complaints and re-inclusion requests. Strategic changes in the process were implemented to make it more effective. The update also focused on moving from old data centers to new ones.
Jagger Update (October / November 2005) – Google encouraged users to give feedback concerning websites that used black hat SEO strategies to rank well. Sites which were found to be using such techniques were removed from the search results. Google cleaned up canonical problems and focused on relevance in reciprocal linking.
Big Daddy (February 2006) – Google focused on inbound and outbound links. Sites that have very low trust in links, or linked out to many spam sites saw pages disappear from the index. Spam sites were moved into a supplemental category in the search results. Users noticed that even after complying with Google’s “help” that their websites were still going “supplemental.”
Pluto Update (August 2006) – Update focused on backlinks reported by Google. There were no significant changes in search engine results.
Caffeine Update (August 2009) – Update focused on infrastructure to allow Google to better index information online, and do it much faster. It enabled deeper processing, which allowed Google to deliver more relevant search results. This update eventually allowed Google to introduce page speed as a ranking factor.
Mayday Update (May 2010) – Google launched update that focused on long tail traffic.
Panda Update (February 2011) – Google cracked down on content farms and sites that had low quality, thin or scraped content. Focus was placed on unique content and content depth. Many websites were affected by the update. Most content farms got hit hard. The Panda update has been rolled out in several steps throughout the year.
Major updates from Google were typically focused on improving search results and the ability to index information on the Internet. Google has also launched updates to give more information to users and improve the overall experience. These updates include:
Universal Search (May 2007) – Universal Search ranked images, videos, news websites and other results into the same search results pages. The feature allowed people to search everything on a specific topic.
Real-Time Search (December 2009) – Google incorporated information from sources like Twitter, Facebook and blogs into its search results, giving users the ability to find the most recent information on trends about a certain topic.
Google Instant (September 2010) – Google Instant took what users typed and completed it with the most likely string of words. The result was a smarter, faster search engine that was interactive, predictive and powerful.
Google Places (October 2010) – Places were Google’s new local search results that organized information based on location. The results allowed users to easily decide where to go.
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