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Best 9 user research methods for 2023

Last updated

31 January 2023


Chloe Garnham

Reviewed by

Jean Kaluza

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User experience design (UX) is the process of creating user-centric products. UX helps ensure products are simple, easy to use, and helpful in solving problems. 

To do this, user research is essential. By utilizing user research methods, designers gain insights into user behavior, preferences, needs, and intentions for the purpose of creating products that will benefit people. 

But where does user research begin, and which techniques are most useful? Let’s take a look at the best methods for user research in 2023. 

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What are user research methods?

User experience research methods are techniques that help designers gain data, information, and insights into users

Methods for user research are typically designed to: 

  • Learn about user behavior and attitudes 

  • Identify key pain points, challenges, and problems for users

  • Discover opportunities for solutions 

  • Test what works and what doesn’t 

Choosing the right user research method

Before you choose a user research methodology, it’s essential to consider the individual project. Research methods are not one-size-fits-all. Instead, they ought to be catered to each project to gain the most relevant insights. 

A useful starting point is beginning with the problem in mind. First, ask: “What question should our research be solving?” 

By defining the question, it’s simpler to see what data and information you may need to collect and, therefore, which research methods will be most useful. 

More than one research method may be necessary to discover the key elements of user behavior and preferences. What can be most useful is combining different categories of research to explore all aspects. That’s because research methods generally fall into one of two group sets: qualitative and quantitative, attitudinal and behavioral.

Qualitative vs quantitative

Qualitative data is measured by types of categories. This type of data is discovered directly from users, typically through techniques like focus groups, usability testing, and field studies. Qualitative data helps teams discover why users do what they do and the motivations behind behaviors. 

Quantitative data, on the other hand, is measured by numerical values gained indirectly from users – things that involve what happened and when it happened. Quantitative methods are typically measured by mathematical analysis or data collection. A/B testing and analytics are examples of this method. 

Attitudinal vs behavioral

Attitudinal research is based on users' attitudes towards things – basically, their intentions and beliefs about products and services. That includes what they think about something or what they think they will do in a particular situation. 

Behavioral research, however, is focused on what people actually do. Interestingly, although people might hold certain attitudes toward things, their behavior might indicate something else. 

As the famous Henry Ford quote goes: “If I had asked people what they wanted, they would have said faster horses.”

This highlights the essential need to observe user behavior and discover how people interact with new ideas. 

The most useful research methods

Choosing the right UX research methodology for your team will depend largely on the issue you’re trying to solve. These are some of the most effective and widely used research techniques in UX design

Focus groups

Focus groups are a well-known research method for good reason. They can provide a significant amount of information about users in a short period of time.  

Focus groups involve a small number of people (typically less than ten) and tend to be informal. They’re used to gather information about users, their pain points, preferences, and how they may use a product. 

In a focus group, users are gathered together to discuss a range of topics set out by a moderator. Users will answer questions, offering insights into their thinking to ultimately help designers create the best possible solutions. This is a qualitative and attitudinal research type. 

Focus groups are most useful for gaining: 

  • Insights into how users perceive your product

  • Spontaneous responses you may not discover otherwise 

  • Information about key problems and pain points for users 

  • An understanding of what your users want from a solution 

There are downsides to focus groups, however, such that users may side with the loudest or most vocal person in the room rather than displaying or verbalizing their real, individual opinions. Sometimes this can be just as valuable to learn; other times, it could greatly inhibit your ability to seek the truth. This is why coupling focus groups with a behavioral research method can be very helpful. 


In design, prototyping is critical. Prototyping means creating an early, low-fidelity, and low-cost version of your final product. This can involve something as simple as a series of paper drawings or a more complete clickable prototype of the product. 

Prototypes allow users to see and interact with what will become your final offering. This means you get the chance to gain behavioral data about your users. You can ‘see them in action’, during which issues and roadblocks will quickly become clear. 

By prototyping, you can discover:

  • Key issues with the product 

  • Whether or not users find the product simple to use 

  • Failures, successes, and loopholes 

  • Whether the product is satisfying for users 

A major drawback of prototyping is that, if done at too high of fidelity, it can be costly with not enough flexibility to make changes. On the opposite side of the spectrum, too low fidelity may not give the user a close enough experience to give accurate feedback. That’s why it’s essential to test through all stages of the design process – not just in the beginning. 

Usability testing

Usability testing is critical for all UX design. Usability testing ensures that a product fulfills its intended purpose, that it’s simple to use, and that moments of friction can be tweaked. 

The method involves taking a small group of intended users through a series of tests. The tests help to generate feedback for designers and developers to iterate and optimize their creations. 

Usability tests commonly involve three main groups: 

  1. A UX researcher who runs the tests 

  2. A small group of participants who individually perform a series of tasks  

  3. Other team members who observe the participants as they take the tests (this is optional)

The technique is advantageous as it helps to reduce assumptions – rather than designers assuming they know how users will behave, they gather evidence based on users experiencing the product. This can prove whether a product will be useful or not. 

Usability testing is often completed in conjunction with prototypes in the early stages of the design process. But usability testing shouldn’t stop there. Testing throughout the design, development, and optimization process is critical to ironing out issues and creating products that truly delight users. 

Usability testing templates

Field studies

Field research throws researchers right into the scene. In field studies, users are observed in their own environment rather than a lab or office setting. This helps design teams gain a broad understanding of how people will interact with products in daily living. Ultimately, it helps you to better serve people and their real-life needs. 

Rather than designing based on assumptions about how users will interact with something new, the aim of field studies is to jump into the user’s world and see things from their point of view. 

A team designing smart home devices, for example, will benefit greatly from meeting with study participants in their homes to see how they use devices. They can observe what common daily activities they may want help with and how a device works in a typical home – not an office.  

Field studies can help to show: 

  • How people really use their products 

  • In what context users use products in real-world examples 

  • Issues that may not otherwise come up in lab studies (lack of wifi, unexpected interruptions, unforeseen multi-tasking)

Ultimately, field studies mean diving right into the scene to see how products will work in the day-to-day environment of users. 


Surveys are a useful technique for gathering large amounts of information. They help to build a picture of what users want and need from products. 

Surveys can be a very broad concept. If the right questions are asked, they can provide key information. On the other hand, collated data can lack utility if the data cannot be aggregated into something statistically accurate or measurable.

It’s helpful, then, to explore what survey type will work best for your project. That begins with the decision to use open-ended or closed-ended questions. 

Closed-ended questions end in a ‘yes’ or ‘no’ or have predetermined answers in the form of multiple choice. These are useful for gathering key data and discovering commonalities with users. The resulting data can easily be measured, graphed, and analyzed.

Open-ended questions, on the other hand, allow users to provide more information about their preferences, motivations, and behavior. This resulting data, though more colorful, isn’t easily measured, can’t be graphed, and takes much longer to analyze.

When conducting surveys, it’s also important to choose a large group of participants to ensure statistical relevance against your product’s user base. For market-wide surveys, you’ll need to solve for statistical relevance against an estimated size of the market. This gets a bit into statistics, where researchers would solve for the p-value to determine confidence in the relevance of the data. 

Surveys can help to: 

  • Identify common problems for users 

  • Discover what users want from products 

  • Assess the user’s readiness for new solutions 

  • Learn more about intended users 

Surveys are limited, however, in providing a statistically accurate depiction of what is happening with a given product or market. It’s essential, then, to couple this type of research technique with more qualitative methods that provide greater insight into why those things may be happening  – such as an ethnographic study that aligns with your survey.

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Card sorting

A lesser-known research technique, known as card sorting, can be helpful in discovering how people categorize and understand information. 

In card sorting, users are given a series of cards that represent different categories or concepts. Users are asked to sort the cards into different groups based not on instructions but on what makes the most sense to them. 

This research technique can be very helpful for making information architecture in a website or app easy to access and relevant for users. 

Designers of a social media app, for example, may benefit from creating a series of cards. The cards could represent different aspects of the app, such as settings, sounds, personal information, passwords, usernames, account management, home feed updates, notifications, friend lists, profiles, and more. 

By allowing users to sort these different items, trends may begin to emerge. This can help design teams categorize information within the app into a logical sequence that makes the most sense for users. Ultimately, card sorting can make information architecture easy to access and understand. 

User personas

User personas help designers create products with a specific type of person in mind rather than creating products that are too general. 

To develop user personas, designers will use information gathered in other research methods – things like focus groups, surveys, and usability testing – as well as additional information. The process of creating user personas helps designers to clarify who they’re creating for. It can also highlight gaps in knowledge about the intended audience. 

User personas ensure designers can truly empathize with the intended user and design for them without considering the user as an afterthought. 

A user persona is typically a one or two-page document that includes information such as:

  • Key attributes 

  • Motivations

  • Goals 

  • Pain points 

  • Personality information

An example might be Sally, a 40-year-old single woman who is looking to meet a partner. She has a few key goals. She wants to make genuine connections in the real world. And she wants to be assured of safety – she wants to know that the people she has spoken to online, are the same people she’ll meet in real life. When she uses our product, customer service can share quotes from users that would fall under her persona.

Design teams can ensure that the process of matching with and speaking to other people is simple and painless. They can also bolster their safety by using a Facebook login feature to keep spam profiles to a minimum and thus keep Sally feeling safe on the platform.

Knowing Sally’s concerns, reading things she’s shared, and sometimes identifying a face can form a human need to solve her concerns. The more UX designers know about and empathize with their users as they create the designs –– their wants, needs, and challenges –– the better the team can create meaningful and useful experiences for them. 

A/B testing

A/B testing –– also known as split testing –– is a common and useful behavioral research method. The process involves offering two versions of your product to users. This might be a subject line, a layout, a call-to-action (button), a color scheme, or more. 

In A/B testing, one set of users is shown version A of the product, while another set of users is shown version B. Researchers then assess which version is more effective. This could be measured by clicks, time spent on a task, via survey, or loyalty to the brand. 

A company sending email marketing, for example, might employ the use of A/B testing with email subject lines. One set of users (typically 50%) will receive one subject line, while the remaining users will receive another. The research teams can then assess how many people opened the first email with version A of the subject line compared to those who received version B. 

This type of research helps businesses quickly settle design disputes or make data-backed changes to perhaps an underperforming new feature. 

Another example is the use of different colored buttons. By showing half of the audience a green button and the other half a blue button, researchers can assess which colored button results in the most amount of clicks. 

A/B testing helps clarify for teams what’s more effective and helpful for users. It’s a reliable research technique, as the data gathered is from real-life examples. 

To ensure the tests are reliable, it’s essential to use a large enough group to have statistically significant results. It’s also important to change only one variable at a time to ensure you have a deep understanding of what users prefer in each scenario. 

What can be gained from research methods?

Some of the most well-known companies in the world have succeeded largely because they know their customers and they’ve conducted rigorous user research. Conducting user research can mean the difference between succeeding with a new product or not. 

Some of the key metrics that can come from research methods include: 

  • Higher engagement 

  • Increased conversions 

  • Greater loyalty 

  • Improved customer satisfaction 

  • Boosted sign-ups 

  • Better reviews 

Conducting research can also save the company time and money. That’s because user research can avoid re-works, reduce the risk of failure, and reduce the time spent in development stages. It can also bolster a business case for new projects. 

User experience research is a critical step in producing truly user-centric products and services. It means designing for people and their specific needs while solving key problems. 

User research methods can also help uncover key issues and friction within products in the early stages, which can cut costs for teams. 

Doing the right amount of research can mean the difference between delighting users and solving their problems –– or not. 

Ultimately, by performing user research methodologies, teams gain unbiased data and information from intended users. This helps to overcome assumptions being made by design teams and gets to the crux of what users want and need from products.

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