Search engines typically presume that the considerably more popular a site, page, or document
Search engines are generally answer machines. Whenever a person performs an online search, the search engine scours its collection of billions of documents and does two things: first, it returns only those results which are relevant or useful to the searcher's query; secondly, it ranks all those results according to the popularity of the websites providing the information. It is both relevance and popularity that the process of SEO is meant to impact.
With a search engine, relevance means a lot more than finding a page with the right words. During the early days of the web, search engines did not go much further than this simplistic step, and search results ended up of limited value. Through the years, smart engineers have created better ways to match results to searchers’ queries. Today, hundreds or thousands of factors influence relevance, and Search engines typically presume that the considerably more popular a site, page, or document, the more valuable the information it contains should be. This assumption has proven reasonably successful in terms of user satisfaction with search results.
Popularity and relevance are not determined manually. Alternatively, the engines employ mathematical equations (algorithms) to organize the wheat from the chaff (relevance), and then to rank the wheat in order of quality (popularity). These algorithms often consist of hundreds of factors. From the search marketing field, we refer to them as “ranking factors.” Moz constructed a resource specifically on this subject: Search Engine Ranking Factors.