Improve ( increase ) Alexa rank

A collection of methods which can improve your Alexa Traffic Rank What is the Alexa Rank? In simple terms, the Alexa Rank is a ranking system of your website which bases its ranking on the level of traffic each website receives from the number of people who visit a website with the Alexa toolbar installed. The most important element of any website is content – good quality informative content cannot be beaten when trying to get a good page rank. The more people who visit your website and return or recommend it, the more your traffic will naturally increase. Below are a few methods that can help to improve your alexa rank :

1) Install the Alexa toolbar on your computer and request that anyone who knows you do the same.

2) Put an Alexa rank widget on your website. Each click can count as a visit even if the toolbar is not used by the visitor.

3) Write an article or blog on Alexa. Webmasters love searching methods to improve their sites. Webmasters are also very likely to have the Alexa toolbar installed. Each visit will increase your alexa rank.

4) Use forums to post messages that include your url. Try and make your post interesting to encourage readers to visit your site.

5) Make use of social networking sites. Get your website Dugg and you could increase traffic. Make sure anything that is Dugg is note worthy.

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Another cool trick is using the Alexa Toolbar method. Previously, people use to install Alexa Toolbar for IE and the Search Status Plugin for Firefox. Both of these use to do the job very effectively. But now, Alexa has released their Firefox toolbar and things has become much more easier.

Yet another trick is the Browser Homepage method. Put your website as your browser home page and let it load every time when you open up a new browser. That’s it.

All of these techniques work wonderfully and they are damn effective. Do it to see for yourself and come back here to leave a comment. Have fun.

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PageRank is a link analysis algorithm that assigns a numerical weighting to each element of a hyperlinked set of documents, such as the World Wide Web, with the purpose of “measuring” its relative importance within the set. The algorithm may be applied to any collection of entities with reciprocal quotations and references. The numerical weight that it assigns to any given element E is also called the PageRank of E and denoted by PR(E). 

The name PageRank is a trademark of Google. The PageRank process has been patented ( U.S. Patent 6,285,999 ). The patent is not assigned to Google but to Stanford University.
General description of PR

Google describes PageRank: “ 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 more than the sheer volume of votes, or links a page receives; 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”. ”

In other words, a PageRank results from a “ballot” among all the other pages on the World Wide Web about how important a page is. A hyperlink to a page counts as a vote of support. The PageRank of a page is defined recursively and depends on the number and PageRank metric of all pages that link to it (” incoming links”). A page that is linked to by many pages with high PageRank receives a high rank itself. If there are no links to a web page there is no support for that page.

Google assigns a numeric weighting from 0-10 for each webpage on the Internet; this PageRank denotes a site’s importance in the eyes of Google. The scale for PageRank is logarithmic like the Richter Scale and roughly based upon quantity of inbound links as well as importance of the page providing the link.

Numerous academic papers concerning PageRank have been published since Page and Brin’s original paper.[2] In practice, the PageRank concept has proven to be vulnerable to manipulation, and extensive research has been devoted to identifying falsely inflated PageRank and ways to ignore links from documents with falsely inflated PageRank.

Alternatives to the PageRank algorithm include the HITS algorithm proposed by Jon Kleinberg, the IBM CLEVER project and the TrustRank algorithm.

taken from : http://www.prtag.com/what-is-pagerank-pr.php