History of Web Analytics - Lead Forensics
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Whilst the notion of measuring and analyzing your website success seems commonplace these days, it hasn’t always been so. Let’s look at the history of web analytics, and some vital vocab encountered along the way.

 

A brief history of web analytics…

Whilst web analytics was in its infancy in the early ’90s the Web Analytics Association didn’t propose their standardized definition until 2006, showing you how long the term and the ideal took to build.

Web analytics started simple, with basic tools counting very general, overarching figures.  As time progressed, the way these tools collected and presented data advanced as did the scope of information on offer. As web analytics converted from log-based data collection to JavaScript tag-based analytics (more on that below…), around the year 2000, the process saw its first shift, when Google purchased Urchin, which was then redeveloped and released as the free tool Google Analytics in 2005. Web analytics impacted the business world with a rapid effect.

Over time the ability to gather and analyze website data became universal and simple. To this day Google Analytics remains the most popular tool, but many crave deeper and more accessible data. The future of web analytics aims to show more than just “overall visits”, it aims to prove the intent of each individual visit, allowing users the see their website through their visitor’s eyes.

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

 

Log-based data collection

This is the real-time analysis of records generated by servers or devices and provided the backbone for early website analytics. It’s often used to highlight system errors, intrusion attempts and security issues but was also used to measure basic website metrics in the early ’90s.

A web-server automatically creates log files containing visitor information such as visit duration and pages visited, and although these files were usually used to measure bandwidth issues, it was discovered they could also be decoded to reveal website data.

This method was only able to provide the big, overarching figures such as overall traffic, meaning businesses had to do the analysis part themselves, but this was nonetheless an enormous insight into early online activity. The problem was, this data was often inaccurate and very basic, and as the reliance on business websites increased so did the need for a more advanced solution.

 

Hit counters

These were very early web analytics tools which paved the way for the more advanced software on offer today. Very simply, a hit counter is installed on a webpage to count the number of unique visits. Though a basic idea, these counters can be hugely effective in understanding brand engagement, as the counter only counts new IP addresses it offers a basic understanding of website reach.

Though these are still popular widgets today, they involve very little set-up and maintenance, many have now become more advanced to meet the market’s needs. Modern hit counters often include information regarding keywords, visitor origin, traffic patterns and visit time/date.

 

Alexa rank

This sudden influx of web analytics lead to the creation of the Alexa rank, aiming to prove how websites measure against each other over a 3-month period. Gauging overall traffic across the specified period, Alexa offers business insight into how their website compares to others and how it’s perceived by an outside audience.

This rank appears helpful but is almost notorious for its inaccuracy, offering “very rough” estimates of where websites rank on a global scale. However, Alexa (owned by Amazon) continually aim to improve their rank, ensuring it offers businesses beneficial insight.

It will likely come as no surprise to know that Google is consistently rated the number 1 website by Alexa, with each user viewing an average of 7.93 pages per day.

 

JavaScript tag-based analytics

Around the year 2000, it became clear that the log-based web analytics couldn’t offer businesses the metrics they craved, so the JavaScript tag-based method came into play. A snippet of code is applied to each webpage that gathers visitor information and cookies, the information is then bundled into a string of code that is sent to a host for the user to access.

Whilst this is often a higher cost option and means using different privacy settings (due to the use of Cookies), it does offer far more detailed metrics with a high level of accuracy. This method is also able to offer more than just numbers, helping businesses gain insight into trends and user behaviour in real time, without the need to “do the maths”. This was the solution needed to move with the web analytics times and with the release of Google Analytics, this method became commonplace for web analytics tools and solutions.

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