Skip To Content

Quantitative and Qualitative: Meet The Perfect Research Duo

Lindsey Hart

What do you do when confronted with muddy waters in your research process? Our favorite answer is to get more information to help contextualize the problem and gain a deeper understanding. However, this can be easier said than done since gathering more data can sometimes add to the confusion. This is where multiple research methods come into play within the research process. Quantitative and qualitative research processes work to contextualize each other, helping you to draw conclusions and fill in the blanks where there are holes or questions.

Quantitative & Qualitative Research

The two key types we want to discuss are:

  • Quantitative Research: Number-based information
  • Qualitative Research: Word and thought-based information

Quantitative

Quantitative research yields data expressed in numerals. One method to capture data is tracking interactions. Google Analytics 4 is a powerful tool that can accumulate massive amounts of quantitative data to give you direct insight into how users interact with your site. Another way to collect quantitative data is through surveys using number scales and experimentation with a clear, measurable numeral that is being tracked.

Another good way to think about it is that quantitative data will more commonly yield a how and a what for the questions you’re asking and numbers that can back that up.

Qualitative

Qualitative research focuses on more nuanced takes that involve direct feedback through words from participants. Methods for this research include focus groups, one-on-one interviews, and open-ended survey questions, which participants can answer without any constraints. Researchers can get further insight directly from the audience you need to hear from. 

When gathering qualitative data, you are more likely to identify new problems that may have been unforeseen or find a way to your questions.

The need for both

With any data collection, you can run into bias, whether from within or from participants. An internal bias can look like your researcher making assumptions based on their worldview and experience, which is not always detrimental but something to keep an eye on. With this established bias, it’s easy to make assumptions about something entirely outside your realm of knowledge based on a desire to conclude using what can be one-dimensional quantitative data points.

Conversely, within qualitative research studies, an inherent bias can sometimes come into play in the groups based on several factors. In focus groups, the social pressure to agree could skew data, or even in one-on-one interactions, there could be a desire not to offend or a lapse in memory. That’s why gathering diverse views is even more critical, so you look at things from multiple perspectives. 

Additionally, quantitative research can help form the questions that need to be asked in the first place. Otherwise, bias from the researcher can mitigate what otherwise would be a clear pain point that may have been missed by not reviewing the numbers first.

When working with both types of research within the same study, you are inherently more likely to get a holistic view that ultimately leads to more accurate conclusions overall.

A real-world example

Poverty is a complex and challenging subject to breach and one that comes with many preconceived notions and biases regarding how it’s translated culturally. A person’s relationship with poverty, whether being subject to it or an observer who isn’t impacted by it, can harshly define the views of those who are afflicted with poverty. 

One of these untrue biases can be the assumption that people in poverty are lazy and unhealthy by choice. Quantitative studies were done to find that there is a disproportionate amount of obesity within communities that are food insecure and in poverty. Researchers could have quickly concluded that this confirms their bias is propagated in society, and people in poverty have a proclivity for bad food.

Now let’s look from a research standpoint

However, when qualitative researchers entered these communities and talked with food-insecure people, they noted a significant need for access to healthy foods. These spaces were often set up to have fast food as a cornerstone of the available food in neighborhoods.

Young office manager working with papers and computer working at office. Man in a suit working. | Quantitative and Qualitative Research

Photo Credit: Envato Elements

Once this extra layer of context is brought into light, it becomes clear that we are products of our environment, and if the environment is unhealthy, that will echo to the people subject to it. While this is a more extensive study than what we would do in our four walls, a consideration in a checkout process or a navigation layout shows how important it is to understand the environment in which your users exist. 

We could assume the checkout process isn’t running as smoothly as possible because of a layout issue. After talking directly to users, it may be revealed that the UX text that gave instructions was missing since they weren’t familiar with that checkout process. This can be applied to product descriptions, navigation layouts, and forms. Directly addressing user needs and bolstering the feedback with actual data is a definitive way to identify meaningful improvements in online environments like websites.

Our preferred method

When combining different research types, like quantitative and qualitative research, you can clearly see the value of approaching a problem from multiple perspectives. While numbers create confidence and can be exciting to conclude from, those conclusions must be ultimately humanized with qualitative research to confirm or deny any inherent bias that may be present.

In our UX research, we consult numbers and statistics that can be gathered and contextualize those with user testing so we can listen to the real insight of an actual user experiencing the site. This will often confirm much of what we initially think, however without that confirmation, these thoughts are assumptions, educated or otherwise.

Join us in brightening your digital future