Google Personalized Search

Personalized search feature of Google Search
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. On April 20, 2005, it was made available as a non beta service, but still separate from ordinary Google Search. On November 11, 2005, it became a part of the normal Google Search, but only to users with Google Accounts. Beginning on December 4, 2009, Personalized Search was applied to all users of Google Search, including those who are not logged into a Google Account. In addition to customizing results based on personal behavior and interests associated with a Google Account, Google also implemented social search results in October 2009 based on people whom one knows. Operating on the assumption that one's associates share similar interests, these results would give a ranking boost to sites from within a user's "Social Circle". These two services integrated into regular results by February 2011 and expanded results by including content shared to users known through social networks.

Google's search algorithm is driven by collecting and storing web history in its databases. For non authenticated users Google looks at anonymously stored browser cookies on a user's browser and compares the unique string with those stored within Google databases. Google accounts logged into Google Chrome use user's web history to learn what sites and content they like and base the search results presented on them. Using the data provided by the user Google constructs a profile including gender, age, languages, and interests based on prior behaviour using Google services. When a user performs a search using Google, the keywords or terms are used to generate ranked results based upon the PageRank algorithm. This algorithm, according to Google, is their "system of counting link votes and determining which pages are most important based upon them. These scores are then used along with many other things to determine if a page will rank well in a search." "PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at considerably more than the sheer volume of votes, or links a page receives; for example, it also analyzes the page that casts the vote. Votes cast by pages that are themselves "important" weigh more heavily and help to make other pages 'important.' Using these and other factors, Google provides its views on the pages' relative importance,"

Since the search division launched the very first version with customized search results in 2005 and began to give consideration to previously visited sites, new factors have been added to refine search results. According to Google, the conclusion they have made after many years of testing, the incomparably best indicator for deciding which results are relevant to the user is the search phrase itself not user data and that personalisation of search results is not as big a factor as it used to be. Harvard law professor Jonathan Zittrain disputed the extent to which personalization filters distort Google search results, saying that "the effects of search personalization have been light". Further, Google provides the ability for users to shut off personalization features if they choose, by deleting Google's record of their search history and setting Google to not remember their search keywords and visited links in the future.

Location data allows Google to provide information based upon current location and places that the user has visited in the past, based upon GPS location from an Android smartphone or the user's IP address. Google uses this location data to provide local listings grouped with search results using the Google Local platform featuring detailed reviews and ratings from Zagat.

Search history was first used to personalize search results in 2005 based upon previous searches and clicked links by individual end users. Then, in 2009, Google announced that personalized search would no longer require a user to be logged in, and instead Google would use an anonymous cookie in a web browser to customize search results for those who were not logged in. Personalization makes search experience inconsistent for different users requiring the SEO industry to be aware of both personalized and non personalized search results to get an increase in ranking. However, in recent years new research had stated that search engines do not create the kind of filter bubbles previously thought. In a study of the political impact of search engines in seven countries carried out at Michigan State University, researchers discovered that search engines were a complement to other news sources that people already used. Users checked out an average of 4.5 news sources across various media to obtain an understanding, and those with a specific interest in politics checked even more. The researchers note that filter bubbles sound like a real problem and that they primarily appear to apply to people other than yourself. Their conclusion is, nonetheless, that the problem is overblown, the evidence anecdotal, and it is impossible to see that search engines contribute to the creation of filter bubbles based on the empirical evidence produced by the study.