When it comes to User Experience (UX) Research and Design, data plays a crucial role in understanding user behaviors and identifying potential issues that need to be resolved. There are two main types of data that are commonly used in UX research: Quantitative and Qualitative data. It is interesting to me that sometimes the Web Analytics guys think Qualitative is an unnecessary waste of time, so let's dive into how they work together to tell a more complete picture.
First, let's talk about Quantitative data. Quantitative data involves collecting information in numerical form, which can be easily analyzed and measured. This type of data is often gathered through A/B testing and behavioral analytics tools. For example, if a UX Designer wants to understand how users interact with a website, they might use A/B testing to compare the performance of two different design layouts. The quantitative data collected from this testing could include metrics such as click-through rates, page views, and conversion rates. Quantitative is the "What". What are the users doing?
On the other hand, Qualitative Data involves gathering insights and opinions from users in a non-numeric form. This can be achieved through methods such as interviews, focus groups, and usability testing. For instance, if a UX Researcher wants to understand the pain points that users experience when navigating through a mobile app, they might conduct usability testing to observe how users interact with the app and gather feedback on their experience. Qualitative is the "Why". Why are they behaving the way they are?
When it comes to identifying and defining a user issue that needs to be resolved, both Quantitative and Qualitative Data come together to provide a comprehensive understanding. Let's consider an example of how these two types of data can be used to identify a user issue.
Suppose a company wants to improve the user experience of its e-commerce website. By analyzing Quantitative Data such as click-through rates and bounce rates, the UX team may notice that a high percentage of users are leaving the website without making a purchase. This Quantitative Data suggests that there may be an issue with the website's navigation or checkout process.
To gain a deeper understanding of this issue, the team could conduct usability testing and gather Qualitative feedback from users. During the testing, they observe that users are struggling to find the product they are looking for and are encountering difficulties during the checkout process. Additionally, through interviews, users express frustration with the lack of filtering options and the complexity of the checkout steps. This level of detail and filtering would not be picked up from Quantitative alone.
By combining the Quantitative Data on user behavior with the Qualitative insights and opinions gathered from usability testing and interviews, the UX team can identify clear user issues - rather than navigation being the concern as originally thought, the ability to drill down to the desired product is lacking as well as there being an overly complex checkout process. This integrated approach allows the team to develop effective solutions and improvements that address both the Quantitative and Qualitative aspects of the user issue.
Teams that don't have the Qualitative Data at hand are unable to validate prior to launching fixes and enhancements and can end up in an ongoing churn of throwing spaghetti against the wall, hoping to land on the actual problem. The cost of wasted time, throw away work, and impacts to website credibility/customer trust could easily pay to have User Testing in place.