March 29, 2016
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Which comes first: card sorting or tree testing?

“Dear Optimal, I want to test the structure of a university website (well certain sections anyway). My gut instinct is that it's pretty 'broken'. Lots of sections feel like they're in the wrong place. I want to test my hypotheses before proposing a new structure. I'm definitely going to do some card sorting, and was planning a mixture of online and offline. My question is about when to bring in tree testing. Should I do this first to test the existing IA? Or is card sorting sufficient? I do intend to tree test my new proposed IA in order to validate it, but is it worth doing it upfront too?" — Matt

Dear Matt,

Ah, the classic chicken or the egg scenario: Which should come first, tree testing or card sorting?

It’s a question that many researchers often ask themselves, but I’m here to help clear the air! You should always use both methods when changing up your information architecture (IA) in order to capture the most information.

Tree testing and card sorting, when used together, can give you fantastic insight into the way your users interact with your site. First of all, I’ll run through some of the benefits of each testing method.


What is card sorting and why should I use it?

Card sorting is a great method to gauge the way in which your users organize the content on your site. It helps you figure out which things go together and which things don’t. There are two main types of card sorting: open and closed.

Closed card sorting involves providing participants with pre-defined categories into which they sort their cards. For example, you might be reorganizing the categories for your online clothing store for women. Your cards would have all the names of your products (e.g., “socks”, “skirts” and “singlets”) and you also provide the categories (e.g.,“outerwear”, “tops” and “bottoms”).

Open card sorting involves providing participants with cards and leaving them to organize the content in a way that makes sense to them. It’s the opposite to closed card sorting, in that participants dictate the categories themselves and also label them. This means you’d provide them with the cards only, and no categories.

Card sorting, whether open or closed, is very user focused. It involves a lot of thought, input, and evaluation from each participant, helping you to form the structure of your new IA.


What is tree testing and why should I use it?

Tree testing is a fantastic way to determine how your users are navigating your site and how they’re finding information. Your site is organized into a tree structure, sorted into topics and subtopics, and participants are provided with some tasks that they need to perform. The results will show you how your participants performed those tasks, if they were successful or unsuccessful, and which route they took to complete the tasks. This data is extremely useful for creating a new and improved IA.

Tree testing is an activity that requires participants to seek information, which is quite the contrast to card sorting. Card sorting is an activity that requires participants to sort and organize information. Each activity requires users to behave in different ways, so each method will give its own valuable results.


Comparing tree testing and card sorting: Key differences

Tree testing and card sorting are complementary methods within your UX toolkit, each unlocking unique insights about how users interact with your site structure. The difference is all about direction.

Card sorting is generative. It helps you understand how users naturally group and label your content; revealing mental models, surfacing intuitive categories, and informing your site’s information architecture (IA) from the ground up. Whether using open or closed methods, card sorting gives users the power to organize content in ways that make sense to them.

Tree testing is evaluative. Once you’ve designed or restructured your IA, tree testing puts it to the test. Participants are asked to complete find-it tasks using only your site structure – no visuals, no design – just your content hierarchy. This highlights whether users can successfully locate information and how efficiently they navigate your content tree.

In short:

  • Card sorting = "How would you organize this?"
  • Tree testing = "Can you find this?"


Using both methods together gives you clarity and confidence. One builds the structure. The other proves it works.


Which method should you choose?

The right method depends on where you are in your IA journey. If you're beginning from scratch or rethinking your structure, starting with card sorting is ideal. It will give you deep insight into how users group and label content.

If you already have an existing IA and want to validate its effectiveness, tree testing is typically the better fit. Tree testing shows you where users get lost and what’s working well. Think of card sorting as how users think your site should work, and tree testing as how they experience it in action.


Should you run a card or tree test first?

In this scenario, I’d recommend running a tree test first in order to find out how your existing IA currently performs. You said your gut instinct is telling you that your existing IA is pretty “broken”, but it’s good to have the data that proves this and shows you where your users get lost.

An initial tree test will give you a benchmark to work with – after all, how will you know your shiny, new IA is performing better if you don’t have any stats to compare it with? Your results from your first tree test will also show you which parts of your current IA are the biggest pain points and from there you can work on fixing them. Make sure you keep these tasks on hand – you’ll need them later!

Once your initial tree test is done, you can start your card sort, based on the results from your tree test. Here, I recommend conducting an open card sort so you can understand how your users organize the content in a way that makes sense to them. This will also show you the language your participants use to name categories, which will help you when you’re creating your new IA.

Finally, once your card sort is done you can conduct another tree test on your new, proposed IA. By using the same (or very similar) tasks from your initial tree test, you will be able to see that any changes in the results can be directly attributed to your new and improved IA.

Once your test has concluded, you can use this data to compare the performance from the tree test for your original information architecture.


Why using both methods together is most effective

Card sorting and tree testing aren’t rivals, view them as allies. Used together, they give you end-to-end clarity. Card sorting informs your IA design based on user mental models. Tree testing evaluates that structure, confirming whether users can find what they need. This combination creates a feedback loop that removes guesswork and builds confidence. You'll move from assumptions to validation, and from confusion to clarity – all backed by real user behavior.

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Online card sorting: The comprehensive guide

When it comes to designing and testing in the world of information architecture, it’s hard to beat card sorting. As a usability testing method, card sorting is easy to set up, simple to recruit for and can supply you with a range of useful insights. But there’s a long-standing debate in the world of card sorting, and that’s whether it’s better to run card sorts in person (moderated) or remotely over the internet (unmoderated).

This article should give you some insight into the world of online card sorting. We've included an analysis of the benefits (and the downsides) as well as why people use this approach. Let's take a look!

How an online card sort works

Running a card sort remotely has quickly become a popular option just because of how time-intensive in-person card sorting is. Instead of needing to bring your participants in for dedicated card sorting sessions, you can simply set up your card sort using an online tool (like our very own OptimalSort) and then wait for the results to roll in.

So what’s involved in a typical online card sort? At a very high level, here’s what’s required. We’re going to assume you’re already set up with an online card sorting tool at this point.

  1. Define the cards: Depending on what you’re testing, add the items (cards) to your study. If you were testing the navigation menu of a hotel website, your cards might be things like “Home”, “Book a room”, “Our facilities” and “Contact us”.
  2. Work out whether to run a closed or open sort: Determine whether you’ll set the groups for participants to sort cards into (closed) or leave it up to them (open). You may also opt for a mix, where you create some categories but leave the option open for participants to create their own.
  3. Recruit your participants: Whether using a participant recruitment service or by recruiting through your own channels, send out invites to your online card sort.
  4. Wait for the data: Once you’ve sent out your invites, all that’s left to do is wait for the data to come in and then analyze the results.

That’s online card sorting in a nutshell – not entirely different from running a card sort in person. If you’re interested in learning about how to interpret your card sorting results, we’ve put together this article on open and hybrid card sorts and this one on closed card sorts.

Why is online card sorting so popular?

Online card sorting has a few distinct advantages over in-person card sorting that help to make it a popular option among information architects and user researchers. There are downsides too (as there are with any remote usability testing option), but we’ll get to those in a moment.

Where remote (unmoderated) card sorting excels:

  • Time savings: Online card sorting is essentially ‘set and forget’, meaning you can set up the study, send out invites to your participants and then sit back and wait for the results to come in. In-person card sorting requires you to moderate each session and collate the data at the end.
  • Easier for participants: It’s not often that researchers are on the other side of the table, but it’s important to consider the participant’s viewpoint. It’s much easier for someone to spend 15 minutes completing your online card sort in their own time instead of trekking across town to your office for an exercise that could take well over an hour.
  • Cheaper: In a similar vein, online card sorting is much cheaper than in-person testing. While it’s true that you may still need to recruit participants, you won’t need to reimburse people for travel expenses.
  • Analytics: Last but certainly not least, online card sorting tools (like OptimalSort) can take much of the analytical burden off you by transforming your data into actionable insights. Other tools will differ, but OptimalSort can generate a similarity matrix, dendrograms and a participant-centric analysis using your study data.

Where in-person (moderated) card sorting excels:

  • Qualitative insights: For all intents and purposes, online card sorting is the most effective way to run a card sort. It’s cheaper, faster and easier for you. But, there’s one area where in-person card sorting excels, and that’s qualitative feedback. When you’re sitting directly across the table from your participant you’re far more likely to learn about the why as well as the what. You can ask participants directly why they grouped certain cards together.

Online card sorting: Participant numbers

So that’s online card sorting in a nutshell, as well as some of the reasons why you should actually use this method. But what about participant numbers? Well, there’s no one right answer, but the general rule is that you need more people than you’d typically bring in for a usability test.

This all comes down to the fact that card sorting is what’s known as a generative method, whereas usability testing is an evaluation method. Here’s a little breakdown of what we mean by these terms:

Generative method: There’s no design, and you need to get a sense of how people think about the problem you’re trying to solve. For example, how people would arrange the items that need to go into your website’s navigation. As Nielsen Norman Group explains: “There is great variability in different people's mental models and in the vocabulary they use to describe the same concepts. We must collect data from a fair number of users before we can achieve a stable picture of the users' preferred structure and determine how to accommodate differences among users”.

Evaluation method: There’s already a design, and you basically need to work out whether it’s a good fit for your users. Any major problems are likely to crop up even after testing 5 or so users. For example, you have a wireframe of your website and need to identify any major usability issues.

Basically, because you’ll typically be using card sorting to generate a new design or structure from nothing, you need to sample a larger number of people. If you were testing an existing website structure, you could get by with a smaller group.

Where to from here?

Following on from our discussion of generative versus evaluation methods, you’ve really got a choice of 2 paths from here if you’re in the midst of a project. For those developing new structures, the best course of action is likely to be a card sort. However, if you’ve got an existing structure that you need to test in order to usability problems and possible areas of improvement, you’re likely best to run a tree test. We’ve got some useful information on getting started with a tree test right here on the blog.

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How to get started with tree testing 🌱

Are your visitors really getting the most out of your website? Tree testing (or sometimes referred to as reverse card sorting) takes away the guesswork by telling you how easily, or not, people can find information on your website. Discover why Treejack is the tool of choice for website architects.

What’s tree testing and why does it matter? 🌲 👀

Whether you’re building a website from scratch or improving an existing website, tree testing helps you design your website architecture with confidence. How? Tools like Treejack use analysis to help assess how findable your content is for people visiting your website. 

It helps answer burning questions  like:

  • Do my labels make sense?
  • Is my content grouped logically?
  • Can people find what they want easily and quickly?  If not, why not?

Treejack provides invaluable intel for any Information Architect. Why? Knowing where and why people get lost trying to find your content, gives you a much better chance of fixing the actual problem. And the more easily people can find what they’re looking for, the better their experience which is ultimately better for everyone.

How’s tree testing work? 🌲🌳🌿

Tree testing can be broken down into two main parts: 

  • The Tree - Your tree is essentially your site map – a text-only version of your website structure.
  • The Task - Your task is the activity you ask participants to complete by clicking through your tree and choosing the information they think is right. Tools like Treejack analyse the data generated from doing the task to build a picture of how people actually navigated your content in order to try and achieve your task.  It tells you if they got it right or wrong, the path they took and the time it took them.

Whether you’re new to tree testing or already a convert, effective tree testing using Treejack has some key steps.

Step 1.  The ‘ Why’:  Purpose and goals of tree testing

Ask yourself what part of your information architecture needs improvement – is it your whole website or just parts of it? Also think about your audience, they’re the ones you’re trying to improve the website for so the more you know about their needs the better. 

Tip:  Make the most of what tree testing offers to improve your website by building it into your overall design project plan

Step 2.  The ‘How’:   Build your tree

You can build your tree using two main approaches: 

  • Create your tree in spreadsheet and import it into Treejack or
  • Build your tree in Treejack itself, using the labels and structure of your website.

Tip:  Your category labels are known as ‘parent nodes’. Your information labels are known as ‘child nodes’.

Step 3. The ‘What’: Write your tasks

The quality of your tasks will be reflected in the usefulness of your data so it’s worth making sure you create tasks that really test what you want to improve.

Tip:  Use plain language that feels natural and try to write your tasks in a way that reflects the way people who visit your website might actually think when they are trying to find information on your site.

Step 4.  The ‘Who’:  Recruit participants

The quality of your data will largely depend on the quality of your participants. You want people who are as close to your target audience as possible and with the right attitude - willing and committed to being involved.

Tip:  Consider offering some kind of incentive to participants – it shows you value their involvement.

Step 5.  The ‘insights’: Interpret your results

Now for the fun part – making sense of the results. Treejack presents the data from your tree testing as a series of tables and visualizations. You can download them in a spreadsheet in their raw format or customized to your needs.

Tip:  Use the results to gain quick, practical insights you can act on right away or as a starter to dive deeper into the data.

When should I use tree testing? ⌛

Tree testing is useful whenever you want to find out if your website content is labelled and organised in a way that’s easy to understand.  What’s more it can be applied for any website, big (10+ levels with 10000s of labels) or small (3 levels and 22 labels) and any size in between.  Our advice for using Treejack is simply this: test big, test small, test often.

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Live training: How to benchmark an existing site structure using Treejack

If you missed our live training, don’t worry, we’ve got you covered! In this session, our product experts Katie and Aidan discuss why, how and when to benchmark an existing structure using Treejack.

They also talk through some benchmarking use cases, demo how to compare tasks between different studies, and which results are most helpful.

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