How to Use Bounce Rate as a Quality Guide

What Is a Bounce Rate?

A bounce occurs when a user visits a website and exits the page from which they came without having moved to another page on the same website.

A higher bounce rate means users leave your website without viewing any additional pages. A lower bounce rate means users stay on your website and have moved to a different page within your website.

Keeping track of your bounce rate is a fantastic quality indicator to determine which pages are working for you. Before you become alarmed, know this: a high bounce rate does not indicate failure! A high bounce rate might be the nature of your website.

Referential vs. Content-Driven Websites

A referential-driven page or website presents information solely for the purpose of providing an authoritative and unbiased resource. Online referential resources may include dictionaries, glossaries, timelines, encyclopedias, etc., and these pages are often static (i.e., they do not require new material to stay fresh). Referential-driven websites typically have higher bounce rates because that's the nature of the website - readers search for the reference material, find the website, and leave.

Content-driven websites must stay fresh and constantly provide relevant material. Examples of content-driven websites include article directories, blogs, and news pages. A higher bounce rate on this type of site may be an indicator of poor quality, irrelevant content, poor navigation, and more.

Expert Authors Should Aim for a Low Bounce Rate

As content providers, Expert Authors who provide high quality content should aim for a low bounce rate (50% or less) and focus on increasing the average time the visitor spends on the site. Unlike referential-driven website providers, content-driven websites want visitors to stay on the website and continue clicking through to different articles or areas of informative content on the website.

Using tools like Google Analytics, gather your pageviews, visitors, visitor duration, and bounce rate. Compare pages and determine why one page may be performing poorly and why one page may be performing well. How was the quality of writing? Navigation issues? Keyword selection? Ads on the page? Length of the article?

To reduce your website's bounce rate and increase the time on the page/site, use the pages that performed well as a template or theme to emulate on other pages while still providing original content. Additionally, try the following strategies:

• Update your website with quality content frequently
• Try out features important to your audience
• Create interactivity (i.e., two-way flow of information between you and your audience)
• Give your audience a reason to stick around (e.g., resources, quizzes, games, etc.)
• Routinely check your links to ensure they are working properly
• Continue driving traffic to your website via quality articles, social media, etc.

Please note: Don't be discouraged by a high bounce rate if visitors stay on the page longer than average (approximately 2 minutes). It could indicate the reader found their information, read the article, and left. However, if a content-driven page is clocking under a minute with a high-bounce rate - let these be key indicators that improvement is needed.

Understanding the dynamics and performance of your website is the key to success. Not only will you be able to target your audience by providing the content they want both in your articles and on your website, you will save yourself from the agony of wondering what is wrong with your website and your articles.

A National Repository on  Maternal Child Health developed my me has a very good average Bounce Rate of 16%.

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How Google Search Engine Works

First of all it's important to recognize how Google works. Essentially Google has a huge database that it refers to and which it builds automatically with the help of spiders and robots. These spiders are PHP scripts (programs running on the Google server) which surf the web as we do by following links from one page to another. When they find a page, they will then attempt to categorize it by looking for words that are repeated often (or just a couple of times) and by looking at what terms are associated with the page on other sites (in the links for instance). The order is dictated by which site is the most relevant, as well as which seems to be the best quality based on external references etc, and you will then be given a list based on these factors.

In short then Google looks for matches in your text as well as similar themes on the page. It doesn't (yet) understand what you are asking it and so you shouldn't phrase your query as a question. Searching 'How do I go about fixing my PC?' isn't going to be very useful.

The other reason this isn't going to be very useful is that the language is too chatty (meaning that it will occur on fewer sites a that's not the way everyone speaks) and because it's too general meaning the results won't necessarily help you with your specific computer problem.

What you need to do then is to think of the short snippets of code that are likely to appear on a relevant page and then search for that. So in other words if your monitor won't turn on you should type in 'monitor won't turn on' or 'monitor not turning on' which is likely to match a lot of discussions on forums as well as a lot of other pages.

Better yet for something like that is to search for any specific error codes if they come up, as these will be reprinted by people on forums etc who are asking for advice.

Understanding the SERPs

'SERPs' are the pages that come up when you do a search – 'Search Engine Results Pages'. These include your results as well as some other things. The top few listings for instance will be adverts and these will have a very feint yellowish background behind them – look out for this to identify the ads.

Meanwhile you will see a little listing underneath each result. This snippet of text comes right from the page and this is your best tool for deciding whether that page is providing the right information before you go ahead and click it. Be discerning here and you can save yourself a lot of time.

James Delurno's work with a registry cleaner company has taught him about how badly people are using Google to find their software. He mostly writes about technology and computer maintenance topics but decided to write this one about using Google effectively.

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How does Google work?

Google's Secret Formula

In the past 12 months, Google doubled its staff, tinkered with its search engine to speed up results, and now answers more queries than Microsoft and Yahoo combined. But there’s one query we had to answer ourselves: How does Google work?

Blame spell-check. Ten years ago this September, so the story goes, some Stanford grad students were helping Larry Page choose a name for his search engine. “Googolplex,” said Sean ­Anderson. (They’d already sensed how big this could become.) “Googol,” Page replied. Anderson, checking to see if the name was taken, typed g-o-o-g-l-e into his browser and made the most famous spelling mistake since p-o-t-a-t-o-e. Page registered the name within hours, and today, Google isn’t a typo, it’s a verb, one with a market cap of about $160 billion. Here, then, is a guide to what happens during a typical Google search—now, of course, with automatic spell-check.

1. Query Box: It all starts with somebody typing in a request for information about the safest dog food, what time the D.M.V. closes, or what the prime rate is in China.

2. Domain-Name Servers: “Hello, this is your operator . . . ” The software for Google’s domain-name servers runs on computers in leased or company-owned data centers all over the world, including one in the old Port Authority headquarters in Manhattan. Their sole purpose is to shepherd searches into one of Google’s clusters as efficiently as possible, taking into account which clusters are nearest to the searcher and which are least busy at that instant.

3. The Cluster: The request continues into one of at least 200 clusters, which sit in Google-owned data centers worldwide.

4. Google Web Server: This program splits a query among hundreds or thousands of machines so that they can all work on it at the same time. It’s the difference between doing your grocery shopping all by yourself and having 100 people simultaneously find one item and toss it into your cart.

5. Index Server: Everything Google knows is stored in a massive database. But rather than waiting for one computer to sift through those gigabytes of data, Google has hundreds of computers scan its “card catalog” at the same time to find every relevant entry. Popular searches are cached—held in memory—for a few hours rather than run all over again. That means you, Britney.

6. Document Server: After the index server compiles its results, the document server pulls all the relevant documents—the links and snippets of text from its massive database. How does Google search the Web so quickly? It doesn’t. It keeps three copies of all the information from the internet that it has indexed in its own document servers, and all those data have already been prepped and sorted.

7. Spelling Server: Google doesn’t read words; it looks for patterns of characters, be they in English or Sanskrit. If it sees your requested pattern a thousand times but finds a million hits for a similar pattern that’s off by one character, it connects the dots and politely suggests what you probably meant, even while it provides you the results, if any, for your fat-fingered query for “hwedge funds.”

8. Ad Server: Each query is simultaneously run through an ad database, and matches are fed to the Web server so that they’re placed on the results page. The ad team is in a race with the search team. Google vows to deliver all searches as quickly as possible; if ad results take longer to pull up than search results, they won’t make it onto the page—and Google won’t make money on that search.

9. Page Builder: The Google Web server collects the results of the thousands of operations it runs for a query, organizes all the data, and draws Google’s cunningly simple results page on your browser window, all in less time than it took to read this sentence.

10. Results Displayed: Often in 0.25 seconds or less.

Cluster Control

Google’s genius lies in its networking software, which helps thousands of cheap computers in a cluster act like one huge hard drive. Those inexpensive computers allow Google to replace parts ­without stopping the whole show: If a computer drops dead, there are at least two others ready to take its place while an engineer swaps out the busted machine.

Power Power

Just about the only thing limiting Google’s performance is how much electricity the company can buy. One of its newest data centers (code name: Project 02) is near the Columbia River in The Dalles, Oregon, which has access to 1.8 gigawatts of cheap hydroelectric power; not coincidentally, this is where major internet hookups from Asia connect to U.S. networks. The byte factory has two computing centers, each the size of a football field.

Petabytes

Based on the few numbers Google releases, experts guess that at least 20 petabytes of data are stored on its servers. But Googleytes are ­famous for understatement; Wired says Google may have 200 petabytes of capacity. So how much is that? If your iPod were just 1 petabyte (one million gigabytes), you’d have about 200 million songs to shuffle. And if you started downloading a petabyte over your high-speed internet connection, your great-great-great-great-grandchild might still be around when the last few bytes get transferred, in 2514.

Page Rank

Google decides how reliable a site is—and thus how important the site’s content will be when Google forms a list of search results—by considering more than 200 factors as it analyzes content. But the secret sauce is Google’s patented formula for following and scoring every link on a page to learn how different sites connect, which means a site is deemed reliable based largely on the quality of the sites that link to it.

Googlebots

Google deploys programs called spiders to build its copies of the internet. On popular sites, Googlebots may follow every link several times an hour. As they scour the pages, the spiders save every bit of text or code. The raw data are pulled back into the cluster, run through the mill, and scheduled to incrementally replace the older data already on the index and doc servers, ensuring that results are fresh, never frozen.

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