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Wednesday, April 11, 2012

Two Methodologies used in web analytics


As mentioned in my other post about What Google Analytics Can’t Do, one of the key factors of getting your site a visible ranking is to know how well it performs with search engines and how well it meets your site visitors’ needs. To know about this, you must use one or more web analytics tools, whose function is to provide collection, measurement and reporting of web traffic data. There are different tools and most if not all of them are based on either one of the two methodologies: page tagging or web server log files.

Page tagging method

Page tags, as its name describes, works based on tagging individual web page with some tracking code written in Javascript. When the webpage is open in a browser (with Javascript enabled), the tracking code is triggered and starts collecting and sending data to a server. That server has an application that can gather and process the data, then present them in form of useful information – web metrics. This technique is also referred to as the client-side data collection.

Google Analytics is an example of web analytics application that uses page taggingmethod. Let’s take a look at the whole process involved:

You tag your web pages by inserting the tracking code on each page -> Visitors visit your website -> (Visitors’) Web browsers send information to Google Anallytics server -> Google Analytics stores and processes data -> You access Google Analytics to view the metrics

Web server log file method

A web server log (file) is a log file, like a text file, that is automatically created by the web server with details of its activities. Every visitor to your website will be tracked or more exactly logged by the server. The server creates an entry for each visit in its log with details about the visitor’s IP address, date and time of the visit, the page and files requested, bytes served, referrer, user agent etc. Log files have a wealth of data, and because of this, each log file is pretty big in size (we’re talking about tens or hundreds of megabytes per text file. As a result, to analyze log files, you’d need a web log analyzer, a software that can read/import log files and spit out useful information in a user-friendly way. This technique, independent of visitor’s browsers, is referred to as the server-side data collection.

Click Tracks and Awstats are examples of a web log analyzers. Let’s take a look at what happens:
Visitors visit your website -> Your web server creates entries in its log file -> You use Click Tracks/Awstats to process the logs and get the reports/metrics

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