Card Sorting vs Tree Testing: what's the best?

There’s no doubt usability is a key element of all great user experiences, how do we apply and test usability principles for a website? This article looks at usability principles in web design, how to test it, practical tips for success and a look at our remote testing tool, Treejack.

‍

A definition of usability for websites 🧐📖

‍

Web usability is defined as the extent to which a website can be used to achieve a specific task or goal by a user. It refers to the quality of the user experience and can be broken down into five key usability principles:

‍

• Ease of use: How easy is the website to use? How easily are users able to complete their goals and tasks? How much effort is required from the user?
• Learnability: How easily are users able to complete their goals and tasks the first time they use the website?
• Efficiency: How quickly can users perform tasks while using your website?
• User satisfaction: How satisfied are users with the experience the website provides? Is the experience a pleasant one?
• Impact of errors: Are users making errors when using the website and if so, how serious are the consequences of those errors? Is the design forgiving enough make it easy for errors to be corrected?

‍

Why is web usability important? 👀

‍

Aside from the obvious desire to improve the experience for the people who use our websites, web usability is crucial to your website’s survival. If your website is difficult to use, people will simply go somewhere else. In the cases where users do not have the option to go somewhere else, for example government services, poor web usability can lead to serious issues. How do we know if our website is well-designed? We test it with users.

‍

Testing usability: What are the common methods? 🖊️📖✏️📚

‍

There are many ways to evaluate web usability and here are the common methods:

‍

• Moderated usability testing: Moderated usability testing refers to testing that is conducted in-person with a participant. You might do this in a specialised usability testing lab or perhaps in the user’s contextual environment such as their home or place of business. This method allows you to test just about anything from a low fidelity paper prototype all the way up to an interactive high fidelity prototype that closely resembles the end product.
• Moderated remote usability testing: Moderated remote usability testing is very similar to the previous method but with one key difference- the facilitator and the participant/s are not in the same location. The session is still a moderated two-way conversation just over skype or via a webinar platform instead of in person. This method is particularly useful if you are short on time or unable to travel to where your users are located, e.g. overseas.
• Unmoderated remote usability testing: As the name suggests, unmoderated remote usability testing is conducted without a facilitator present. This is usually done online and provides the flexibility for your participants to complete the activity at a time that suits them. There are several remote testing tools available ( including our suite of tools ) and once a study is launched these tools take care of themselves collating the results for you and surfacing key findings using powerful visual aids.
• Guerilla testing: Guerilla testing is a powerful, quick and low cost way of obtaining user feedback on the usability of your website. Usually conducted in public spaces with large amounts of foot traffic, guerilla testing gets its name from its ‘in the wild’ nature. It is a scaled back usability testing method that usually only involves a few minutes for each test but allows you to reach large amounts of people and has very few costs associated with it.
• Heuristic evaluation: A heuristic evaluation is conducted by usability experts to assess a website against recognized usability standards and rules of thumb (heuristics). This method evaluates usability without involving the user and works best when done in conjunction with other usability testing methods eg Moderated usability testing to ensure the voice of the user is heard during the design process.
• Tree testing: Also known as a reverse card sort, tree testing is used to evaluate the findability of information on a website. This method allows you to work backwards through your information architecture and test that thinking against real world scenarios with users.
• First click testing: Research has found that 87% of users who start out on the right path from the very first click will be able to successfully complete their task while less than half ( 46%) who start down the wrong path will succeed. First click testing is used to evaluate how well a website is supporting users and also provides insights into design elements that are being noticed and those that are being ignored.
• Hallway testing: Hallway testing is a usability testing method used to gain insights from anyone nearby who is unfamiliar with your project. These might be your friends, family or the people who work in another department down the hall from you. Similar to guerilla testing but less ‘wild’. This method works best at picking up issues early in the design process before moving on to testing a more refined product with your intended audience.

‍

Online usability testing tool: Tree testing 🌲🌳🌿

‍

Tree testing is a remote usability testing tool that uses tree testing to help you discover exactly where your users are getting lost in the structure of your website. Treejack uses a simplified text-based version of your website structure removing distractions such as navigation and visual design allowing you to test the design from its most basic level.

‍

Like any other tree test, it uses task based scenarios and includes the opportunity to ask participants pre and post study questions that can be used to gain further insights. Tree testing is a useful tool for testing those five key usability principles mentioned earlier with powerful inbuilt features that do most of the heavy lifting for you. Tree testing records and presents the following for each task:

‍

• complete details of the pathways followed by each participant
• the time taken to complete each task
• first click data
• the directness of each result
• visibility on when and where participants skipped a task

‍

Participant paths data in our tree testing tool 🛣️

‍

The level of detail recorded on the pathways followed by your participants makes it easy for you to determine the ease of use, learnability, efficiency and impact of errors of your website. The time taken to complete each task and the directness of each result also provide insights in relation to those four principles and user satisfaction can be measured through the results to your pre and post survey questions.

‍

The first click data brings in the added benefits of first click testing and knowing when and where your participants gave up and moved on can help you identify any issues.Another thing tree testing does well is the way it brings all data for each task together into one comprehensive overview that tells you everything you need to know at a glance. Tree testing's task overview- all the key information in one placeIn addition to this, tree testing also generates comprehensive pathway maps called pietrees.

‍

Each junction in the pathway is a piechart showing a statistical breakdown of participant activity at that point in the site structure including details about: how many were on the right track, how many were following the incorrect path and how many turned around and went back. These beautiful diagrams tell the story of your usability testing and are useful for communicating the results to your stakeholders.

‍

Usability testing tips 🪄

‍

Here are seven practical usability testing tips to get you started:

‍

• Test early and often: Usability testing isn’t something that only happens at the end of the project. Start your testing as soon as possible and iterate your design based on findings. There are so many different ways to test an idea with users and you have the flexibility to scale it back to suit your needs.
• Try testing with paper prototypes: Just like there are many usability testing methods, there are also several ways to present your designs to your participant during testing. Fully functioning high fidelity prototypes are amazing but they’re not always feasible (especially if you followed the previous tip of test early and often). Paper prototypes work well for usability testing because your participant can draw on them and their own ideas- they’re also more likely to feel comfortable providing feedback on work that is less resolved! You could also use paper prototypes to form the basis for collaborative design sessions with your users by showing them your idea and asking them to redesign or design the next page/screen.
• Run a benchmarking round of testing: Test the current state of the design to understand how your users feel about it. This is especially useful if you are planning to redesign an existing product or service and will save you time in the problem identification stages.
• Bring stakeholders and clients into the testing process: Hearing how a product or service is performing direct from a user can be quite a powerful experience for a stakeholder or client. If you are running your usability testing in a lab with an observation room, invite them to attend as observers and also include them in your post session debriefs. They’ll gain feedback straight from the source and you’ll gain an extra pair of eyes and ears in the observation room. If you’re not using a lab or doing a different type of testing, try to find ways to include them as observers in some way. Also, don’t forget to remind them that as observers they will need to stay silent for the entire session beyond introducing themselves so as not to influence the participant - unless you’ve allocated time for questions.
• Make the most of available resources: Given all the usability testing options out there, there’s really no excuse for not testing a design with users. Whether it’s time, money, human resources or all of the above making it difficult for you, there’s always something you can do. Think creatively about ways to engage users in the process and consider combining elements of different methods or scaling down to something like hallway testing or guerilla testing. It is far better to have a less than perfect testing method than to not test at all.
• Never analyse your findings alone: Always analyse your usability testing results as a team or with at least one other person. Making sense of the results can be quite a big task and it is easy to miss or forget key insights. Bring the team together and affinity diagram your observations and notes after each usability testing session to ensure everything is captured. You could also use Reframer to record your observations live during each session because it does most of the analysis work for you by surfacing common themes and patterns as they emerge. Your whole team can use it too saving you time.
• Engage your stakeholders by presenting your findings in creative ways: No one reads thirty page reports anymore. Help your stakeholders and clients feel engaged and included in the process by delivering the usability testing results in an easily digestible format that has a lasting impact. You might create an A4 size one page summary, or maybe an A0 size wall poster to tell everyone in the office the story of your usability testing or you could create a short video with snippets taken from your usability testing sessions (with participant permission of course) to communicate your findings. Remember you’re also providing an experience for your clients and stakeholders so make sure your results are as usable as what you just tested.

‍

Related reading 🎧💌📖

‍

• Usability testing with Optimal Workshop
• Usability Testing: Five types of usability tests
• Usability Heuristics: How to conduct a heuristic evaluation
• Interface Usability:User Interface Design Basics

Usability guru Jared Spool has written extensively about the 'scent of information'. This term describes how users are always 'on the hunt' through a site, click by click, to find the content they’re looking for. Tree testing helps you deliver a strong scent by improving organisation (how you group your headings and subheadings) and labelling (what you call each of them).

‍

Anyone who’s seen a spy film knows there are always false scents and red herrings to lead the hero astray. And anyone who’s run a few tree tests has probably seen the same thing — headings and labels that lure participants to the wrong answer. We call these 'evil attractors'.In Part 1 of this article, we’ll look at what evil attractors are, how to spot them at the answer end of your tree, and how to fix them. In Part 2, we’ll look at how to spot them in the higher levels of your tree.

‍

The false scent — what it looks like in practice

‍

One of my favourite examples of an evil attractor comes from a tree test we ran for consumer.org.nz, a New Zealand consumer-review website (similar to Consumer Reports in the USA). Their site listed a wide range of consumer products in a tree several levels deep, and they wanted to try out a few ideas to make things easier to find as the site grew bigger.We ran the tests and got some useful answers, but we also noticed there was one particular subheading (Home > Appliances > Personal) that got clicks from participants looking for very different things — mobile phones, vacuum cleaners, home-theatre systems, and so on:

‍

‍

‍

The website intended the Personal appliance category to be for products like electric shavers and curling irons. But apparently, Personal meant many things to our participants: they also went there for 'personal' items like mobile phones and cordless drills that actually lived somewhere else.This is the false scent — the heading that attracts clicks when it shouldn’t, leading participants astray. Hence this definition: an evil attractor is a heading that draws unwanted traffic across several unrelated tasks.

‍

Evil attractors lead your users astray

‍

Attracting clicks isn’t a bad thing in itself. After all, that’s what a good heading does — it attracts clicks for the content it contains (and discourages clicks for everything else). Evil attractors, on the other hand, attract clicks for things they shouldn’t. These attractors lure users down the wrong path, and when users find themselves in the wrong place they'll either back up and try elsewhere (if they’re patient) or give up (if they’re not). Because these attractor topics are magnets for the user’s attention, they make it less likely that your user will get to the place you intended. The other evil part of these attractors is the way they hide in the shadows. Most of the time, they don’t get the lion’s share of traffic for a given task. Instead, they’ll poach 5–10% of the responses, luring away a fraction of users who might otherwise have found the right answer.

‍

Find evil attractors easily in your data

‍

The easiest attractors to spot are those at the answer end of your tree (where participants ended up for each task). If we can look across tasks for similar wrong answers, then we can see which of these might be evil attractors.In your Treejack results, the Destinations tab lets you do just that. Here’s more of the consumer.org.nz example:

‍

‍

Normally, when you look at this view, you’re looking down a column for big hits and misses for a specific task. To look for evil attractors, however, you’re looking for patterns across rows. In other words, you’re looking horizontally, not vertically. If we do that here, we immediately notice the row for Personal (highlighted yellow). See all those hits along the row? Those hits indicate an attractor — steady traffic across many tasks that seem to have little in common. But remember, traffic alone is not enough. We’re looking for unwanted traffic across unrelated tasks. Do we see that here? Well, it looks like the tasks (about cameras, drills, laptops, vacuums, and so on) are not that closely related. We wouldn’t expect users to go to the same topic for each of these. And the answer they chose, Personal, certainly doesn’t seem to be the destination we intended. While we could rationalise why they chose this answer, it is definitely unwanted from an IA perspective. So yes, in this case, we seem to have caught an evil attractor red-handed. Here’s a heading that’s getting steady traffic where it shouldn’t.

‍

Evil attractors are usually the result of ambiguity

‍

It’s usually quite simple to figure out why an item in your tree is an evil attractor. In almost all cases, it’s because the item is vague or ambiguous — a word or phrase that could mean different things to different people. Look at our example above. In the context of a consumer-review site, Personal is too general to be a good heading. It could mean products you wear, or carry, or use in the bathroom, or a number of things. So, when those participants come along clutching a task, and they see Personal, a few of them think 'That looks like it might be what I’m looking for', and they go that way.Individually, those choices may be defensible, but as an information architect, are you really going to group mobile phones with vacuum cleaners? The 'personal' link between them is tenuous at best.

‍

Destroy evil attractors by being specific

‍

Just as it’s easy to see why most attractors attract, it’s usually easy to fix them. Evil attractors trade in vagueness and ambiguity, so the obvious remedy is to make those headings more concrete and specific. In the consumer-site example, we looked at the actual content under the Personal heading. It turned out to be items like shavers, curling irons, and hair dryers. A quick discussion yielded Personal care as a promising replacement — one that should deter people looking for mobile phones and jewellery and the like.In the second round of tree testing, among the other changes we made to the tree, we replaced Personal with Personal Care. A few days later, the results confirmed our thinking. Our former evil attractor was no longer luring participants away from the correct answers:

‍

Testing once is good, testing twice is magic

‍

This brings up a final point about tree testing (and about any kind of user testing, really): you need to iterate your testing —  once is not enough.The first round of testing shows you where your tree is doing well (yay!) and where it needs more work so you can make some thoughtful revisions. Be careful though. Even if the problems you found seem to have obvious solutions, you still need to make sure your revisions actually work for users, and don’t cause further problems. The good news is, it’s dead easy to run a second test, because it’s just a small revision of the first. You already have the tasks and all the other bits worked out, so it’s just a matter of making a copy in Treejack, pasting in your revised tree, and hooking up the correct answers. In an hour or two, you’re ready to pilot it again (to err is human, remember) and send it off to a fresh batch of participants.

‍

Two possible outcomes await.

• Your fixes are spot-on, the participants find the correct answers more frequently and easily, and your overall score climbs. You could have skipped this second test, but confirming that your changes worked is both good practice and a good feeling. It’s also something concrete to show your boss.
• Some of your fixes didn’t work, or (given the tangled nature of IA work) they worked for the problems you saw in Round 1, but now they’ve caused more problems of their own. Bad news, for sure. But better that you uncover them now in the design phase (when it takes a few days to revise and re-test) instead of further down the track when the IA has been signed off and changes become painful.

‍

Stay tuned for more on evil attractors

‍

In Part 1, we’ve covered what evil attractors are and how to spot them at the answer end of your tree: that is, evil attractors that participants chose as their destination when performing tasks. Hopefully, a future version of Treejack will be able to highlight these attractors to make your analysis that much easier.

‍

In Part 2, we’ll look at how to spot evil attractors in the intermediate levels of your tree, where they lure participants into a section of the site that you didn’t intend. These are harder to spot, but we’ll see if we can ferret them out.Let us know if you've caught any evil attractors red-handed in your projects.

The key purpose of running a card sort is to learn something new about how people conceptualize and organize the information that’s found on your website. The insights you gain from running a card sort can then help you develop a site structure with content labels or headings that best represent the way your users think about this information. Card sorts are in essence a simple technique, however it’s the details of the sort that can determine the quality of your results.

‍

Adding context to cards in OptimalSort – descriptions, links and images

‍

In most cases, each item in a card sort has only a short label, but there are instances where you may wish to add additional context to the items in your sort. Currently, the cards tab in OptimalSort allows you to include a tooltip description, a link within the tooltip description or to format the card as an image (with or without a label).

‍

‍

We generally don’t recommend using tooltip descriptions and links, unless you have a specific reason to do so. It’s likely that they’ll provide your participants with more information than they would normally have when navigating your website, which may in turn influence your results by leading participants to a particular solution.

‍

Legitimate reasons that you may want to use descriptions and links include situations where it’s not possible or practical to translate complex or technical labels (for example, medical, financial, legal or scientific terms) into plain language, or if you’re using a card sort to understand your participants’ preferences or priorities.

‍

If you do decide to include descriptions in your sort, it’s important that you follow the same guidelines that you would otherwise follow for writing card labels. They should be easy for your participants to understand and you should avoid obvious patterns, for example repeating words and phrases, or including details that refer to the current structure of the website.

‍

A quick survey of how card descriptions are used in OptimalSort

‍

I was curious to find out how often people were including descriptions in their card sorts, so I asked our development team to look into this data. It turns out that around 15% of cards created in OptimalSort have at least some text entered in the description field. In order to dig into the data a bit further, both Ania and I reviewed a random sample of recent sorts and noted how descriptions were being used in each case.

‍

We found that out of the descriptions that we reviewed, 40% (6% of the total cards) had text that should not have impacted the sort results. Most often, these cards simply had the card label repeated in the description (to be honest, we’re not entirely sure why so many descriptions are being used this way! But it’s now in our roadmap to stop this from happening — stay tuned!). Approximately 20% (3% of the total cards) used descriptions to add context without obviously leading participants, however another 40% of cards have descriptions that may well lead to biased results. On occasion, this included linking to the current content or using what we assumed to be the current top level heading within the description.

‍

Use of card descriptions

‍

‍Create pie charts

‍

Testing the effect of card descriptions on sort results

‍

So, how much influence could potentially leading card descriptions have on the results of a card sort? I decided to put it to the test by running a series of card sorts to compare the effect of different descriptions. As I also wanted to test the effect of linking card descriptions to existing content, I had to base the sort on a live website. In addition, I wanted to make sure that the card labels and descriptions were easily comprehensible by a general audience, but not so familiar that participants were highly likely to sort the cards in a similar manner.

‍

I selected the government immigration website New Zealand Now as my test case. This site, which provides information for prospective and new immigrants to New Zealand, fit the above criteria and was likely unfamiliar to potential participants.

‍

‍

‍

Navigating the New Zealand Now website

‍

When I reviewed the New Zealand Now site, I found that the top level navigation labels were clear and easy to understand for me personally. Of course, this is especially important when much of your target audience is likely to be non-native English speaking! On the whole, the second level headings were also well-labeled, which meant that they should translate to cards that participants were able to group relatively easily.

‍

There were, however, a few headings such as “High quality” and “Life experiences”, both found under “Study in New Zealand”, which become less clear when removed from the context of their current location in the site structure. These headings would be particularly useful to include in the test sorts, as I predicted that participants would be more likely to rely on card descriptions in the cases where the card label was ambiguous.

‍

‍

I selected 30 headings to use as card labels from under the sections “Choose New Zealand”, “Move to New Zealand”, “Live in New Zealand”, “Work in New Zealand” and “Study in New Zealand” and tweaked the language slightly, so that the labels were more generic.

‍

‍

‍

I then created four separate sorts in OptimalSort:Round 1: No description: Each card showed a heading only — this functioned as the control sort

‍

‍

Round 2: Site section in description: Each card showed a heading with the site section in the description

‍

Round 3: Short description: Each card showed a heading with a short description — these were taken from the New Zealand Now topic landing pages

‍

Round 4:Link in description: Each card showed a heading with a link to the current content page on the New Zealand Now website

‍

For each sort, I recruited 30 participants. Each participant could only take part in one of the sorts.

‍

What the results showed

‍

An interesting initial finding was that when we queried the participants following the sort, only around 40% said they noticed the tooltip descriptions and even fewer participants stated that they had used them as an aid to help complete the sort.

‍

Participant recognition of descriptions

‍

‍Create bar charts

‍

Of course, what people say they do does not always reflect what they do in practice! To measure the effect that different descriptions had on the results of this sort, I compared how frequently cards were sorted with other cards from their respective site sections across the different rounds.Let’s take a look at the “Study in New Zealand” section that was mentioned above. Out of the five cards in this section,”Where & what to study”, “Everyday student life” and “After you graduate” were sorted pretty consistently, regardless of whether a description was provided or not. The following charts show the average frequency with which each card was sorted with other cards from this section. For example in the control round, “Where & what to study” was sorted with “After you graduate” 76% of the time and with “Everyday day student life” 70% of the time, but was sorted with “Life experiences” or “High quality” each only 10% of the time. This meant that the average sort frequency for this card was 42%.

‍

Untitled chartCreate bar charts

‍

On the other hand, the cards “High quality” and “Life experiences” were sorted much less frequently with other cards in this section, with the exception of the second sort, which included the site section in the description.These results suggest that including the existing site section in the card description did influence how participants sorted these cards — confirming our prediction! Interestingly, this round had the fewest number of participants who stated that they used the descriptions to help them complete the sort (only 10%, compared to 40% in round 3 and 20% in round 4).Also of note is that adding a link to the existing content did not seem to increase the likelihood that cards were sorted more frequently with other cards from the same section. Reasons for this could include that participants did not want to navigate to another website (due to time-consciousness in completing the task, or concern that they’d lose their place in the sort) or simply that it can be difficult to open a link from the tooltip pop-up.

‍

What we can take away from these results

‍

This quick investigation into the impact of descriptions illustrates some of the intricacies around using additional context in your card sorts, and why this should always be done with careful consideration. It’s interesting that we correctly predicted some of these results, but that in this case, other uses of the description had little effect at all. And the results serve as a good reminder that participants can often be influenced by factors that they don’t even recognise themselves!If you do decide to use card descriptions in your cards sorts, here are some guidelines that we recommend you follow:

• Avoid repeating words and phrases, participants may sort cards by pattern-matching rather than based on the actual content
• Avoid alluding to a predetermined structure, such as including references to the current site structure
• If it’s important that participants use the descriptions to complete the sort, you should mention this in your task instructions. It may also be worth asking them a post-survey question to validate if they used them or not

‍

We’d love to hear your thoughts on how we tested the effects of card descriptions and the results that we got. Would you have done anything differently?Have you ever completed a card sort only to realize later that you’d inadvertently biased your results? Or have you used descriptions in your card sorts to meet a genuine need? Do you think there’s a case to make descriptions more obvious than just a tooltip, so that when they are used legitimately, most participants don’t miss this information?

‍

Let us know by leaving a comment!