What is web analytics?

The Internet has given us access to an incredible amount of information. While many companies are today concentrating their efforts to ensure their presence on the Internet and boost their profits, others have understood the importance of web analytics in optimizing their performance and adjusting their web marketing strategy. This article aims to give you an introduction to web analytics so that you understand exactly what it is. If you wish to know more, you can consult our other articles in the section “Our Articles – Web Analytics“.

The purpose of web analytics is to track, collect, measure, and analyze data from the Internet in order to optimize a website as well as the web marketing actions undertaken.

A brief history of web analytics

At the birth of the Internet, things were relatively simple. Someone would write an address using URL (Uniform Resource Locator), a file with text and links appeared and everything was done. Life was so simple.

Nevertheless, errors occurred regularly. Errors prevented files from loading properly or links from returning users to the desired page. An error message was often shown without additional information about the reason for the error. We later learned that there was an error report system related to the website hosting server. Each “request” made to the server was then analyzed and we were finally able to discover that the report did not only relate to user visits. It was also possible to know the name of the file that was loaded, the date, the page visited, the IP address (Internet Protocol), the browser used (e.g. Internet Explorer) and so on.

To put things in a better context, you should understand that in the past a ‘request’ simply corresponded to viewing a file.

As files began to get heavier and more complex, some people began to take interest in data generated by web servers and to create web analytics programs. This is when web analytics was born. Analog, designed by Dr. Stephen Turner in 1995, was the first web analytics program available on the Internet. This program is still one of the most used ones today.

The evolution of web analytics

The year 2000 was marked by the increase of Internet users using dynamic IP addresses (the server assigns a new IP address to each connection). It was increasingly difficult to identify unique visitors to websites. Web analysts therefore tried to use the data sent by various browsers, but it was still not optimal insofar as all browsers do not work in the same way.

For these reasons (and others that are useless to be cited in this article), the programming language “Javascript” was created and became the new standard for collecting data from websites. A few Javascript lines were added to each page to send information to the server whenever it is loaded.

Here is an example of Javascript code lines used by the “Crazy Egg” program. This allows you to analyze your visitor behaviour thanks to the movements of their mouse. To have all these valuable information, just add these characters in the code of your site:

<Script type = “text / javascript”>

// <! [CDATA [

Document.write (‘<scr’ + ‘ipt

Src = “http://crazyegg.com/pages/scripts/1111.js?’+

(New Date ()) getTime () + ‘”~ CAtype =” text / javascript “> </ scr’ + ‘ipt>’);


</ Script>

Web analytics today and the challenges of tomorrow

For a long time, companies have spent money on their websites because they had to ensure their presence on the web. It was “cool” to be on the net. The web then developed at an incredible speed to become a fully-fledged driver for any business strategy used to generate business opportunities. In order to justify their increasingly important expenses, Internet marketing managers have had to use analytical tools to measure the return on investment of their various campaigns.

Even today, most people think that web analytics consists solely of measuring the clicks made on a website. In reality, tracking user clicks represents only a small part of what you can measure. This is the reason why some companies that have invested in analytical solutions are frustrated when they compare their clicks and the revenue generated online. It is therefore necessary to go further in the use of analytical tools and take into account other variables that will give a clearer vision of your web marketing performance.

As you can see, web analysis should be extended to all possible research fields (number of clicks, page views, average time spent on the site, average time spent on each page, bounce rate, traffic sources, etc.) so that the data will better speak to you. You need to understand each parameter in order to get a clear view of the behavior of your visitors/customers. Companies have learned to acquire powerful tools to collect data from their websites, but they do not always know how to sort through and analyze their data. Analytical experts are often faced with analyzing an enormous amount of information (Big Data). It is sometimes difficult to use this data if the company has not clearly defined its objectives, set up a budget and a plan dedicated to result analysis.

With the increasing development of new information and communication systems, web-marketing strategies are becoming more complex and analytical needs are increasing so that companies can better define the priorities and the sectors they wish to invest in. It is very common to see that a company spends $2,000 a month on social network campaigns, $5,000 on Google/Yahoo/Bing search networks, and $2,000 on remarketing and emailing campaigns without investing a single dollar in web analytics. How can these companies measure the impact of each communication sector if no effort is made to analyze the results? Perhaps a performance analysis would identify the most relevant sources of traffic and thus alter their budget allocation.

Every company interprets data differently

In web analytics, you need to make sure that apples are always compared with apples. Indeed, it is very easy to manipulate the figures to obtain beautiful curves without the results having any concrete meaning. Although they are not always voluntary, manipulation errors can cause managers to make bad decisions.

Take for example the case of an e-commerce site. Is it good or bad to see that your number of page views is greater than the number of visitors? For some, the fact that visitors interact with the website by consulting other pages is going to be a sign of a good performance (visitors stay on the site and look to go further) while others will interpret this as a result of a lack of relevance regarding the landing page (visitors go to other pages because they did not find what they were looking for on the first one).

In fact, analyzing the relationship between page views and the number of visitors is not enough to draw a conclusion. It is necessary to go further in the analysis and understand the time visitors spent on each page, as well as the specific pages they consulted in order to identify a certain logic in their navigation. For example, if your visitors automatically return to the home page as soon as they arrive on the landing page you offer, it is a good bet that the content is not relevant to their search.

With the development of Mobile navigation, you have to adapt the shape of your content according to the different resolutions of screens. Similarly, the intention is not always the same when a user uses a mobile device versus a computer; you will also need to adapt the message that you want to pass along on different devices.


The purpose of this article was to give you an idea of the basics of web analytics as well as to make you aware of the importance this strategy presents to a company’s Internet communication strategy. To give you a concrete approach, each client who collaborates with My Little Big Web is allocated a bank of hours dedicated to the analysis of its current and future performances. We believe that it is not optimal to launch web marketing campaigns if the analytical structure has not been set up to allow us to analyze the results we obtain.

If you liked this article, you might like this one: What is remarketing and how can I use it?

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What is web analytics?
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