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The conventional web analytics tools are good but not sufficient

Conventional web analytics tools describe visitor behaviour and provide data about visitors, but they don’t provide insight into their underlying behaviour and motivations.

conventional web analytics tools

The conventional web analytics tools

The goal of conventional web analytics tools is to gain insights into the behaviour of website visitors and their use of a website. This information informs decision making on how best to maximise a website’s effectiveness to increase sales in a web shop or get more clicks on a banner ad, for example.

The underlying technology vision

Web analytics tools, as we know them today, utilise a technology vision that was developed approximately 10 years ago. They could be called quantitative system user tools.

Quantitative: because the purpose of the tools is to measure and quantify visitor behaviour. This means discovering how many visitors act in a certain way. Therefore, these tools cannot provide insight into the actual experience visitors have during their time on site.

System user: because the purpose of these tools is to describe how a system is used, and not if visitors who used the system experienced what they came for.

In other words, web analytics tools describe visitor behaviour and provide data about visitors, but they don’t provide insight into their underlying behaviour and motivations.

 

The strength

The philosophy behind this technology vision can be considered a hypothesis-driven approach. This means that, using an experience base, you provide a given type of data output and reports from which you expect the different users of a web analytics tool to benefit.

The strength of this method is drawing knowledge from other people’s experiences and making it a valuable argument for not having to reinvent the wheel.

The weaknesses

This conventional method has three built-in weaknesses:

  • Systems that use this method can provide insight into data that, in concrete and detailed terms, can tell how users of a website behaved. However, the method cannot explain why users behave as they do.
  • It can’t detect new patterns and trends in user behaviour as the tools used are designed to process and display data in one particular way. Basically, the tools are not able to adapt. They can’t display patterns and trends that fall outside of what they’re programmed to recognise.
  • These tools are based on an in-depth thinking explaining how users use a website – not why users use a website, or what the purpose of their visit was. You could say they show the company’s image of the user, not the user’s image of the company.

Conventional web analytics tools are not sufficient

There’s a reason that virtually all companies use a web analytics tool in their daily work of developing websites. Conventional tools are good and do what they’re made to do.

But, it‘s dangerous to make decisions about the development of a site using only conventional tools. They don’t give the full picture.

How do visitors interact with your website’s content, why do they use your website and what trends and patterns can be exploited to achieve your marketing goals or drive more leads and sales for your business?

These are all questions that conventional website analytics tools fail to address.

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Purpose:
Collection of data about browser / operating system usage, screen size, mobile browser, etc.

Value:
Optimizing the user interface to best serve the media the users access the solution on.

Purpose:
Collecting data on traffic to the site, including geography, retrievers, reference sources (search engines, social media, etc.).

Value:
Insight allows for optimization of online marketing campaigns.

Purpose:
Insight into the use of the site, including traffic patterns on the site, use of navigation elements, banner click, etc.

Value:
Optimize navigation and content to support business goals.

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