Jasmin's UXR space

UX research (or User Experience Research or User Research) focuses on understanding user behaviors, needs, and motivations through observation techniques and many other feedback methodologies. This field of research aims at improving the usefulness and usability of products, services, or processes by incorporating experimental and observational research methods to guide the design, development, and refinement of a product.

Working alongside designers, engineers, and programmers in all stages of product creation and idealisation, UX researchers typically follow an iterative, cyclical process in which problem spaces are identified through observation, for which solutions are then proposed. From these proposals, design solutions are prototyped and then tested with the target user group. This process is repeated as many times as necessary. To this end, UX research borrows methods and techniques from a variety of fields, most notably from psychology research. The methods used in UX research can be clustered into quantitative and qualitative research methods. Both quantitative and qualitative methods pose unique strengths and weaknesses. Quantitative and qualitative should not be seen as opposing each other with one being superior to the other, but should rather be used in complimentary fashion to leverage the best of both.

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Table 1. Contrasting few quantitative and qualitative research methods commonly used in UX research.

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Sources:

https://en.wikipedia.org/wiki/User_research

https://www.uxbooth.com/articles/complete-beginners-guide-to-design-research/

 

How does UX research differ from other kind of research?

 

Research isn't simply research. There are different types of research. Think of academic disciplines likes physics and psychology: Both are research disciplines, but they have different interests, ask different questions, and use different methods and analysis techniques to produce insights. In the same manner, there are different research disciplines in industries. Most commonly there are market research, UX research, and data science. Let’s look into the differences:

UX research differs from market research in many ways. While some of the methods used in market research and UX research might overlap (e.g., surveys and interviews), the research interests, research goals, research scale, and research questions asked are different. Market research is concerned with topics around market sizes, market shares, trends, and segments as well as with consumer behaviours, demographics, preferences, and attitudes. Its goal is to keep the big picture and to gather high-level information about target markets/consumers and about the competition. To that end, market research usually exploits larger sample sizes to answer research questions. Market research is important to monitor product performance and competitiveness to maintain and/or increase sales. In contrast to this, the main driver of UX research is not to maintain and/or increase sales; though it contributes to it in the longer run. Instead, UX research is concerned with producing detailed insights based on observations of interactions between humans and technologies. These detailed insights are obtained from usually smaller sample sizes. UX research is also less focused on demographics or what people say (i.e., attitudes), but lays the focus on individual circumstances, context, and what people do and why (i.e., behaviours). The ultimate goal of UX research is, hence, to constantly improve users experiences and interactions with digital touch points.

UX research also very much differs from data science. Similar to the relationship between UX research and market research, UX research and data science also share some methods and analysis techniques (e.g., quantitative data and statistics), but are completely different when it comes to the research fields' research interests, goals, scale, and questions. Data science is concerned with extracting quantitative insights from vast datasets that contain noisy, structured, or unstructured data by means of scientific methods, statistics, data analytics, and algorithms. Oftentimes these data are produced passively, for example, when users interact with a technology. Data science allows to improve digital products as well as to build new data-based products and features. In comparison to the fields of UX and market research, the sample sizes and data points they deal with are huge. Also, their main tasks evolve around building data infrastructure, curating datasets, and coding. While both UX research and data science produce detailed insights based on observations of interactions between humans and technologies, data scientists do so solely based on very large, quantitative datapoints, which are oftentimes produced passively. In contrast, UX researchers rely on conducting studies to extract smaller datapoints. The insights from data science commonly answer what users do or how often they do something, but it is UX research that answers why they do it.

 

Table 2. Simplified breakdown of the differences and similarities between UX research, data science, and market research.

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Sources:

https://ogilvy.medium.com/market-research-or-ux-research-8b0e992e916d

https://builtin.com/data-science

Mitigating risk

There’s a plethora of stories how product were built and turned out to be a huge failure. And sure, no risk, no fun. But much risk, much pain, one can counter. While, UX research (or any research) isn’t a panacea to risk, it considerably helps to reduce risk by identifying early on what users want, need, wish, which aspects of a product cause pain and which gain,… Thereby UX research paves a customer-centric path that leads to a higher chance of success. It’s about striking the right balance between research and risk. But the less research you’re willing to conduct, the more risk you’re taking; that’s one thing you should be aware of.

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Saving time

Investing in research infrastructure and in-house professionals is a big time-saver in the long-run, because conducting research is faster (and cheaper) than developing and redeveloping products and services that were built based on wrong assumptions. Good documentation, transparency, and communication are other big contributors to time saving, because they avoid same or similar research being conducted over and over again. The biggest mistake many make is to overanchor on short-term outcomes, which end up being more time-costly in the long-run, such as not investing in research infrastructure and documentation from early on due to overhead costs and time, while this results in inefficiencies with higher costs and more time investments required later down the line).

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Saving money

According to Usability.gov, half of the time invested in development accounts for redevelopment. Businesses regularly waste vast amounts of money on avoidable issues. UX research prevents you from making mistakes based on unfounded assumptions and thereby can save a great deal of money. It is cheaper to test with few users than it is to develop and redevelop products and services that were poorly built.

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Better Communication

Researchers are trained to separate gut feelings and opinions from data, to translate business goals into testable research strategies, and to back-translate data to actionable insights to drive business value. Researchers are also good in planning things out and documenting as well as visualising data to tell stories. They can help coders to find bugs and technical issues, they can help designers to develop a design vision based on user feedback, they can help marketers with a better understanding of their customers, they can help product managers with product strategy, and they can help decision makers make customer-informed decisions.