March 29, 2016
1 min read

Which comes first: card sorting or tree testing?

“Dear Optimal Workshop,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 — 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 organised 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 — 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.

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 — hopefully it is much better now!

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Empowering UX Careers: Designlab Joins Forces with Optimal Workshop

Optimal Workshop is thrilled to welcome Designlab as our newest education partner. This collaboration merges our strengths to provide innovative learning opportunities for UX professionals looking to sharpen their design skills and elevate their careers. 

The Power of a Design-First Education Partner

What makes Designlab unique is its exclusive focus on design education. For more than a decade, they have dedicated themselves to providing hands-on learning experiences that  combine asynchronous, online lessons and projects with synchronous group sessions and expert mentorship. With a robust catalog of industry-relevant courses and an alumni network of over 20,000 professionals, Designlab is committed to empowering designers to make an impact at both individual and team levels.

What Designlab Offers for Experienced Designers

Designlab offers a range of advanced programs that support ongoing professional development. Some courses that might be interesting for our audience include:

  • Data-Driven Design: Gain confidence in your ability to collect and interpret data, justify design decisions with business impact, and win over stakeholders. 
  • Advanced Figma: Accelerate your design workflow and become a more efficient Figma user by learning tools like components, auto-layout, and design tokens. 
  • Strategic Business Acumen for Designers: Learn the foundational business knowledge and frameworks you need to influence strategy and get your design career to the next level.  
  • Advanced Usability and Accessibility: Strengthen your usability and accessibility skills, integrate universal design principles into your work, and improve advocacy for inclusivity in design.  

These courses ensure that experienced designers can enhance their technical and strategic skills to solve complex problems, lead projects, and design user-centered experiences.

Solutions for Design Teams

Designlab also offers solutions for design teams looking to upskill together. These solutions can range from multi-seat enrollments to their courses to custom facilitation and training programs, perfectly tailored to your teams’ needs. By partnering with Designlab, companies ensure their teams are equipped with practical skills and a forward-thinking mindset to tackle design challenges effectively.

READ: Designing for Accessibility with The Home Depot

Special Offer for the Optimal Workshop Community

To celebrate this partnership, Optimal Workshop users can take advantage of a special discount—$100 off any Designlab course with the code OPTIMAL. Whether you’re looking to refine your skills or explore new areas of expertise, Designlab’s programs offer the perfect opportunity to invest in your professional growth.

Explore how Designlab’s offerings can help you level up your design career—whether it’s through mastering advanced tools, leveraging data more, or becoming a more strategic thinker. With continuous learning at the heart of success in UX and product design, there’s no better time to start your journey with Designlab.

Unlock your potential and discover new possibilities with Designlab’s courses today. Use code OPTIMAL to save $100 on your next course and take the next step in your design career.

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Ready for take-off: Best practices for creating and launching remote user research studies

"Hi Optimal Work,I was wondering if there are some best practices you stick to when creating or sending out different UX research studies (i.e. Card sorts, Prototyye Test studies, etc)? Thank you! Mary"

Indeed I do! Over the years I’ve learned a lot about creating remote research studies and engaging participants. That experience has taught me a lot about what works, what doesn’t and what leaves me refreshing my results screen eagerly anticipating participant responses and getting absolute zip. Here are my top tips for remote research study creation and launch success!

Creating remote research studies

Use screener questions and post-study questions wisely

Screener questions are really useful for eliminating participants who may not fit the criteria you’re looking for but you can’t exactly stop them from being less than truthful in their responses. Now, I’m not saying all participants lie on the screener so they can get to the activity (and potentially claim an incentive) but I am saying it’s something you can’t control. To help manage this, I like to use the post-study questions to provide additional context and structure to the research.

Depending on the study, I might ask questions to which the answers might confirm or exclude specific participants from a specific group. For example, if I’m doing research on people who live in a specific town or area, I’ll include a location based question after the study. Any participant who says they live somewhere else is getting excluded via that handy toggle option in the results section. Post-study questions are also great for capturing additional ideas and feedback after participants complete the activity as remote research limits your capacity to get those — you’re not there with them so you can’t just ask. Post-study questions can really help bridge this gap. Use no more than five post-study questions at a time and consider not making them compulsory.

Do a practice run

No matter how careful I am, I always miss something! A typo, a card with a label in the wrong case, forgetting to update a new version of an information architecture after a change was made — stupid mistakes that we all make. By launching a practice version of your study and sharing it with your team or client, you can stop those errors dead in their tracks. It’s also a great way to get feedback from the team on your work before the real deal goes live. If you find an error, all you have to do is duplicate the study, fix the error and then launch. Just keep an eye on the naming conventions used for your studies to prevent the practice version and the final version from getting mixed up!

Sending out remote research studies

Manage expectations about how long the study will be open for

Something that has come back to bite me more than once is failing to clearly explain when the study will close. Understandably, participants can be left feeling pretty annoyed when they mentally commit to complete a study only to find it’s no longer available. There does come a point when you need to shut the study down to accurately report on quantitative data and you’re not going to be able to prevent every instance of this, but providing that information upfront will go a long way.

Provide contact details and be open to questions

You may think you’re setting yourself up to be bombarded with emails, but I’ve found that isn’t necessarily the case. I’ve noticed I get around 1-3 participants contacting me per study. Sometimes they just want to tell me they completed it and potentially provide additional information and sometimes they have a question about the project itself. I’ve also found that sometimes they have something even more interesting to share such as the contact details of someone I may benefit from connecting with — or something else entirely! You never know what surprises they have up their sleeves and it’s important to be open to it. Providing an email address or social media contact details could open up a world of possibilities.

Don’t forget to include the link!

It might seem really obvious, but I can’t tell you how many emails I received (and have been guilty of sending out) that are missing the damn link to the study. It happens! You’re so focused on getting that delivery right and it becomes really easy to miss that final yet crucial piece of information.

To avoid this irritating mishap, I always complete a checklist before hitting send:

  • Have I checked my spelling and grammar?
  • Have I replaced all the template placeholder content with the correct information?
  • Have I mentioned when the study will close?
  • Have I included contact details?
  • Have I launched my study and received confirmation that it is live?
  • Have I included the link to the study in my communications to participants?
  • Does the link work? (yep, I’ve broken it before)

General tips for both creating and sending out remote research studies

Know your audience

First and foremost, before you create or disseminate a remote research study, you need to understand who it’s going to and how they best receive this type of content. Posting it out when none of your followers are in your user group may not be the best approach. Do a quick brainstorm about the best way to reach them. For example if your users are internal staff, there might be an internal communications channel such as an all-staff newsletter, intranet or social media site that you can share the link and approach content to.

Keep it brief

And by that I’m talking about both the engagement mechanism and the study itself. I learned this one the hard way. Time is everything and no matter your intentions, no one wants to spend more time than they have to. Even more so in situations where you’re unable to provide incentives (yep, I’ve been there). As a rule, I always stick to no more than 10 questions in a remote research study and for card sorts, I’ll never include more than 60 cards. Anything more than that will see a spike in abandonment rates and of course only serve to annoy and frustrate your participants. You need to ensure that you’re balancing your need to gain insights with their time constraints.

As for the accompanying approach content, short and snappy equals happy! In the case of an email, website, other social media post, newsletter, carrier pigeon etc, keep your approach spiel to no more than a paragraph. Use an audience appropriate tone and stick to the basics such as: a high level sentence on what you’re doing, roughly how long the study will take participants to complete, details of any incentives on offer and of course don’t forget to thank them.

Set clear instructions

The default instructions in Optimal Workshop’s suite of tools are really well designed and I’ve learned to borrow from them for my approach content when sending the link out. There’s no need for wheel reinvention and it usually just needs a slight tweak to suit the specific study. This also helps provide participants with a consistent experience and minimizes confusion allowing them to focus on sharing those valuable insights!

Create a template

When you’re on to something that works — turn it into a template! Every time I create a study or send one out, I save it for future use. It still needs minor tweaks each time, but I use them to iterate my template.What are your top tips for creating and sending out remote user research studies? Comment below!

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1 min read

Which comes first: card sorting or tree testing?

“Dear Optimal Workshop,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 — 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 organised 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 — 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.

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 — hopefully it is much better now!

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