Quantitative and qualitative data can give you insight into what your website visitors are doing, and why they’re doing it.
A simple way to think about web analysis is to think about the opposition between traditional (quantitative) analytics and behavior (qualitative) analytics:
- Traditional analytics gives you insight into what is happening on your site
- Behavior analytics gives you insight into why it’s happening
and consider how you could potentially use data from both types of tools to create the best possible experience for your users.
Quantitative data is a collection of numerical information that answers questions like how many? or how often? Quantitative website data can be measured—it can tell you what is happening on your website, but it cannot tell you why.
When you think about quantitative data and traditional web analytics, you might automatically think of Google Analytics (you obviously wouldn’t be the only one). GA and other quantitative web analysis tools (like the five we mentioned earlier) can tell you how many visitors reached a landing page, how many times they clicked through a funnel, and where they dropped off or exited your site.
Qualitative data (also known as categorical data) is a collection of non-numerical information that can be observed, recorded, and categorized. Qualitative website data can’t be measured, but it can help you understand who your visitors are, and why they take a specific action or follow a common online customer journey on your site.
When you think about qualitative data and web analytics, you might think about researching, surveying, and then arranging insights about your website visitors into categories to learn how to improve their customer journey. For example, the qualitative insights you get as a result of asking open-ended questions could tell you exactly who your audience is, why most customers prefer one product over another, or why visitors are abandoning their shopping carts.