Discovery research is a UX essential — Here’s how to get started

Design is all about problem-solving. Often, these are quite big problems with complex answers — so designers break the process down into different stages to make it more manageable. These stages generally focus on research, design, and testing/development.

Today, we’ll take a closer look at how designers can move between the first two stages to gather information and test their ideas before fully launching into the development phase.

With this back-and-forth approach, it’s possible to analyze and make informed decisions about which findings to take forward. Discovery research ultimately leads to a final product that meets users’ needs— not just the designer’s assumptions.

What is discovery research?

Discovery research (also called generative, foundational, or exploratory research) is a process that helps designers understand user needs, behaviors, and motivations through different methods, such as interviews, surveys, and target market analysis.

Discovery research is related to product research but involves a broader analysis. Whereas the former deals with all kinds of research — for brands, innovations, products, and more — the latter is solely focused on the product.

How does discovery research help with design?

Discovery research helps designers understand user needs, behaviors, and motivations, which form the basis of key design decisions.

Conducting this early-stage analysis also ensures that designs are based on real user needs rather than the designer’s assumptions. This approach leads to products that feel more like tailor-made creations rather than a broad approximation of what users want.

Finally, it saves time and money by revealing potential problems before they become bigger (and more expensive) issues further down the line.

What are the main goals of discovery research?

1. Understanding your users better: the first and most important goal of discovery research is to help you get under the skin of your users. By understanding user goals and pain points, you can design solutions that address their needs.
2. Improving design decisions: the second goal of discovery research is to improve design decisions. Instead of simply creating a product the design team thinks is cool, you can develop a product roadmap based on relevant data.
3. Save time and money: testing before leaping right into development means you can spot potential problems and work through them, investing time and resources wisely.
4. Creating a shared vision: discovery research can create a shared vision for a project among the design team. Because the research provides a common understanding of user needs, design teams can more easily agree on what to prioritize.

What are the benefits of using both qualitative and quantitative research methods?

Qualitative research is based on open-ended questions and provides insights into people’s attitudes, opinions, and feelings. Typically, this research involves interviews, focus groups, or surveys. Quantitative research, on the other hand, uses closed-ended questions and focuses on hard data, including:

• Performance analytics: websites and apps contain a wealth of numerical data. Google Analytics can show you everything from the number of page views to time spent on a page.
• Target market analysis: demographic research looks at characteristics such as the age, gender, and location of your target market. It’s often collected through surveys and distributed via email.

The benefits of using qualitative and quantitative research methods are twofold.

Qualitative research is often viewed as ‘creative’ and exploratory, while quantitative research is considered more ‘scientific’ and focused. Both types of research reveal something different, each with its strengths and weaknesses.

Qualitative research is good for exploring new ideas and getting an in-depth understanding of user needs. However, it’s often less reliable than quantitative research and deals with smaller samples, which may not represent the wider population.

Quantitative research is good for obtaining hard data and measuring people’s feelings about specific topics or activities. The downside is it’s less nuanced than qualitative research and may provide a less multifaceted analysis of user needs.

Using both qualitative and quantitative research methods, designers can get a complete picture of user needs.

When should you run a discovery session?

Use a discovery session any time the design team needs to move forward in a design and/or when relying on guesswork or intuition is impossible or risky.

Here are some common real-life examples:

• New market opportunities: companies that want to enter a new market must understand user needs and identify opportunities to fill current gaps.
• Rebranding: before rebranding, organizations have to understand how users feel about the current brand, what they want from it, and what issues to avoid moving forward.
• Redesign: when redesigning a product, design teams need to understand what users like and dislike about the current product and how they can innovate in the future.
• Mergers: to ease the transition, merging companies need to understand how employees from both companies feel about the merger and design processes to meet their needs.
• New organizational strategy: when implementing a new strategy, organizations must consider how employees view the upcoming changes and communicate plans and expectations.
• Organizational problems: companies that are struggling with organizational problems must investigate the root cause of the problem to develop effective solutions.

How do you run a discovery research session?

The exact route you take will depend on your goals. Sometimes, you’ll want to use a mixture of methods (the more, the better). At other times, you’ll focus on one or two options. Here are some common discovery research methods.

User interviews

Interviews are a common qualitative research method. They involve sitting down with users and asking open-ended questions about their needs, behaviors, and motivations. Interviews are very useful for understanding user feelings and attitudes in their own words prior to any design work taking place.

Focus groups

Focus groups are a type of qualitative research that involves a group of people discussing a topic together. Not only does this help you find out how people feel about a design, but it also draws out deeper responses as participants build on each other’s comments.

Tips for running a focus group

• The ideal group size is around eight to ten people. To get started, you’ll need to define the topic of discussion and prepare some questions to spark conversation.
• When conducting the focus group, it’s important to moderate the discussion effectively. Keep things on track, offer up discussion points if the momentum slows, and ensure everyone can speak.
• Once the focus group is over, analyze the data you collected. Write a transcript of the discussion, or use diagramming software to help with the analysis.

Surveys

Surveys are a quantitative research method that asks closed-ended questions about user needs. However, including a few open-ended questions is common to provide context for a user’s responses to closed-ended questions. This type of research is useful for obtaining hard data.

Decide what type of questions you want to ask: closed-ended or open-ended. Closed-ended questions have a ‘yes’ or ‘no’ answer, or participants can choose a specific response from a list of options. Open-ended questions can have a longer, freeform answer subject to various conditions.

Ethnographic user research

Ethnographic user research is a form of qualitative research in which you observe users in their natural environment. This type of research is useful for understanding user behaviors and needs.

Tips for conducting ethnographic user research

• Define the scope of your research, and decide on the observation methods prior to session kick-off.
• Choose one to three research methods that suit your resources and goals. Interviews, surveys, and user testing are all valid forms of observation.
• Once you collect user data, collate and analyze it. At this point, you’ll have dense information. Turning the raw data into business intelligence that makes sense for the wider team and stakeholders is important.

Diary studies

Diary studies are a qualitative research method asking participants to write down their thoughts and feelings about a given topic. Journaling gives a glimpse of a user’s thought processes, so you can better understand how they feel about a design or prototype.

Here are some questions you can ask to get the user thinking:

• What were your thoughts and feelings about the design/prototype?
• How easy was it to use the product?
• What did you like or dislike about it?
• Why did you feel that way?
• What problems did you encounter?
• How well did the design meet your needs?

Diary logging techniques you need to know

• Interval-contingent protocol: ask participants to record their thoughts and feelings at fixed intervals (e.g., every hour or every day). Use this type of diary study to understand how people feel over time.
• Event-contingent protocol: ask participants to record their thoughts and feelings after specific events, such as using a feature or carrying out a particular process. Choose this format to study how people react to specific events.
• Saturation sampling: ask participants to keep a diary until they have nothing new to say about the topic. Similar to interval methods, this diary study helps evaluate user feelings over time.
• Choice sampling: give participants a list of topics to choose from and ask them to record their thoughts and feelings about their chosen topic. This study helps you understand how people feel about different design aspects and what issues are most important to them.

Tips for conducting diary studies

• Make sure you store the data securely if the diaries contain personal or sensitive information.
• Define the study’s goals and the logic you’ll use to evaluate the data you receive. Diary studies can be time-consuming for both participants and researchers. As such, ensuring the study is well-designed and the results are worth the effort is crucial.
• Provide participants with an incentive to take part. Diary studies require time and energy, so it’s a good idea to compensate participants with a gift voucher or free product.

Sort cards

Sort cards are a type of qualitative research that involves asking participants to sort a set of cards into groups. The goal is to observe how people think about a particular topic and design intuitive products.

Where else can you find data?

Chatting with users is important, but don’t neglect the wealth of data already at your fingertips. Web analytics, social media, and customer support data can give you insights into how your users think and feel.

• Business data: if you’re working on an internal tool, you probably have access to a lot of data about how it’s used. This information is invaluable for understanding the steps users take to perform an action or solve a problem.
• Web analytics data: this data tells you how people are using your website or app. Use it to understand what pages are being visited, how much time users spend on a page, and what elements they interact with.
• Social media data: social media can be a great way to understand how people feel about your brand. Use social listening tools to track mentions of your brand and see what people are saying.
• Customer support data: if you offer customer support, the data can show you what problems people encounter when using your product.
• Competitor resources: it’s worth looking at competitor resources, such as websites, blog posts, and whitepapers, for ideas on improving or differentiating your product.

Analyzing and assessing discovery research

So, you’ve got all this data. Now what?

It’s time to assess it. Evaluating your discovery research involves looking at the numbers and determining how it fits together. You can write a report or create a diagram or graph to help you visualize it all.

When assessing qualitative data, it is important to consider the following factors:

• The quality and reliability of the data: bad data could send you in the wrong direction. If in doubt, chuck it out.
• The quantity of the data: too much could be a burden when turning it into reports. Too little might give you unreliable results.
• The context of the data: make sure you apply data to the relevant area, but at the same time, don’t look at it in isolation.
• The meaning of the data: only include responses that directly answer your questions. Don’t include irrelevant or unclear data.
• The validity of the data: data goes out of date. Disregard anything that’s no longer relevant.

Final thoughts

Data visualization features, like those in Cacoo, can help turn all those numbers into insight that makes sense.

Resources like persona templates, user story maps, and other research and design diagrams can help you see patterns and trends in the data and communicate your findings to others — including stakeholders who might not have a technical background.

Remember, your top priority is to make the data as understandable as possible for everyone on the team — whatever their background. After all, data is only useful if it’s used and understood!