Card Sorting: Understand Your Users For Better Information Architecture  (+Best Practices)

Card Sorting: Understand Your Users For Better Information Architecture (+Best Practices)

Have you ever been on a website where you’re looking for something, you click on a category but it’s not there, so you try a different category. 

Nope, still can’t find it. 

Most people will give up and leave if they visit a site and can’t find what they are looking for. 

This is why card sorting is important, it helps your users find what they want and easily navigate through your website, this is especially important if you have a complex information architecture.

What is Information Architecture (IA)?

Information architecture focuses on the organization, structure, and labelling of content in an effective way so that users can find information and complete their tasks easily. The best way to figure out the information architecture is to involve your users in the planning stage by conducting a user research method: Card Sorting.

What is Card Sorting?

Card sorting is a UX research method to derive users’ perceptions of information space. This is done by recruiting a group of people, that are reflective of your target users, to arrange individual labels according to groupings or criteria that makes sense to them. They can be asked to label these groups as well. 

cards sorting

Photo by Pixabay

By doing this, we can discover how your target users’ domain knowledge is structured, and an information architecture that meets your users’ expectations is created as an end result. 

For example: You’re designing a car-rental website, and there’s an offering of about 100 cars for customers to choose from. How would you best organize all the vehicles into suitable categories for customers to easily browse and find what they are looking for? 

Technical terms such as family car, full-size luxury car, and executive car for categories may not make sense to your users, and they may not be able to differentiate between these categories. The best way to find out what terms and categories make the most sense to your customers is to conduct card sorting: ask your customers to organize the vehicles into groupings that make sense to them and see how the patterns emerge.

This technique aims to uncover how a target audience’s domain knowledge is mentally structured. Consequently, this insight is then employed to create an information architecture(IA) that matches users’ mental expectations.

For all intents and purposes, card sorting isn’t a collaborative method for creating navigation. It is, instead, a tool that helps UX designers to better understand the people they are designing for. 

Is card sorting good for UX?

As we have established, card sorting helps when creating the foundation for a robust information architecture. Fundamentally, a good IA forms the building blocks of efficient system navigation that closely matches users’ expectations. 

As a result, with insights gathered from a card sort, UX researchers and designers have sufficient information to: 

  • Build optimal structures for their websites 
  • Decide on what to put on their homepages 
  • Label categories and navigate

Generally speaking, card sorting is mainly useful in two cases:

  • When UX designers want to dissect how people understand and group disparate concepts. This understanding can help them to design better products for users.
  • When UX designers seek to dramatically improve an existing design. Fundamentally, in such instances, they will seek to make their information presentation more predictable for users.

Is card sorting qualitative or quantitative?

Though relatively straightforward, card sorting is a very powerful technique. It can unravel different dimensions of how users think about categories and concepts. Or how they describe them, and this can be incredibly useful when organising information in a manner that is easy to find for general users. 

That being said, card sorting is predominantly a quantitative user research method for measuring the similarity of how users group their sets of information.

How to Conduct Open Card Sorting?

As we have established, card sorting is used to discover how people group concepts into categories in a manner that is logical to them. The grouping data is then analysed with cluster analysis to offer a visual representation of the correlated groups or categories. 

This information is shared with the design team and developers to meaningfully structure the content and navigation of the website to support user goals. 

In practice, the process of card sorting is fairly straightforward. The participants are given a set of cards (typically paper index cards) with example content written on them.

They are then asked to sort the cards into piles based on what they perceive is similarand then describe the groups they make. This can be done with predetermined categories (closed card sort), or without predetermined categories (open card sort). Regardless, results are recorded, analyzed, and applied. 

  1. Choose a set of topics: There should be 40-80 items that represent the main content on the site, each topic should have its own individual index card. Note: Do take care to avoid topics that contain the same words as the users will tend to group them together. 
  2. Organize topics into groups: Shuffle the index cards to remove any possible bias and give them to the user. Ask the user to look at the index cards one at a time and to organize the cards together in groups that make sense to them. The piles can vary in size, and if the user isn’t sure where to place a card, it’s okay to leave it to the side in an “unsure” group. 

Note: Do take care to reassure users that they can change their mind as they go, they can move the index cards from one group to another during the process or even to split off a pile into several new piles. False starts are to be expected since card sorting is a bottom-up process. 

Pro Tip: Ask users to think out loud during the card sorting process: to speak aloud or verbalize their thoughts. Doing so allows you to understand the user’s thought process better, it provides detailed information and allows the user to take their time to analyze. 

  1. Label the groups: Once the user is done sorting all the index cards into groups, give them blank cards to write down a name or label for each group they have created. This will help to reveal the user’s mental model of the topic space, and possibly provide new ideas for navigation categories. Note: It’s vital that this step is done only after all the groups are created. If this step is introduced earlier, the user may lock themselves into categories whilst trying to sort the cards into groups. 
  2. Debrief: Ask the user to explain the rationale behind their thinking and the groups they have created. You may even follow up with questions such as:
  • Were there any items that were especially easy or difficult to place into groups?
  • Were there any cards that you felt belonged to two or more groups?
  • What are your thoughts about the items left in the “unsure” pile?
  1. If needed, ask the user to break down large groups or group together small groups: Avoid doing this during steps 1-4, only do this once the user’s preferred grouping has been defined to their liking and after the initial debrief. You may ask the user to break down a large group into smaller groups or even ask them to group small groups into a larger category. 
  2. Repeat the steps above with 15-20 users: Conducting the card sorting with sufficient users is important in detecting patterns, we recommend at least 15 users to derive enough reliable data. 
  3. Analyze: Look for common groups, categories, themes and items that were commonly paired together. In analyzing the data, if you notice that there were some items that were repeatedly left off in the “unsure” pile, think about why that is. Perhaps the cards weren’t clear enough or it seemed unrelated, that’s why it’s helpful to ask the user why they have left these items in the “unsure” pile.

Also, read: How Many Test Users Are Enough for Card Sorting?

Types of Card Sorting

Open vs Closed vs Hybrid Card Sorting

Open card sorting is the most common, and it follows the steps described above, where users are free to assign the group labels for the groupings they have created. 

Closed card sorting is when a predetermined set of categories are provided to the user, and the user is asked to organize the individual index cards into the predetermined categories. 

Closed card sorting is useful in evaluating whether an existing category structure supports the content well. It doesn’t exactly reveal how users conceptualize a set of topics. Rather, it’s exploited to evaluate how well an existing category structure supports the website’s content, from a user’s perspective. 

However, a drawback is that it isn’t reflective of the users’ mental model.  Instead of closed card sorting, tree testing is a good alternative for evaluating navigation categories. 

Hybrid card sorting is a combination of open and closed card sorting where the user can start by sorting cards into predetermined categories but have the ability to create their own categories if they want to.

Moderated vs Unmoderated Card Sorting

Moderated card sorting includes the debrief step, which provides an opportunity to gain qualitative insights from the user by asking questions, and investigating for further understanding. Moderated card sorting takes a bit more time and is more costly compared to unmoderated card sorting, but it’s a small price to pay for further insights. It is usually guided by a facilitator wherein he/she asks questions, probe for further understanding, and ask about certain cards as needed. 

Unmoderated card sorting entails users organising content into groups independently— with no interaction with a facilitator.

It is faster and cheaper compared to moderated card sorting as the moderator doesn’t need to speak with each individual user but unmoderated card sorting lacks qualitative insights. 

This form of card sorting is suitable as a supplement to moderated card sorting, for highly distinct audience groups where there are 3 different audience groups with 20 users each, it will be very costly and time-consuming to conduct moderated card sorting with all the users. It would be a good idea to conduct moderated card sorting with 5-10 users of each group followed by unmoderated card sorting for the rest of the users of each group.

Paper vs Digital Card Sorting

The traditional way of card sorting is using paper where topics are written on index cards and these physical index cards are given to users to create groups on a large table. 

The main advantage of this method is that there’s no learning curve for the user, and it’s also a flexible process where users can move cards around easily. It is also easier to move around physical cards on a large table compared to manipulating multiple objects on a computer screen where everything can’t be seen in a single view. 

The main disadvantage of paper card sorting is the labour-intensive work where researchers have to manually document the groupings of each user and then input all the data into a tool for further analysis. 

Digital card sorting is done using a software or web-based tool that simulates the card sorting process, the user can drag and drop the index cards into groups. There is a slight learning curve for this method as some users may not be very tech-savvy. 

However, it’s most convenient for the research team as the software can analyze the results and generate the findings: revealing which items are commonly grouped together by all the users, the category names users created and the likelihood of two items being paired together. 

The main disadvantage is that technical issues may occur, causing frustration and barriers for users in creating the exact groupings they want. Digital card sorting is often preferred in this time of remote work and remote user research and it also allows you to conduct card sorting with users that would otherwise be geographically unavailable.

Remote card sorting vs face to face card sorting

Remote card sorting involves participants sorting cards independently on their own digital devices. Generally, participants can perform open or closed card sorts remotely using dedicated programs that subsequently analyze the data for the company.

Face-to-face card sorting involves in-person sessions with an observer present. In practice, users are given a set of cards to move around and then subsequently asked to talk through their thoughts, and the reasoning behind their decisions. As a result, the coordinator is given the opportunity to clarify any confusing observations to gain a better insight into why the user made their choices.

Card Sorting Tools

There are different tools available for conducting a card sorting exercise. For example, papers, cardboards, or an online card-arranging program for remote sessions. 

Some examples include:

  1. UserZoom UserZoom is known for its clean and intuitive user interface however you do need to buy the whole package that includes tree test, click test, survey, basic usability test and more. The card sorting tool has a feature in which you can invite users to your study in multiple ways, and it also allows you to segment your users into demographic groups. UserZoom allows you to invite your own participants or select participants from their database of over 120 million users. Pricing: Available upon request 
  2. OptimalSort OptimalSort has a simple user interface for users and unlike UserZoom, the card sorting tool is available as a standalone product. Stakeholders can be invited to view the data in the results interface. They have a card sorting demo for you to try for yourself and a free version available for card sorting tests but there’s a limit of 30 cards with 10 responses and 3 sessions per study. Price: Individual plan is $166 USD/month, the team plan pricing varies depending on how many people are in the team. For a team of 3+ seats, the price is $153 USD/month per user. 
  3. usabiliTEST UsabiliTEST offers a reliable card sorting tools for open, close and hybrid testing, with built-in data and analytics. They allow you to track all the answers the users give and even have a feature to send out automatic reminders to users. They offer a free trial for 48 hours where you can try out the tool without a limit on the number of tests you can do. Price: Premium plan is $24.95 USD/month, pro plan is $224.55 USD for a year 
  4. Proven By Users Offering a clean and simple user interface, this card sorting tool allows you to see them in preview before going live. It allows a feature where the user can create card subgroups or duplicate cards easily, and you can segment the users. The research data can be graphically represented in matrics and dendrograms and the data can even be downloaded in CSV format. Price: $39.95 USD for a month, $69.95 USD for 2 months, $399.95 USD for a year. 
  5. xSort xSort isn’t available on Windows or Linux, it’s only fully integrated with Mac (Intel and PowerPC-based Macs) and their user interface approach is to visually simulate a real-life table with index cards. It provides a variety of open, closed and hybrid card sorting, and the users can create subgroups. In addition, the statistics are updated in real-time. Price: Free

Best practices for card sorting

1. Understand the information available on the website

Similar to any research technique, it’s imperative to clearly establish the objective of the project and what you seek to learn. In this instance, such a goal-oriented approach will help you to determine whether card sorting is the best approach to learn from users. 

Card sorting provides you valuable insight into the perspective of your users. It tells you about how they comprehend different concepts or ideas, and how they exactly feel about them.

This can be used during the selection of potential new features or different naming conventions to get prospective users’ first impressions and instincts of the product.

2. Number your cards

Always number each card to make analysis easier after the session. This consequently makes employing a table or spreadsheet for listing topics easy to understand.

3. Design your cards well

There are no hard or fast rules that dictate card design. However, it’s recommended to ensure cards are meaningful for participants. As such, it is imperative to always test cards with your audience to ensure that they understand the meaning of the information on a card. And can easily group them in a consistent and coherent manner. 

4. Conduct a trial run

Always conduct a trial run with colleagues or friends before performing your first card sort to uncover any typos, errors or misunderstandings that may arise. This can prove valuable since missing any errors may adversely throw off the real user data.

5. Limit the number of cards. 

While it can be tempting to desire that participants sort through all of your content. It’s important to be mindful of participant fatigue. So, limit the number of cards to 30 to 40, especially for an open sort.

6. Keep the topics short and to the point.

Strive for the topics to be to the point to ensure that the cards are easy to readwithout compromising the content. In fact, consider randomising the order of presentation to ensure that content has a chance to be sorted earlier in the session.

7. Provide a time estimate

Always provide the participants with a clear estimate of how long the card sort might take to help them gauge the required time and effort.

8. Use both open and closed card sorting

Consider using both open and closed card sorting as one enables you to learn what goes together. While the other helps you to test out your labels to determine if they are intuitive enough for your participants.

What is reverse card sorting?

Reverse card sorting, also known as tree testing, is a technique for evaluating and validating navigation categories that involves users trying to find items by surfing through a hierarchy. But without the influence of navigation aids and visual design. 

The technique validates the effectiveness of tags and the existing structure of the website. 


Card sorting is highly useful in understanding how users think about your content, and in the arrangement of information architecture. It helps companies to organize their content in an effective way that is reflective of the users’ mental models, making it much easier for customers to find the information they want and complete their tasks with ease.

Remember to always consider the card sorting objectives, tools, content, and people, despite it being a relatively straightforward process. Ensure to perform it properly and pay close attention to each element. 

Lastly, this user research methodology works best at the beginning of projects, especially if you’re working on redesigning a site. 

What is Data Analytics – Explained

What is Data Analytics – Explained

We are in the 21st century, where data analytics is one of the most popular terminologies and is used nonchalantly across industries. 

It is because a lot of decision-making has shifted from gut-based and impromptu to data-backed. It not only includes designing but has seeped down to user experience too. 

User experience design (UXD) is a process that goes beyond the design of a product or service. It encompasses understanding how users interact with a product or service and designing it to evoke the desired response. Data analytics has a significant role to play in UX design, as it helps us understand user behaviour and how best to meet their needs. 

In this article, we will explore what data analytics is, its types, the steps involved, how it can help UX design, and some common use cases where we can apply its varying techniques. So stay tuned!

What is data analytics?

90% of corporations value data analytics as an essential competency to ace. But what is data analytics?

Data analytics and optimisation is about using raw data to improve decision-making. It can help you identify patterns and trends in your data, which we can use for planning and optimisation purposes. 

Data analytics can help understand customer behaviour and preferences so that better customer service can be provided. In the end, data analytics helps organisations make better decisions faster by identifying opportunities and risks early in the decision-making process. 

data analytics

Photo by Lukas

What is the typical process that a data analyst will follow?

Here are the steps a data analyst follows while conducting data analytics – 

Step 1: Define the question(s) you want to answer

Data analysts typically start by understanding the business goals, which can be gleaned from business stakeholders. It will help you select the data collection methods most relevant to your inquiry. Once you have a good understanding of what information is required, you can then plan out the most suitable approach to collect the data as well as the approach for analysis and interpretation of data. 

Step 2: Data collection

Gathering data is an important step in any analysis or research. It is the data analyst’s job to unearth all the relevant information and compile it in a reliable and accurate format. It will allow business decisions to be based on sound analytics rather than assumptions or guesses and shape a more secure future. Data could already be available (for example, past traffic and usage data of an existing mobile app) or it would need to be collected over a period of time (for a newly launched website).

Step 3: Clean the data

Now that you have ample data at your disposal, it is imperative to understand that not everything will contribute to improving the user experience or  UX design process. So, you need to clean the data to filter unwanted, disconnected, or incomplete entries before moving on to the next stage. 

Step 4: Analyse the data

The most important use of analytics is the ability to execute exploratory data analysis on the data which has been collected and cleaned. 

By using data visualisation tools and dashboards, you can keep track of everything from customer engagement rates to website clicks through conversion rates. These are some very essential data points when planning and executing effective UX-related strategies.

Now that you have analyzed the data, the next vital step is to interpret your findings and validate them against your expectations. It will enable you to discover unforeseen trends and patterns crucial for your decision-making. 

Step 5: Visualise and share your findings

It is also helpful when you are able to share the visualised data to different people in the organisation so that they can harness the benefit to make their decision. Sometimes it is also possible to provide live data visualisation in an online dashboard so that the business stakeholders/managers can keep monitoring certain important events. 

Data analytics techniques

Data analytics has become an essential tool for UX design. It helps improve the quality and design of an interface by revealing user insights (e.g. how quickly a user takes to go through a set of steps using your interface). This information can be used to make changes, such as improving navigation or adding new functionality. 

But it is vital to understand that there are a lot of data analytics techniques, and not every methodology can be helpful for your needs. 

Therefore, you need to understand them all and carefully choose the ones that you can use. Following are some of the most commonly used types:

Descriptive analytics

It is a data analysis technique that helps you understand trends and changes in your data. This can include calculating medians, mean, standard deviations, etc., to understand tendencies and variations within a data set. 

The results help UX designers to understand customer behaviour. For example, analysing how users interact with a trendy website helps the designers to analyse if it is a factor that could contribute to higher sales. 

The results of the descriptive analysis are usually the starting point for in-depth statistical analysis. 

Diagnostic analytics

Unlike most data analytics types, diagnostic analytics focuses more on the reason behind the occurrence of an incident. It uses a myriad of data inputs and hypotheses to reach an outcome.  This involves checking various factors like patterns, trends, and data relationships to understand what caused a problem or outcome. 

For example, websites relying on customer data use diagnostic analysis to understand why customers do what they do and how their behaviour can help improve the product and UX. 

A customer may have various reasons to abandon a product in their cart. By gathering feedback from the users, an analyst can diagnose if product design or usability is one of the reason behind abandoning it mid-way.  

Predictive analytics

Predictive analytics is a vital tool in business operations that helps them predict future possibilities by analysing historical data. It allows you to extract insights from data so that decisions can be made better and actions are taken accordingly. 

For example, an ecommerce platform may use it to forecast sales based on past year sales data and other external factors like seasonal behaviours, market economics, etc. This information can then be used to create new marketing campaigns or plan for new products/services. 

Prescriptive analytics

It is a process of extracting insights from data to make recommendations that can help business decisions. It involves using testing and other techniques like mathematical modelling, A/B testing, etc. in collaboration with predictive analytics to recommend solutions for achieving desired results. 

For example, a website may want to utilise prescriptive analysis to determine the most efficient page design, CTAs, etc, that optimise user interaction and sales. 

Regression analysis

A regression analysis is a data analytics technique that helps you to understand how users interact with your website or product. By analyzing how different user segments behave, you can identify and estimate the relationship between variables. It helps correct errors in your data so that the user experience is improved. 

It is done by checking the correlation between a dependent variable and independent variable. 

For example, you budget for an email marketing campaign and want to check how much revenue is generated using the same. In this case, the email marketing campaign is your independent variable, and the sales revenue is your dependent variable. A regression analysis helps to find out a positive, negative or neutral correlation between the two variables, which in turn helps you make an informed decision on future budget spending. 

Factor analysis

Factor analysis involves identifying patterns in user behavior and using this information to improve the design of products or services. The idea behind it is to reduce a large number of variables to a smaller number of factors. It concentrates large datasets into smaller, more manageable samples, enabling users to identify hidden patterns. 

The results can be used for further analysis, ensuring you get deeper insights regarding their UX and how people react to changes in your design ecosystem.

In web design, for example, it could be used to understand relationships between various consumer behaviours or traits. A UX designer can conduct a consumer survey with a set of questionnaires to identify the underlying factors that drive variations within the data. 

Cohort analysis

Cohort analysis is a data analytics technique that helps you understand user behavior and is a subset of behavioral analytics. It takes the data from a given dataset rather than individual units. This means that it involves grouping similar customers based on shared behaviours. These cohorts share similar characteristics, which helps identify patterns throughout the customer lifecycle.  

A website, for example, may group its visitors based on their sign-up date, gender, age or demography. They can then track their purchases and cart abandonment to reveal differences in purchase behaviours of different groups. This, in turn, can help the designers or marketers to make more informed decisions on product changes, marketing strategies, etc. 

Cluster analysis

Cluster analysis is a research technique that sorts different data points into clusters for decision-making. These are internally homogeneous and externally heterogeneous, which enables the team to find the data distribution in a given dataset and make decisions accordingly. 

For example, a website launching a new product may want to segment its customers based on their purchase behaviour. Cluster analysis can be used here to identify those with similar purchasing habits, which can help create a targeted marketing plan. 

Time series analysis

One of the most important ways to collect data is through time series analysis – understanding how customers interact with your product over time. It will allow you to identify changes in behaviour, use that information to improve design decisions, and measure the impact on customer satisfaction. 

Charts and graphs are great tools for visualising complex data in a way that’s easy for humans (and machines) to understand. By using them wisely, you can create informative and helpful designs for users – rather than pretty or flashy ones.

Since time series analysis is used with non-stationary data (those that fluctuate with time), it is an excellent tool for ecommerce platforms to make more informed decisions.

Sentiment analysis

When it comes to user experience, nothing is more important than understanding the sentiment of your users. By doing so, you can design a better product that meets their needs and expectations. 

Besides improving user satisfaction, sentiment analytics also plays a vital role in customer retention and suggestion-based improvement processes for products and services. Knowing what users like helps you create content that’s engaging and useful – ultimately leading to long-term success for all involved!

An application, for example, may analyze its customer reviews to determine the overall sentiment on its usability and design. This could then help to make changes/alterations in the design to improve customer satisfaction. 

Social media analytics

This is the process of collecting and analysing data from social media platforms to get insight and make better business decisions. It can be done by tracking metrics like the number of social media followers, engagement rate, etc. A marketing team can analyze the performance of their social media campaigns on platforms like Instagram and Facebook and later analyse the results to optimise their campaign. 

Cross platform analytics

It refers to the process of collecting and analyzing data from multiple platforms and devices to get an overall picture of customer behaviour and how they interact with a brand at various touchpoints. 

An ecommerce company, for example, can track the customer’s browsing and purchase behaviour on their mobile app, website, or retail store. A combined analysis of all these data can help them make informed marketing decisions and create better customer experience strategies for the future. 

Loading speed analytics

This process measures and analyses the time it takes for a website or application to load. It aims to identify the slow-loading elements which may negatively impact user experience. Once identified, these can be optimised to provide better UX to the users. 

Website owners, for example, may use tools like PageSpeed Insights or GTmetric to check loading speed and analyse the results to make improvements. 

Heatmap for user behaviour

Heatmaps are a graphical representation of user behaviour on a web app or website. Here, colours are used to represent various interactions. These are used in UX research to see how a potential customer interacts with a page, hovers, scrolls, clicks, etc. It can help websites understand which products receive more interest, where the user stops on the page, etc. 

For designers, this information can be vital to create better website designs and making more effective layouts to improve UX. 

Data analytics examples

Photo by Pixabay

Data analytics examples

Here is how data analytics can change UX designing – 

  • Measuring the performance of different user interfaces, so that designers can user test, rethink and improve accessibility and usability.
  • Finding the potential areas or points which user is leaving without completing the purchase. Then further UX research can be carried out to uncover the reason for such abandonment. 
  • Optimising UX of the conversion funnel, which then contributes to high sales.
  • Finding out instances of rage-clicking and figuring out ways to minimize it. 
  • Rearranging content to ensure it goes with the user’s search intent. 


Data analytics can play a vital role in the design process of user experience (UX) projects. 

By understanding user behaviour and trends, data analytics can help designers make informed decisions about the design of user interfaces. 

In addition to helping to design better user experiences, data analytics can also help optimise the design processes and improve the quality of user experience design. 

Establishing a seamless experience for your users is a priority in terms of sales achieved and contributes to better business outcomes without significantly increasing manual labour. 

Talk to our user experience consulting team on how you can explore and choose the right data analysis technique for your project.

UX Methods & Tools in Asia Survey

UX Methods & Tools in Asia Survey

Ever wonder what are the research or design tools available in the market that could benefit your career in the UX industry? Yet, when you try to look around, you’re just bombarded with… So many tools, and so little time to explore. Fret not, we’ve got you covered! From the list of available tools to the reasons for using them, we’ve compiled an exhaustive list for all your UX research needs after surveying UX researchers and designers across Asia.

Here’s what we will cover in this article. You may continue to read on or skip to specific sections by clicking the links below:

    Who We Surveyed

    We’ve collected responses from all around Asia, and here are some information of our survey respondents:

    Qualitative UX Research Tools

    Research, research and more research, you just can’t escape from them in the UX industry. Some of the more common qualitative UX research techniques include Card Sorting, Customer Journey Mapping, Online User Interviews, and Usability Testing.  

    Card Sorting

    Card sorting is a research technique used to understand how users would organize, group, or label certain information within a site. To conduct this research method, researchers can use either online tools or offline tools such as sticky notes, paper, or actual cards. We found that most researchers in Asia prefer online tools now, but some still use offline tools occasionally.  

    Here are the most used card sorting tools by researchers: 


    And here are the tools researchers are looking forward to try in their next research project:

    1. UXbeam
    2. Figma

    Customer Journey Mapping

    Customer Journey Mapping shows the interaction between the organization and their customer, allowing them to have a better understanding of their customer’s needs and expectations. With that, they will be able to plan and strategize on what needs to be worked on and improved further. Interestingly, we found that offline tools such as blackboards (or whiteboard or empty walls) are still preferred by most researchers in Asia.

    Here are the most used customer journey mapping tools by researchers:


    And here are the tools researchers are looking forward to try in their next research project:

    1. Adobe XD
    2. Miro
    3. Smaply
    4. UXPressia
    5. OmniGraffle

    Online User Interviews

    User Interviews, which involve collecting information directly from users, can be considered one of the most popular methods in UX research. The COVID-19 pandemic highlighted that even though physical interviews are not a viable option, there are still many online platforms that could support user interviews. Although each platform has its ups and downs, we found the top tools loved by most researchers in Asia.

    Here are the most used online user interview tools by researchers:


    And here are the tools researchers are looking forward to try in their next research project:

    1. Maze
    2. Direct interviews
    3. Dovetail

    Usability Testing

    How do you know whether users are able to complete tasks successfully with ease? Usability Test is the answer! A usability testing session is a great way to watch how users actually use your product be it a website or physical product. Why? Because good design is not enough, we need to make sure users can enjoy using the products and understand the problems the “real” users are facing.

    Here are the most used usability testing tools by researchers:


    And here are the tools researchers are looking forward to try in their next research project:

    1. Lookback
    2. UsabilityHub

    Quantitative Research Tools

    The popular phrase “Numbers don’t lie” can be observed through people’s interest in collecting data and statistics. Hence, it’s not surprising that some of the common quantitative UX research methods include utilizing Digital Analytics, Heatmaps, and Online Surveys. For those of you who love numbers, here are some interesting tools you can try

    Digital Analytics

    Through capturing users’ usage patterns, navigational path, clicks to conversion, and time spent when using a product, we’re able to predict and determine future trends.

    Here are the most used Digital Analytics tools by researchers:


    And here are the tools researchers are looking forward to try in their next research project:

    1. Mixpanel
    3. Smartlook


    Heatmaps allow you to observe how people interact with website pages, specifically their cursor movements, and item selection on the screen, which is helpful when planning for site optimization and improving digital user experience.

    Even though some digital analytics tools are able to capture heatmap data, when it comes to the tools researchers used specifically for heatmapping, here are the tools they use:


    Online Survey

    Online surveys are arguably the cheapest and easiest way to collect data in a short period of time. The overall convenience and flexibility of online surveys explain why they’re a crowd’s favorite: researchers have the flexibility in designing the survey, meanwhile respondents are able to answer the questions at their own pace and comfort.   

    Here are the most used online survey tools by researchers:


    And here are the tools researchers are looking forward to try in their next research project:

    1. SurveyCircle
    2. Hotjar

    Respondent Recruitment Tools

    Regardless of what type of research you plan to conduct, you will always need respondents to fulfill and answer the burning questions you have in mind. However, respondent recruitment can be a challenging quest to conquer, especially if your target audience is niche. So, how do most researchers recruit people for their research? We found that email and word of mouth are still used by many, whilst others also use online tools such as Google Forms.

    Respondent Recruitment

    Here are the top 3 respondent recruitment tools that are frequently used by researchers in Asia:


    Design Tools

    User Interface Design 

    Shapes, colors, fonts… those who love designing and creating new things digitally need to continuously adapt to the changing trends and tools to keep inspired. But wait, there are a lot of tools out there that leave designers overwhelmed.

    Our finding shows that these are the most used user interface design tools by designers in Asia:


    And here are the tools UX designers in Asia are looking forward to try in their next UX design project:

    1. UXPin
    2. Axure
    3. Framer
    4. Sketch
    5. Zeplin
    6. Invision


    How do you know if clients really like your product before spending time and effort creating a website? How do you imagine the interaction before you code it? Prototype is the solution! 

    Here are the most used prototyping tools by designers:


    And here are the tools UX designers are looking forward to try in their next UX design project:

    1. Adobe XD
    2. Zaplin
    3. Framer
    4. Sketch
    5. Origami Design



    Architects create architectural blueprints before they start building. How about designers? They create wireframes to show the overall content layout and functionality of a webpage or app. 

    Here are the most used wireframing tools by designers in Asia:


    And here are the tools Asian UX designers are looking forward to try in their next user interface design project:

    1. Miro
    2. Mockplus
    3. Balsamiq 

    Research Repository Tools

    Whether you are a UX researcher or designer, we’ve all had times when we were lost in our own pool of resources. Trying to find that piece of crucial information suddenly becomes more exhausting and time-consuming. As the saying goes, sharing is caring. Hence, setting up a research repository is important to better organize and accelerate your research process. 

    Here are the most used research repository tools by researchers and designers:


    Project Management Tools

    Managing projects can be quite challenging at times, especially when working with different people. Hence, there are many project management tools in the market that could benefit you by easing this intimidating process.

    Here are the most used project management tools by researchers and designers:


    User Testing and its Applications

    User Testing and its Applications

    Understanding customers is vital to the success of any business. The main goal of any business should be to minimise potential client frustrations with their product or service.


    Whether a physical product or a digital, the idea should be to exceed customer expectations by considering customer feedback throughout the product ideation and development. One activity product developers can employ to ensure that they’re creating solutions that match what customers are seeking is user testing.

    What is user testing?

    User testing is a systematic process of observing how prospective users navigate a product prototype or feature. Subsequently, this information is collected to analyse the ways in which users find the product easy or difficult for them to employ.

    So, user testing activities illustrate precisely what problems users may encounter during their interaction with the functions of a website, app, product, or service— in realistic conditions (or mimicking realistic conditions). 

    Why is user testing important?

    User testing focuses on evaluation exercises to identify various pain points and positive attributes to incrementally enhance user experience before taking a product to market. 

    It helps to determine product usability and to decide whether a product is ready for launch to real users. User testing achieves this by collecting qualitative data to understand the intention and motivation driving customer behaviours. This consequently helps creators to make informed design decisions to positively impact user experiences.

    Generally, user testing is important to:

    • Uncover users’ needs and challenges through their actual use of your design.
    • Assess prospective users’ performance and mental state as they attempt to complete tasks, to evaluate how well a design works.
    • Make faster-informed decisions based on proven customer needs 
    • Implement a customer-first approach.

    How does user testing work?

    Following are the key steps involved in user testing:

    1. Creation of product, prototype, or feature

    Before you conduct a user testing exercise, you’ll require a real product or feature to test. This could be a new product, or existing version of a product, or even a sample.

    2. Choose a testing method

    Once you have a product or feature to test, select a method of user testing to employ. As you do this, carefully consider a test method best suited to the type of information you’re seeking to obtain, and the depth of feedback. 

    3. Write a test script

    Afterwards, write a test script to get the most out of your time and get comparable results. This will serve as a technical guide for the moderator as it lists the tasks to be tackled sequentially and supplemented with a hypothesis and a goal. 

    4. Recruit subjects for the user test

    After the above steps, you’ll need to recruit test respondents for your user testing. These should be real prospective clients, ideally, actual members of your intended audience, or users who match your client personas. 

    Such careful selection will help you achieve the desired outcomes and data from the people who matter most. 

    Read our article on ‘How to recruit the right respondents for user research.”

    5. Determine a location to perform the testing

    Once you have a product, testing method, and test subjects, determine the best time and location for your test. This decision depends on the nature of your product or feature, its use case and capabilities. Furthermore, you’ll need to carefully consider the test subject’s environment, as distractions might not be ideal.

    User Testing can be done in a UX research lab, where you invite participants to a central location. On the other hand, you can also be conducted remotely online as well, making it possible for your test with participants from all over the world easily. 

    6. Decide on the length of the test.

    Test respondents are sometimes cautious about the length of a user test as they sometimes have limited time. Furthermore, disparate users take different amounts of time.

    Unfortunately, longer tests typically return poor-quality responses and feedback due to fatigue, boredom, and lack of interest. For moderated user testing, it’s recommended to be around 60 minutes to avoid cognitive overload on the users. As for unmoderated user testing, the study should be completed by an average of 15-20 minutes.

    7. Executing the user test

    Before starting your user test, ensure that your subjects have all the instructions they need. For example, directions on how to provide their feedback and analysis. 

    Depending on the product, industry, and preferred test method, the directions and instructions for test subjects might differ prior to or during the test. 

    8. Evaluate and analyse the test results.

    Analysis of data should take place soon after user testing; otherwise, there is an inherent risk that important details might be forgotten. In addition, this evaluation and analysis should consider different metrics like, completion rate, error-free rate, critical errors, non-critical errors, and error-free rate. 

    After the evaluation process, you can make minor or drastic iterative modifications to accordingly improve your product.

    Types and methods of user testing

    Usability testing

    Usability testing principally focuses on determining how easy a product design is to use for a group of representative users. It typically involves carefully observing users as they complete different tasks, from early product development to release.

    A/B testing

    A/B testing is fundamentally the process by which two different variants of a product are sent to different groups of prospective users. It is imperative to remember that each user group must receive only one variant of the product, not both. Furthermore, they must be sent on the same day and time to optimally track customer reactions. 

    Generally, the central goal of A/B testing is to extensively gain insight into customer behaviour and preferences. This testing method is one of the most efficient and fastest ways to increase customer conversions. 

    Focus groups

    As a qualitative research technique, focus groups principally involve organising a discussion on a given product or topic with a group of 8-10 participants. These discussions typically take 60-90 minutes and seek to obtain information on users’ motivations and behaviours in response to the product. 

    During focus group engagements, real users discuss various attributes of a product, or feature. One of the product designers, researchers, or other employees typically leads such discussions to ensure you’re receiving your desired type of feedback. 

    For the most part, a focus group discussion will typically cover the test subjects’ concerns about a specific aspect of a product that’s brought up by the focus group facilitator.

    Heat map testing

    A heat map is a graphical data visualisation that demonstrates how website users click, scroll, and move on a web page. Heat map testing fundamentally revolves around engaging users to analyse their mouse or eye movements when using a product or service.

    Subsequently, heat map analysis is conducted to analyse the heat maps generated from the recording tool to determine what grabs a user’s attention. Or even where users spend most of their time, and how much time is spent on specific areas to determine which elements need improvement.

    Card sorting

    Card sorting is a user testing method that involves users organising index card (physical or digital) according to criteria that make the most sense to them. During product development, this testing technique helps guide the design of information architecture, menu structures, workflows, or website navigation paths.

    Respondent recruitment for user testing

    Respondents are a fundamental tenet of user testing. However, finding the right respondents is no easy feat, as researchers need to carefully vet them, and then schedule a time to engage them. 

    Unfortunately, some respondents cannot deliver meaningful feedback or insight. In turn, suboptimal respondents negatively impact the quality of user testing. 

    Netizen’s respondent recruitment service can help provide a tailored solution that focuses on recruiting the right respondents for surveys, focus groups, and in-depth user interviews. 


    The core purpose of user testing is to evaluate the success of a product or feature from the standpoint of customers. This is because while designers involved in the creation of the product might find it easy to use, the target customers may not. 

    Fortunately, user testing provides tunnel vision into where the product falls short for the intended audience. It essentially reveals where users are typically confused or frustrated. This information can then be leveraged to iterate the product’s design.

    Overall, well-planned and executed user testing uncovers actionable, qualitative data that product design teams can exploit to make faster, better decisions to improve customer satisfaction. 

    Reach out to us at Netizen Experience to discuss about user testing services and the requirements for your project.

    What is User Experience- A Complete Guide

    What is User Experience- A Complete Guide

    Any business should aim to create products that people will love to use. To achieve this, it’s important to extensively understand customers’ problems, frustrations, and expectations.

    User experience has slowly transformed over the last decade from a customer-centric service in the realm of product and service design to more personalized offerings. 

    Furthermore, the emergence of multiple digital distribution channels has made delivering optimal user experiences a necessity rather than an added value.

    What is user experience?

    User experience (UX) encompasses a user’s emotions and attitudes about using a specific physical product, digital application or service. It assesses practical, affective, experiential, emotive, meaningful and valuable aspects of human-computer interaction (HCI) and product ownership.

    It also considers users’ opinions on a product’s features, including utility, efficiency and simplicity of use.

    Why is it important to have a consistent user experience?

    As alluded to, user experience is typically subjective in nature to the degree of individual perception and thought, with respect to a product. 

    In fact, UX has been highly dynamic and constantly modified over time because of changing usage circumstances and even iterative changes to the product. 

    That being said, maintaining an optimal user experience via consistent design is pivotal to helping the users feel a sense of familiarity with a product. As a result, users can easily transfer their existing knowledge to new contexts and environments whenever any iterations are made to a product.  

    They can focus on completing their tasks rather than spending extra time trying to learn how to continually use the product. Thus, it helps nurture a feeling of trust whilst eliminating any potential frustrations that might trigger them to abandon tasks.

    What is considered a good user experience?

    A good UX is one that places a focus on customers and their interactions with a product. 

    Overall, a good user experience will consist of the following elements:

    • Usefulness: A useful product always solves user problems. That being said, design intentionality is a core part of user experience since a product that’s not ‘useful’ may not always be ‘usable’.
    • Enjoyable: An enjoyable product is always usable as its design delights the user. Typically, such products reflect what the user may be feeling and create a positive connection with them.
    • Usable: A usable product indicates that its design, structure, and purpose are simple to understand. And thus, propagates a great user experience. 
    • Equitable: An equitable product maintains a design that’s helpful to people with diverse backgrounds and abilities. In simpler terms, its design addresses the needs of diverse audiences regardless of background, gender, race, or ability.
    • Desirable: A good user experience should evoke emotion and appreciation via a brand identity that makes it desirable
    • Accessible: A great experience constitutes content that is accessible to all types of people. For example, those with disabilities.
    • Credible: A good user experience is credible and inspires trust. 

    User experience (UX) deliverables

    User experience deliverables are various outputs dictated during the UX design process— either during the project or once it’s complete. 

    In practice, deliverables enable UX designers to communicate different design ideas and findings to stakeholders in order to iterate the product and make improvements. They also allow UX designers to get buy-in for their ideas.

    Competitor assessment

    Evaluating the strengths and weaknesses of competitors can help align one’s UX strategy. For example, creating a competitive analysis report to detail the interaction designs of competitors can help pinpoint pitfalls and missed opportunities that one can leverage.

    Information Architecture

    Information architecture is the art of structurally organising and labelling websites in a manner that’s easy to understand for users. For large sites, this is particularly important to understand disparate content elements and how to organise them for diverse visitors. 

    For example, setting up a content inventory and a sitemap with suggested navigation, or instituting sample user flows that reveal how visitors peruse a site.

    User research

    User research can help uncover user needs, tendencies, and motivations. This research exercise can either collect quantitative or qualitative data from user testing sessions to inform sign-up flow redesigns or customer onboarding processes.

    Interaction Design

    An interaction design focuses on providing prospective users with a prototype to review how interactions with a site might occur. It seeks to uncover how users will probably complete critical tasks, seek out information, and use a product. 

    User Experience Design vs User Interface

    A user interface (UI) is a series of pages, screens, and visual elements. For example, switches, buttons and icons that facilitate a user when interacting with a product or service.

    On the other hand, user experience design focuses on designing products to ensure the most positive emotional experience possible as they interact with it. 

    Generally, a great product that people love typically necessitates both good UI and good UX. For instance, a dating app that looks visually appealing with intuitive navigation (UI) can be slow and make users click through multiple screens to make a match.

    In such instances, users might not want to use the app repeatedly, no matter how aesthetically commanding it looks. However, if its content is helpful and organised in a logical and intuitive way, it will most likely sustain consumer attention.

    User Experience vs Usability

    User experience is a design process that combines business-hypothesis driven experimentation and validated learning during product development cycles to improve user perceptions of a product. UX activities cover a user’s entire experience with a product. For example, how they expected it to work, and how they feel about continually using it.

    On the other hand, usability testing focuses on determining how successfully a user can exploit a product to achieve a specific goal. 

    These are typically five key metrics used to measure usability: 

    • Learnability: This metric evaluates how easy it is for prospective users to complete a generic task. For instance, logging into a website for the first time
    • Satisfaction: It assesses how enjoyable a product is to use.
    • Efficiency: This metric determines how fast users can fully complete a task once they have interacted with a product design.
    • Memorability: This metric analyses users’ ability to reuse a site fluently after taking a significant amount of time without using it. Essentially, determining how easily users can start using it again without issues. 
    • Errors: This assesses the number of repetitive mistakes users make when using a product or site. 

    How to improve the user experience of a site?

    Following are some key parameters to check in order to improve the UX of a site:

    Page loading time

    The loading page speed can make or break a website. 

    For example, Google statistics revela that 53% of users might leave the site is loading speed is longer than 3 seconds.  Simply put, humans aren’t really patient, especially when they have many options.

    So, it’s imperative to ensure that site users can quickly accomplish their primary goals, without going through painstaking load times. Remember, high load times and waiting times could affect the perception of users.

    Use Fitt’s Law to improve UX

    Fitt’s law is a predictive model used to determine the amount of time it takes for a particular user to move their mouse/cursor to a target area on a website. 

    Despite its multiple variations, Fitt’s law revolves around the idea that the time needed to move to a target largely depends on the distance to it. It is widely used with great success in modern UX design to improve site ergonomics, usability and user experiences. 

    UX design tools

    It is important to use the right tools for researching, storyboarding, prototyping, and wireframing to get the best user experience outcomes during the UX design process. 

    There are a plethora of UX tools available, some free and others that dictate a monthly subscription fee. 

    For example, Adobe XD & Figma enables UX designers to expertly curate unique websites and mobile apps with advanced prototyping, wireframing, and vector design capabilities. However, it is a subscription-based tool.

    On the other hand,  Storyboarder is a free storyboarding software with basic features made for UX designers of all levels to quickly create drawings and stick figures to plot ideas.

    Use white space generously

    One cheat code to ensure optimal user experiences is smartly using white spaces. Even subtle uses of whitespace can allow one’s design to breathe and stand out. In essence, white space always adds an aura of simplicity and elegance to web pages.

    Ask for customer feedback

    Collecting and reacting to customer feedback can help you significantly improve user experiences. However, if you don’t listen to your customers during the design process, you risk setting yourself up to lose opportunities to enhance your product.

    Conduct a UX review/audit

    As humans, we tend to focus on completing a task, with very little time set for reflection. As a result, we typically create systems fraught with weaknesses and discrepancies. A UX review can help you address any issues or avoid replicating the same problems repeatedly.

    Personalization in user experience

    Users’ requirements for convenience and ease of use will only grow as the world evolves into an on-demand environment. This means that users expect products to be specifically tailored to them as they are continuously bombarded by different product options.

    With this in mind, personalization in user experience design focuses on customising user journeys and experiences to match users’ exact choices and requirements. Fundamentally, this process seeks to exclusively meet users’ requirements and instruct them through a tailored conversion funnel.

    User experience examples


    Duolingo is an educational platform for learning different languages. The website is intuitively designed to be welcoming, with three prompt questions to help users set their learning goals. Overall, the website seeks to make it extremely frictionless to get started, which sets it apart from competitors.

    Image Credit:


    As a leading marketing automation platform, Mailchimp is well known for its humanisation of technology that adds depth to the often-boring experience of email marketing. It succeeds in delivering a unique and seamless user experience with an application that serves like a team member than a simple tool, when being used to get the job done.


    Image Credit:


    As we established throughout the article, a person’s feelings, perceptions and attitudes about using a product constitute user experience. 

    We also observed that UX comprises features of human-computer interaction that are experiential, emotive, meaningful, and useful. 

    UX has gained momentum as a consequence of modern-day users’ dynamically changing internal mental states (predispositions, moods, expectations, needs, motivation etc.). 

    As such, it’s more imperative than ever to strive for the best user experiences that overcome complex user requirements but fulfil usability and functionality demands— regardless of the environment. 

    To achieve this meaningfulness of activity and voluntariness of use, remember to pay attention to the following principles of UX design:

    • Always focus on the user.
    • Improve accessibility
    • Conduct iterative usability testing
    • Have consistency throughout the website
    • Employ a hierarchical approach
    • Put the user in control

    Reach out to us for user experience consulting services on your project!