Web analytics is a powerful tool for gaining insights into how your website is performing, but understanding the different types of data can be confusing. In this blog post, we’ll explore the two main categories of web analytics data: qualitative and quantitative.
Quantitative Data Quantitative data refers to numerical data that can be measured objectively. It includes metrics such as pageviews, bounce rate, conversion rate, and revenue. This type of data is useful for understanding how many people are visiting your site and what they’re doing while they’re there.
For example, if you run an online store, you might use quantitative data to track how many visitors are adding items to their cart and how many are completing the checkout process. You could also use it to track which pages on your site are getting the most traffic and which ones have the highest bounce rates.
Quantitative data is typically collected using web analytics tools such as Google Analytics or Adobe Analytics. These tools track user behavior on your site and provide reports that allow you to analyze your data and make data-driven decisions.
Qualitative Data Qualitative data refers to non-numerical data that can provide insights into why users behave in certain ways. This type of data includes things like user feedback, surveys, and customer support tickets. Qualitative data is less structured than quantitative data and requires more interpretation.
For example, if you run an e-commerce website, you might use qualitative data to understand why customers are abandoning their carts. You could send a survey to users who have abandoned their carts to ask them why they didn’t complete the purchase. This information could help you identify common pain points and improve the user experience on your site.