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Web analytics is the measurement of the behaviour of visitors to a website. In a commercial context, it especially refers to the measurement of which aspects of the website work towards the business objectives; for example, which landing pages encourage people to make a purchase. Many different vendors provide web analytics software and services. Web analytics technologies There are two main technological approaches to collecting web analytics data. The first method, logfile analysis, reads the logfiles in which the web server records all its transactions. The second method, page tagging, uses JavaScript on each page to notify a third-party server when a page is rendered by a web browser. Web server logfile analysis Web servers have always recorded all their transactions in a logfile. It was soon realised that these logfiles could be read by a program to provide data on the popularity of the website. In the early 1990s, web site statistics consisted primarily of counting the number of client requests made to the web server. This was a reasonable method initially, since each web site often consisted of a single HTML file. However, with the introduction of images in HTML, and web sites that spanned multiple HTML files, this count became less useful. Two units of measure were introduced in the mid 1990s to gauge more accurately the amount of human activity on web servers. These were page views and visits (or sessions). A page view was defined as a request made to the web server for a page, as opposed to a graphic, while a visit was defined as a sequence of requests from a uniquely identified client that expired after a certain amount of inactivity, usually 30 minutes. The page views and visits are still commonly displayed metrics, but are now considered rather unsophisticated measurements. The emergence of search engine spiders and robots in the late 1990s, along with web proxies and dynamically assigned IP addresses for large companies and ISPs, made it more difficult to identify unique human visitors to a website. Log analyzers responded by tracking visits by cookies, and by ignoring requests from known spiders. The extensive use of web caches also presented a problem for logfile analysis. If a person revisits a page, the second request will often be retrieved from the browser's cache, and so no request will be received by the web server. This means that the person's path through the site is lost. Caching can be defeated by configuring the web server, but this can result in degraded performance for the visitor to the website. Page tagging Concerns about the accuracy of logfile analysis in the presence of caching, and the desire to be able to perform web analytics as an outsourced service, led to the second data collection method, page tagging. In the mid 1990s, Web counters were commonly seen — these were images included in a web page that showed the number of times the image had been requested, which was an estimate of the number of visits to that page. In the late 1990s this concept evolved to include a small invisible image instead of a visible one, and, by using JavaScript, to pass along with the image request certain information about the page and the visitor. This information can then be processed by a web analytics company, and extensive statistics generated. This can be done remotely, by the web analytics company. The web analytics service also manages the process of assigning a cookie to the user, which can uniquely identify them during their visit and in subsequent visits. Logfile analysis vs page tagging Both logfile analysis programs and page tagging solutions are readily available to companies which wish to perform web analytics. In many cases, the same web analytics company will offer both approaches. The question then arises which method a company should choose. There are advantages and disadvantages to each approach. Advantages of logfile analysis The main advantages of logfile analysis over page tagging are as follows. Advantages of page tagging The main advantages of page tagging over logfile analysis are as follows. Economic factors Logfile analysis is almost always performed in-house. Page tagging can be performed in-house, but it is more often provided as a third-party service. The economic difference between these two models is often the most important difference for a company deciding which to purchase. Which solution is cheaper often depends on the amount of technical expertise within the company, the vendor chosen, the amount of activity seen on the web sites, the depth and type of information sought, and the number of distinct web sites needing statistics. Hybrid methods Some companies are now producing programs which collect data through both logfiles and page tagging. By using a hybrid method, they aim to produce more accurate statistics than either method on its own. Other methods Other methods of data collection have been used, but are not currently widely deployed. These include integrating the web analytics program into the web server, and collecting data by sniffing the network traffic passing between the web server and the outside world. There is also another method of the page tagging analysis. Instead of getting the information from the user side, when he opens the page, it’s also possible to let the script work on the server side. Right before a page is sent to a user it then sends the data. Key definitions Problems with cookies Historically, vendors of page-tagging analytics solutions have used third-party cookies, that is cookies sent from the vendor's domain instead of the domain of the website being browsed. Third-party cookies can handle visitors who cross multiple unrelated domains within the company's site, since the cookie is always handled by the vendor's servers. However, third-party cookies in principle allow tracking an individual user across the sites of different companies, allowing the analytics vendor to collate the user's activity on sites where he provided personal information with his activity on other sites where he thought he was anonymous. Although web analytics companies deny doing this, other companies such as companies supplying banner ads have done so. Privacy concerns about cookies have therefore led a noticeable minority of users to block or delete third-party cookies. In 2005, some reports showed that about 9-11% of Internet users blocked third-party cookies. Most vendors of page tagging solutions have now moved to provide at least the option of using first-party cookies (cookies assigned from the client domain). Another problem is cookie deletion. When web analytics depend on cookies to identify unique visitors, the statistics are dependent on a persistent cookie to hold a unique visitor ID. When users delete cookies, they usually delete both first- and third-party cookies. If this is done between interactions with the site, the user will appear as a first-time visitor at their next interaction point. Without a persistent and unique visitor id, conversions, click-stream analysis, and other metrics dependent on the activities of a unique visitor over time, cannot be accurate. Cookies are used because IP addresses are not unique to users and may be shared by large groups. Other methods of uniquely identifying a user are technically challenging and would limit the trackable audience or would be considered suspicious. Cookies are the selected option because they reach the lowest common denominator without using technologies regarded as spyware. Unique landing pages vs referrals for campaign tracking Tracking the amount of activity generated through advertising relationships with external web sites through the Referrals reports available in most web analytics packages is significantly less accurate than using unique landing pages. Referring URLs are an unreliable source of information for the following reasons: See also | |||||||
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