December 11, 2018

How to interpret your card sort results Part 2: closed card sorts and next steps

In Part 1 of this series we looked at how to interpret results from open and hybrid card sorts and now in Part 2, we’re going to talk about closed card sorts. In closed card sorts, participants are asked to sort the cards into predetermined categories and are not allowed to create any of their own. You might use this approach when you are constrained by specific category names or as a quick checkup before launching a new or newly redesigned website.In Part 1, we also discussed the two different - but complementary - types of analysis that are generally used together for interpreting card sort results: exploratory and statistical. Exploratory analysis is intuitive and creative while statistical analysis is all about the numbers. Check out Part 1 for a refresher or learn more about exploratory and statistical analysis in Donna Spencer’s book.

Getting started

Closed card sort analysis is generally much quicker and easier than open and hybrid card sorts because there are no participant created category names to analyze - it’s really just about where the cards were placed. There are some similarities about how you might start to approach your analysis process but overall there’s a lot less information to take in and there isn’t much in the way of drilling down into the details like we did in Part 1.Just like with an open card sort, kick off your analysis process by taking an overall look at the results as a whole. Quickly cast your eye over each individual card sort and just take it all in. Look for common patterns in how the cards have been sorted. Does anything jump out as surprising? Are there similarities or differences between participant sorts?

If you’re redesigning an existing information architecture (IA), how do your results compare to the current state? If this is a final check up before launching a live website, how do these results compare to what you learned during your previous research studies?If you ran your card sort using information architecture tool OptimalSort, head straight to the Overview and Participants Table presented in the results section of the tool. If you ran a moderated card sort using OptimalSort’s printed cards, you’ve probably been scanning them in after each completed session, but now is a good time to double check you got them all. And if you didn’t know about this handy feature of OptimalSort, it’s something to keep in mind for next time!

The Participants Table shows a breakdown of your card sorting data by individual participant. Start by reviewing each individual card sort one by one by clicking on the arrow in the far left column next to the Participants numbers. From here you can easily flick back and forth between participants without needing to close that modal window. Don’t spend too much time on this — you’re just trying to get a general impression of how the cards were sorted into your predetermined categories. Keep an eye out for any card sorts that you might like to exclude from the results. For example participants who have lumped everything into one group and haven’t actually sorted the cards.

Don’t worry- excluding or including participants isn’t permanent and can be toggled on or off at anytime.Once you’re happy with the individual card sorts that will and won’t be included in your results visualizations, it’s time to take a look at the Results Matrix in OptimalSort. The Results Matrix shows the number of times each card was sorted into each of your predetermined categories- the higher the number, the darker the shade of blue (see below).

A screenshot of the Results Matrix tab in OptimalSort.
Results Matrix in OptimalSort.

This table enables you to quickly and easily get across how the cards were sorted and gauge the highest and lowest levels of agreement among your participants. This will tell you if you’re on the right track or highlight opportunities for further refinement of your categories.If we take a closer look (see below) we can see that in this example closed card sort conducted on the Dewey Decimal Classification system commonly used in libraries, The Interpretation of Dreams by Sigmund Freud was sorted into ‘Philosophy and psychology’ 38 times in study a completed by 51 participants.

A screenshot of the Results Matrix in OptimalSort zoomed in.
Results Matrix in OptimalSort zoomed in with hover.

In the real world, that is exactly where that content lives and this is useful to know because it shows that the current state is supporting user expectations around findability reasonably well. Note: this particular example study used image based cards instead of word label based cards so the description that appears in both the grey box and down the left hand side of the matrix is for reference purposes only and was hidden from the participants.Sometimes you may come across cards that are popular in multiple categories. In our example study, How to win friends and influence people by Dale Carnegie, is popular in two categories: ‘Philosophy & psychology’ and ‘Social sciences’ with 22 and 21 placements respectively. The remaining card placements are scattered across a further 5 categories although in much smaller numbers.

A screenshot of the Results Matrix in OptimalSort showing cards popular in multiple categories.
Results Matrix showing cards popular in multiple categories.

When this happens, it’s up to you to determine what your number thresholds are. If it’s a tie or really close like it is in this case, you might review the results against any previous research studies to see if anything has changed or if this is something that comes up often. It might be a new category that you’ve just introduced, it might be an issue that hasn’t been resolved yet or it might just be limited to this one study. If you’re really not sure, it’s a good idea to run some in-person card sorts as well so you can ask questions and gain clarification around why your participants felt a card belonged in a particular category. If you’ve already done that great! Time to review those notes and recordings!You may also find yourself in a situation where no category is any more popular than the others for a particular card. This means there’s not much agreement among your participants about where that card actually belongs. In our example closed card sort study, the World Book Encyclopedia was placed into 9 of 10 categories. While it was placed in ‘History & geography’ 18 times, that’s still only 35% of the total placements for that card- it’s hardly conclusive.

A screenshot of the Results Matrix showing a card with a lack of agreement.
Results Matrix showing a card with a lack of agreement.

Sometimes this happens when the card label or image is quite general and could logically belong in many of the categories. In this case, an encyclopedia could easily fit into any of those categories and I suspect this happened because people may not be aware that encyclopedias make up a very large part of the category on the far left of the above matrix: ‘Computer science, information & general works’. You may also see this happening when a card is ambiguous and people have to guess where it might belong. Again - if you haven’t already - if in doubt, run some in-person card sorts so you can ask questions and get to the bottom of it!After reviewing the Results Matrix in OptimalSort, visit the Popular Placements Matrix to see which cards were most popular for each of your categories based on how your participants sorted them (see below 2 images).

A screenshot of the Popular Placements Matrix in OptimalSort, with the top half of the diagram showing.
Popular Placements Matrix in OptimalSort- top half of the diagram.

A screenshot of the Popular Placements Matrix in OptimalSort, with the top half of the diagram showing.
Popular Placements Matrix in OptimalSort- scrolled to show the bottom half of the diagram.

The diagram shades the most popular placements for each category in blue making it very easy to spot what belongs where in the eyes of your participants. It’s useful for quickly identifying clusters and also highlights the categories that didn’t get a lot of card sorting love. In our example study (2 images above) we can see that ‘Technology’ wasn’t a popular card category choice potentially indicating ambiguity around that particular category name. As someone familiar with the Dewey Decimal Classification system I know that ‘Technology’ is a bit of a tricky one because it contains a wide variety of content that includes topics on medicine and food science - sometimes it will appear as ‘Technology & applied sciences’. These results appear to support the case for exploring that alternative further!

Where to from here?

Now that we’ve looked at how to interpret your open, hybrid and closed card sorts, here are some next steps to help you turn those insights into action!Once you’ve analyzed your card sort results, it’s time to feed those insights into your design process and create your taxonomy which goes hand in hand with your information architecture. You can build your taxonomy out in Post-it notes before popping it into a spreadsheet for review. This is also a great time to identify any alternate labelling and placement options that came out of your card sorting process for further testing.From here, you might move into tree testing your new IA or you might run another card sort focussing on a specific area of your website. You can learn more about card sorting in general via our 101 guide.

When interpreting card sort results, don’t forget to have fun! It’s easy to get overwhelmed and bogged down in the results but don’t lose sight of the magic that is uncovering user insights.I’m going to leave you with this quote from Donna Spencer that summarizes the essence of card sort analysis quite nicely:Remember that you are the one who is doing the thinking, not the technique... you are the one who puts it all together into a great solution. Follow your instincts, take some risks, and try new approaches. - Donna Spencer

Further reading

  • Card Sorting 101 – Learn about the differences between open, closed and hybrid card sorts, and how to run your own using OptimalSort.

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A quick analysis of feedback collected with OptimalSort

Card sorting is an invaluable tool for understanding how people organize information in their minds, making websites more intuitive and content easier to navigate. It’s a useful method outside of information architecture and UX research, too. It can be a useful prioritization technique, or used in a more traditional sense. For example, it’s handy in psychology, sociology or anthropology to inform research and deepen our understanding of how people conceptualize information.

The introduction of remote card sorting has provided many advantages, making it easier than ever to conduct your own research. Tools such as our very own OptimalSort allow you to quickly and easily gather findings from a large number of participants from all around the world. Not having to organize moderated, face-to-face sessions gives researchers more time to focus on their work, and easier access to larger data sets.

One of the main disadvantages of remote card sorting is that it eliminates the opportunity to dive deeper into the choices made by your participants. Human conversation is a great thing, and when conducting a remote card sort with users who could potentially be on the other side of the world, opportunities for our participants to provide direct feedback and voice their opinions are severely limited.Your survey design may not be perfect.

The labels you provide your participants may be incorrect, confusing or redundant. Your users may have their own ideas of how you could improve your products or services beyond what you are trying to capture in your card sort. People may be more willing to provide their feedback than you realize, and limiting their insights to a simple card sort may not capture all that they have to offer.So, how can you run an unmoderated, remote card sort, but do your best to mitigate this potential loss of insight?

A quick look into the data

In an effort to evaluate the usefulness of the existing “Leave a comment” feature in OptimalSort, I recently asked our development team to pull out some data.You might be asking “There’s a comment box in OptimalSort?”If you’ve never noticed this feature, I can’t exactly blame you. It’s relatively hidden away as an unassuming hyperlink in the top right corner of your card sort.

OptimalSortCommentBox1

OptimalSortCommentBox2

Comments left by your participants can be viewed in the “Participants” tab in your results section, and are indicated by a grey speech bubble.

OptimalSortSpeechBubble

The history of the button is unknown even to long-time Optimal Workshop team members. The purpose of the button is also unspecified. “Why would anyone leave a comment while participating in a card sort?”, I found myself wondering.As it turns out, 133,303 comments have been left by participants. This means 133,303 insights, opinions, critiques or frustrations. Additionally, these numbers only represent the participants who noticed the feature in the first place. Considering the current button can easily be missed when focusing on the task at hand, I can’t help but wonder how this number might change if we drew more attention to the feature.

Breaking down the comments

To avoid having to manually analyze and code 133,303 open text fields, I decided to only spend enough time to decipher any obvious patterns. Luckily for me, this didn’t take very long. After looking at only a hundred or so random entries, four distinct types of comments started to emerge.

  1. This card/group doesn’t make sense.Comments related to cards and groups dominate. This is a great thing, as it means that the majority of comments made by participants relate specifically to the task they are completing. For closed and hybrid sorts, comments frequently relate to the predefined categories available, and since the participants most likely to leave a comment are those experiencing issues, the majority of the feedback relates to issues with category names themselves. Many comments are related to card labels and offer suggestions for improving naming conventions, while many others draw attention to some terms being confusing, unclear or jargony. Comments on task length can also be found, along with reasons for why certain cards may be left ungrouped, e.g., “I’ve left behind items I think the site could do without”.
  2. Your organization is awesome for doing this/you’re doing it all wrong. A substantial number of participants used the comment box as an opportunity to voice their general feedback on the organization or company running the study. Some of the more positive comments include an appreciation for seeing private companies or public sector organizations conducting research with real users in an effort to improve their services. It’s also nice to see many comments related to general enjoyment in completing the task.On the other hand, some participants used the comment box as an opportunity to comment on what other areas of their services should be improved, or what features they would like to see implemented that may otherwise be missed in a card sort, e.g., “Increased, accurate search functionality is imperative in a new system”.
  3. This isn’t working for me. Taking a closer look at some of the comments reveals some useful feedback for us at Optimal Workshop, too. Some of the comments relate specifically to UI and usability issues. The majority of these issues are things we are already working to improve or have dealt with. However, for researchers, comments that relate to challenges in using the tool or completing the survey itself may help explain some instances of data variability.
  4. #YOLO, hello, ;) And of course, the unrelated. As you may expect, when you provide people with the opportunity to leave a comment online, you can expect just about anything in return.

How to make the most of your user insights in OptimalSort

If you’re running a card sort, chances are you already place a lot of value in the voice of your users. To ensure you capture any additional insights, it’s best to ensure your participants are aware of the opportunity to do so. Here are two ways you may like to ensure your participants have a space to voice their feedback:

Adding more context to the “Leave a comment” feature

One way to encourage your participants to leave comments is to promote the use of the this feature in your card sort instructions. OptimalSort gives you flexibility to customize your instructions every time you run a survey. By making your participants aware of the feature, or offering ideas around what kinds of comments you may be looking for, you not only make them more likely to use the feature, but also open yourself up to a whole range of additional feedback. An advantage of using this feature is that comments can be added in real time during a card sort, so any remarks can be made as soon as they arise.

Making use of post-survey questions

Adding targeted post-survey questions is the best way to ensure your participants are able to voice any thoughts or concerns that emerged during the activity. Here, you can ask specific questions that touch upon different aspects of your card sort, such as length, labels, categories or any other comments your participants may have. This can not only help you generate useful insights but also inform the design of your surveys in the future.

Make your remote card sorts more human

Card sorts are exploratory by nature. Avoid forcing your participants into choices that may not accurately reflect their thinking by giving them the space to voice their opinions. Providing opportunities to capture feedback opens up the conversation between you and your users, and can lead to surprising insights from unexpected places.

Further reading

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Card Sorting outside UX: How I use online card sorting for in-person sociological research

Hello, my name is Rick and I’m a sociologist. All together, “Hi, Rick!” Now that we’ve got that out of the way, let me tell you about how I use card sorting in my research. I'll soon be running a series of in-person, moderated card sorting sessions. This article covers why card sorting is an integral part of my research, and how I've designed the study toanswer specific questions about two distinct parts of society.

Card sorting to establish how different people comprehend their worlds

Card sorting,or pile sorting as it’s sometimes called, has a long history in anthropology, psychology and sociology. Anthropologists, in particular, have used it to study how different cultures think about various categories. Researchers in the 1970s conducted card sorts to understand how different cultures categorize things like plants and animals. Sociologists of that era also used card sorts to examine how people think about different professions and careers. And since then, scholars have continued to use card sorts to learn about similar categorization questions.

In my own research, I study how different groups of people in the United States imagine the category of 'religion'. Asthose crazy 1970s anthropologists showed, card sorting is a great way to understand how people cognitively understand particular social categories. So, in particular,I’m using card sorting in my research to better understand how groups of people with dramatically different views understand 'religion' — namely, evangelical Christians and self-identified atheists. Thinkof it like this. Some people say that religion is the bedrock of American society.

Others say that too much religion in public life is exactly what’s wrong with this country. What's not often considered is these two groups oftenunderstand the concept of 'religion' in very different ways. It’s like the group of blind men and the elephant: one touches the trunk, one touches the ears, and one touches the tail. All three come away with very different ideas of what an elephant is. So you could say that I study how different people experience the 'elephant' of religion in their daily lives. I’m doing so using primarily in-person moderated sorts on an iPad, which I’ll describe below.

How I generated the words on the cards

The first step in the process was to generate lists of relevant terms for my subjects to sort. Unlike in UX testing, where cards for sorting might come from an existing website, in my world these concepts first have to be mined from the group of people being studied. So the first thing I did was have members of both atheist and evangelical groups complete a free listing task. In a free listing task, participants simply list as many words as they can that meet the criteria given. Sets of both atheist and evangelical respondents were given the instructions: "What words best describe 'religion?' Please list as many as you can.” They were then also asked to list words that describe 'atheism', 'spirituality', and 'Christianity'.

I took the lists generated and standardizedthem by combining synonyms. For example, some of my atheists used words like 'ancient', 'antiquated', and 'archaic' to describe religion. SoI combined all of these words into the one that was mentioned most: 'antiquated'. By doing this, I created a list of the most common words each group used to describe each category. Doing this also gave my research another useful dimension, ideal for exploring alongside my card sorting results. Free lists can beanalyzed themselves using statistical techniques likemulti-dimensional scaling, so I used this technique for apreliminary analysis of the words evangelicals used to describe 'atheism':

Optimalsort and sociological research

Now that I’m armed with these lists of words that atheist and evangelicals used to describe religion, atheism etc., I’m about to embark on phase two of the project: the card sort.

Why using card sorting software is a no-brainer for my research

I’ll be conducting my card sorts in person, for various reasons. I have relatively easy access to the specific population that I’m interested in, and for the kind of academic research I’m conducting, in-person activities are preferred. In theory, I could just print the words on some index cards and conduct a manual card sort, but I quickly realized that a software solution would be far preferable, for a bunch of reasons.

First of all, it's important for me to conductinterviews in coffee shops and restaurants, and an iPad on the table is, to put it mildly, more practical than a table covered in cards — no space for the teapot after all.

Second, usingsoftwareeliminates the need for manual data entry on my part. Not only is manual data entry a time consuming process, but it also introduces the possibly of data entry errors which may compromise my research results.

Third, while the bulk of the card sorts are going to be done in person, having an online version will enable meto scale the project up after the initial in-person sorts are complete. The atheist community, in particular, has a significant online presence, making a web solution ideal for additional data collection.

Fourth, OptimalSort gives the option to re-direct respondents after they complete a sort to any webpage, which allows multiple card sorts to be daisy-chained together. It also enables card sorts to be easily combined with complex survey instruments from other providers (e.g. Qualtrics or Survey Monkey), so card sorting data can be gathered in conjunction with other methodologies.

Finally, and just as important, doing card sorts on a tablet is more fun for participants. After all, who doesn’t like to play with an iPad? If respondents enjoy the unique process of the experiment, this is likely to actually improve the quality of the data, andrespondents are more likely to reflect positively on the experience, making recruitment easier. And a fun experience also makes it more likely that respondents will complete the exercise.

What my in-person, on-tablet card sorting research will look like

Respondents will be handed an iPad Air with 4G data capability. While the venues where the card sorts will take place usually have public Wi-Fi networks available, these networks are not always reliable, so the cellular data capabilities are needed as a back-up (and my pre-testing has shown that OptimalSort works on cellular networks too).

The iPad’s screen orientation will be locked to landscape and multi-touch functions will be disabled to prevent respondents from accidentally leaving the testing environment. In addition, respondents will have the option of using a rubber tipped stylus for ease of sorting the cards. While I personally prefer to use a microfiber tipped stylus in other applications, pre-testing revealed that an old fashioned rubber tipped stylus was easier for sorting activities.

using a tablet to conduct a card sort

When the respondent receives the iPad, the card sort first page with general instructions will already be open on the tablet in the third party browser Perfect Web. A third party browser is necessary because it is best to run OptimalSort locked in a full screen mode, both for aesthetic reasons and to keep the screen simple and uncluttered for respondents. Perfect Web is currently the best choice in the ever shifting app landscape.

participants see the cards like this

I'll give respondents their instructions and then go to another table to give them privacy (because who wants the creepy feeling of some guy hanging over you as you do stuff?). Altogether, respondents will complete two open card sorts and a fewsurvey-style questions, all chained together by redirect URLs. First, they'll sort 30 cards into groups based on how they perceive 'religion', and name the categories they create. Then, they'll complete a similar card sort, this time based on how they perceive 'atheism'.

Both atheist and evangelicals will receive a mixture of some of the top words that both groups generated in the earlier free listing tasks. To finish, they'll answer a few questions that will provide further data on how they think about 'religion'. After I’ve conducted these card sorts with both of my target populations, I’ll analyze the resulting data on its own and also in conjunction with qualitative data I’ve already collected via ethnographic research and in-depth interviews. I can't wait, actually. In a few months I’ll report back and let you know what I’ve found.

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Live training: Dive head first into card sort analysis

Your cards have been sorted, and now you have lots of amazing data and insight to help improve your information architecture. So how do you interpret the results? 

Never fear, our product ninjas Alex and Aidan are here to help. In our latest live training session they take you on a walk-through of card sort analysis using OptimalSort.


What they cover:

  • Use cases for open, closed and hybrid card sort methodologies
  • How, when and why to standardize categories
  • How to interpret 3D cluster views, dendrograms, and similarity matrix
  • Tips on turning those results into actionable insights

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