User experience research is a principal element of today’s web design process. This method allows users to take part in the development of websites and software by giving designers feedback about what they want – and expect – from a high-quality product. This feedback comes from both qualitative and quantitative methods of research. Unfortunately, very few people understand the critical differences between the two. A lack of knowledge during this step of development often leads to misinterpretations that can be detrimental to the success of the final product.
The quantitative method seeks out information that can be expressed in numbers. This information is often collected using automated data collection instruments, such as electronic surveys. This means that the material can be gathered quickly, saving your company both time and money. Unfortunately, when using the quantitative method alone, there can be a data deficiency. Quantitative data gives you the “what,” but not the “why,” so you are only looking at half of the information necessary to make educated decisions. This deficiency can lead to errors when it comes to the actual design of your product. Additionally, data must be run through statistical analyses in order to derive its importance. This requires someone with detailed knowledge of both descriptive and inferential statistics, who is experienced and able to make inferences from numerical data.
Example: Quantitative Data
You work for a film advertisement company. You decide to send out a survey to collect individual’s demographic information (age, gender, socioeconomic status, etc.) and movie genre preferences, with the intention of finding target audiences for the upcoming release of a film. From your survey you conclude that females would prefer to see a Romantic Comedy, while males would prefer to see an Action/Thriller.
Using only quantitative data to form your designs would be similar to reading a book where every other word had been erased. Doesn’t make a lot of sense does it? Qualitative research can fill in the blanks. Qualitative data focuses on comprehensive, deep descriptions about the characteristics of things. This includes behaviors, desires, routines, and a variety of other information most people find essential for user-centered product designs. Where quantitative research has a relatively easy and fast collection process, gathering qualitative data is a bit more involved. This is because the collection of qualitative data usually requires an in-person (or phone) meeting, where the researcher can ask a number of follow up questions and dig deeper into a participant’s answers. While this process can give you a lot of great information, it can also be time consuming and expensive.
Example: Qualitative Data
As a follow up to your survey, you ask several men and women to come in for a short interview about their movie genre preferences. Here, you learn that women prefer to see movies that portray characters they can relate to easily. This is usually Romantic Comedies, whose cast and plotlines center around the lives of females. On the other hand, males prefer to see movies that are exciting, and have fast paced story lines – like Action/Thriller films.
So, would you rather: conserve time and funds, but only be able to see half of the picture? Or, spend a lot of time and money for the ability to dig deeper into the “why” behind your customer’s actions? What if you didn’t have to choose? Understanding the different types of data that are produced, and the different conclusions that can be drawn, from both methods is important whether you are performing the research yourself, or bringing in a consultant. But, what is even more important is understanding how the two can work together to uncover the bigger picture.
Example: Quantitative and Qualitative Data Working Together
When the new Wonder Woman movie comes out – which has been classified as an action film, but portrays a strong female lead and has many supporting females roles – you are tasked with deciding who your advertisements should target; males, females, or both. If you were to rely only on your quantitative data, which showed that males alone enjoyed action movies, you would likely build male focused advertisements. But, if you were using a combination of qualitative and quantitative data, you would see that both male centered and female centered advertisements would be successful because, while it is an action film, the movie also portrays characters that females can relate to.
Though this example may be simple, it shows how taking shortcuts in your research can have serious implications for product success. It can be difficult to know, not only, what kind of research will answer the questions your organization has, but also how to conduct that research effectively. Working with a company that is both knowledgeable and experienced in the field will help you get the most from your research. Explore Discida’s research options now.
Bailey Moulden contributed to this article.