Web analytics is the study of the behavior of website visitors. In a commercial context, web analytics especially refers to the use of data collected from a web site to determine which aspects of the website work towards the business objectives; for example, which landing pages encourage people to make a purchase.
Data collected almost always includes web traffic reports. It may also include e-mail response rates, direct mail campaign data, sales and lead information, user performance data such as click heat mapping, or other custom metrics as needed. This data is typically compared against key performance indicators for performance, and used to improve a web site or marketing campaign's audience response.
Hello Infocom Web Design provides web analytics software and services.
Web servers have always recorded all their transactions in a logfile. Using log analysis software these logfiles can be read by a program to provide data on the popularity of the website. Hello Infocom Web Designprovides logfile analysis services.
Concerns about the accuracy of logfile analysis led to the page tagging method of logfile analysis.
Hello Infocom Web Design 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.
With the increasing popularity of Ajax-based solutions, an alternative to the use of an invisible image, is to implement a call back to the server from the rendered page. In this case, when the page is rendered on the web browser, a piece of Ajax code would call back to the server and pass information about the client that can then be aggregated by Hello Infocom Web Design web analytics team.
Both logfile analysis programs and page tagging are solutions Hello Infocom Web Design have readily available to companies that wish to perform web analytics. The question then arises of which method a company should choose. There are advantages and disadvantages to each approach.
The main advantages of logfile analysis over page tagging are as follows.
The main advantages of page tagging over logfile analysis are as follows.
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 can also be a consideration 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.
Hello Infocom Web Design is now producing programs which collect data through both logfiles and page tagging. By using a hybrid method, we aim to produce more accurate statistics than either method on its own.
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 / she 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.
Hello Infocom Web Design can provide for either of these solutions.
There are no globally agreed definitions within web analytics as the industry bodies have been trying to agree on definitions that are useful and definitive for some time. The main bodies who have had input in this area have been Jicwebs (Industry Committee for Web Standards) ABCe (Auditing Bureau of Circulations electronic, UK and Europe), The WAA (Web Analytics Association, US) and to a lesser extent the IAB (Interactive Advertising Bureau). This does not prevent the following list from being a useful guide, suffering only slightly from ambiguity. Both the WAA and the ABCe provide more definitive lists for those who are declaring their statistics using the metrics defined by either.
A common misconception in web analytics is that the sum of the new visitors and the repeat visitors ought to be the total number of visitors. This becomes clear if the visitors are viewed as individuals on a small scale, but still causes a large number of complaints that analytics software cannot be working because of a failure to understand the metrics.
Here the culprit is the metric of a new visitor. There is really no such thing as a new visitor when you are considering a web site from an ongoing perspective. If a visitor makes their first visit on a given day and then returns to the web site on the same day they are both a new visitor and a repeat visitor for that day. So if we look at them as an individual which are they? The answer has to be both, so the definition of the metric is at fault.
A new visitor is not an individual it is a fact of the web measurement. For this reason it is easiest to conceptualize the same facet as a first visit (or first session). This resolves the conflict and so removes the confusion. Nobody expects the number of first visits to add to the number of repeat visitors to give the total number of visitors. The metric will have the same number as the new visitors, but it is clearer that it will not add in this fashion.
On the day in question there was a first visit made by our chosen individual. There was also a repeat visit made by the same individual. The number of first visits and the number of repeat visits will add up to the total number of visits for that day.
Historically, vendors of page-tagging analytics solutions have used a third-party cookie; 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 28% of Internet users blocked third-party cookies and 22% deleted them at least once a month.
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 subdomain).
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 always unique to users and may be shared by large groups or proxies. 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.
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: