Everything About Web Analytics: (Part 2)


A Brief History of Web Analytics

While monitoring and assessing the effectiveness of your website may seem conventional these days, it wasn’t always the case. Let’s take a look at the history of web analytics, as well as some key terms we’ve come across.

The Web Analytics Association didn’t submit a defined definition until 2006, while web analytics was still in its infancy in the early 1990s, demonstrating how long the word and the ideal took to develop.

Web analytics began with rudimentary technologies that counted extremely broad, sweeping numbers. The manner these technologies collected and displayed data evolved throughout time, as did the extent of information available. Around the year 2000, the process witnessed its first shift, when Google bought Urchin, which was later redesigned and published as the free application Google Analytics in 2005 when web analytics transitioned from log-based data collection to JavaScript tag-based analytics (more on that below…). Web analytics has a rapid influence on the commercial sector.

Here are some key terms and moments in web analytics history:

  • Log-based data collection
  • Hit counters
  • Alexa rank
  • JavaScript tag-based analytics

Log-based data collection

This is the study of records generated by servers or devices in real-time, and it served as the foundation for early website analytics. In the early 1990s, it was also used to measure basic website metrics and to flag system faults, infiltration attempts, and security issues.

A web server’s log files include visitor information such as visit length and pages visited, and while these files were originally intended to be used to track bandwidth difficulties, it was discovered that they could also be decoded to disclose website data.

This system could only offer large, broad data like total traffic, which meant firms had to undertake the research themselves, but it was nevertheless a huge window into early internet activity. The difficulty was that this information was frequently erroneous and simplistic, and as people’s dependence on company websites grew, so did the demand for a more sophisticated solution.

Hit counters

These were the first online analytics tools, paving the way for today’s more complex technologies. A hit counter is a simple tool that counts the number of unique visitors to a website. Though a simple concept, these counters may be quite useful in determining brand engagement because they only collect new IP addresses, providing a rudimentary sense of website reach.

Though these widgets are still popular today, they need very little setup and upkeep, and many have evolved to meet market demands. Keywords, visitor origin, traffic patterns, and visit time/date are frequently included in modern hit counters.

Alexa rank

The Alexa rank was created in response to the unexpected surge of online analytics, with the goal of demonstrating how websites compare to one another over a three-month period. Alexa provides businesses with information on how their website compares to others and how it is regarded by an outside audience by measuring total traffic over a specific time period.

This ranking looks to be useful, however, it is virtually infamous for its inaccuracy, providing “extremely imprecise” predictions of where websites rank globally. However, Alexa (owned by Amazon) is always working to enhance their ranking, ensuring that it provides useful information to companies.

It should come as no surprise that Alexa constantly ranks Google as the top website, with each user reading an average of 7.93 pages every day.

JavaScript tag-based analytics

Around the year 2000, it became evident that log-based web analytics couldn’t provide the numbers that businesses need, thus the JavaScript tag-based technique was introduced. Each webpage has a piece of code that collects visitor information and cookies, which is then packaged into a string of code and transmitted to a host for the user to view.

While this is often a more expensive solution that requires different privacy settings (because of the usage of Cookies), it provides significantly more specific data with a high level of accuracy. This strategy can provide more than just statistics, allowing organizations to receive real-time insight into patterns and user behavior without having to “do the arithmetic.” This was the answer that was required to keep up with the trends in online analytics, and with the debut of Google Analytics, this way became standard for web analytics tools and solutions.