This book is licensed under a Creative Commons by-nc-sa 3.0 license. See the license for more details, but that basically means you can share this book as long as you credit the author (but see below), don't make money from it, and do make it available to everyone else under the same terms.
This content was accessible as of December 29, 2012, and it was downloaded then by Andy Schmitz in an effort to preserve the availability of this book.
Normally, the author and publisher would be credited here. However, the publisher has asked for the customary Creative Commons attribution to the original publisher, authors, title, and book URI to be removed. Additionally, per the publisher's request, their name has been removed in some passages. More information is available on this project's attribution page.
For more information on the source of this book, or why it is available for free, please see the project's home page. You can browse or download additional books there. To download a .zip file containing this book to use offline, simply click here.
Log-file analysis software reads the records, called log filesText files created on the server each time a click takes place, capturing all activity on the Web site., on the Web server, which record all clicks that take place on the server. Web servers have always stored all the clicks that take place in a log file, so the software interprets data that have always been available. A new line is written in a log file with each new request. For example, clicking on a link, an Ajax call, or submitting a form will each result in a new line being written.
Pixel tracking can be used to track e-mail campaigns. Here, a tiny, transparent pixel is placed in the e-mail. When you load the images in the e-mail, you will also load the tiny image that tracks your activity.
In terms of log-file analysis, you should know the following:
In terms of page tagging, you should know the following:
Because of the different methods of collecting data, the raw figures produced by the two services will differ. Sometimes, both are used to analyze a Web site. However, raw figures not matching up should not be a problem. It is through interpreting these figures that you will be able to understand how effective your eMarketing efforts are.
Web site analytics packages can be used to measure most, if not all, eMarketing campaigns. Web site analysis should always account for the various campaigns being run. For example, generating high traffic volumes by employing various eMarketing tactics like SEO (search engine optimization), PPC (pay per click), and e-mail marketing can prove to be a pointless and costly exercise if the visitors are leaving your site without achieving one (or more) of your Web site’s goals. Conversion optimization aims to convert as many of a Web site’s visitors as possible into active customers.
There are three types of Web analytics metrics:
Why would you want to look at the activity of a single visitor? Why would you want to segment the traffic for analysis?
In analysis, metrics can be applied to three different universes:
Here are some of the key metrics you will need to get started on Web site analytics:
Unique visitors. The number of individual people visiting the Web site one or more times within a period of time. Each individual is only counted once. Types of visitors can be categorized as follows:
A repeat visitor may be either a new visitor or a return visitor, depending on the number of times he or she has visited the site within the time period being analyzed.
These are the most basic Web metrics. They tell you how much traffic your Web site is receiving. Looking at repeat and returning visitors can tell you about how your Web site creates loyalty. As well as growing overall visitor numbers, a Web site needs to grow the number of visitors who come back. An exception might be a support Web site—repeat visitors could indicate that the Web site has not been successful in solving the visitor’s problem. Each Web site needs to be analyzed based on its purpose.
The following help characterize the visit to a particular Web site:
ReferrerThe URL that originally generated the request for the current page.. The URL (uniform resource locator) that originally generated the request for the current page.
These are the terms that tell you how visitors reach your Web site and how they move through the Web site. The way that a visitor navigates a Web site is called a click path. Looking at the referrers, both internal and internal, allows you to gauge a click path that visitors take.
The following help characterize how visitors move through the Web site:
When visitors view a page, they have two options: leave the Web site, or view another page on the Web site. These metrics tell you how visitors react to your content. Bounce rate can be one of the most important metrics that you measure! There are a few exceptions, but a high bounce rate usually means high dissatisfaction with a Web page.
Other metrics that apply to eMarketing tactics include the following:
For the most up-to-date definitions, visit http://www.webanalyticsassociation.org to download the latest definitions in PDF (portable document format).
In order to test the success of your Web site, you need to remember the TAO of conversion optimization:
Using your goals and KPIs, you’ll know what metrics you will be tracking. You will then need to analyze these results and take appropriate actions. And the testing begins again!
Metrics use the following: