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!
Improved organization, privacy controls, and more with new Workspaces 🚀
One of our key priorities in 2024 is making Optimal Workshop easier for large organizations to manage teams and collaborate more effectively on delivering optimal digital experiences. Workspaces is going live this week, which replaces teams, and introduces projects and folders for improved organization and privacy controls. Our latest release lays the foundations to provide more control over managing users, licenses, and user roles in the app in the near future.
More control with project privacy 🔒
Private projects allow greater flexibility on who can see what in your workspace, with the ability to make projects public or private and manage who can access a project. Find out more about how to set up private projects in this help article.
What changes for Enterprise customers? 😅
The teams you have set up today will remain the same; they are renamed workspaces.
Studies will be moved to a 'Default project' within the new workspace, from here you can decide how you would like to organize your studies and access to them.
You can create new projects, move studies into them, and use the new privacy features to control who has access to studies or leave them as public access.
Optimal Workshop are here to help if you would like to review your account structure and make changes, please reach out to your Customer Success Manager.
What changes for Professional and Team customers? 😨
Customers on either a Professional or Team plan will notice the studies tab will now be called Workspace. We have introduced another layer of organization called projects, and there is a new-look sidebar on the left to create projects, folders, and studies.
What's next for Workspaces? 🔮
This new release is an essential step towards improving how we manage users, licenses, and different role types in Optimal Workshop. We hope to deliver more updates, such as the ability to move studies between workspaces, in the near future. If you have any feedback or ideas you want to share on workspaces or Optimal Workshop, please email product@optimalworkshop.com; we'd love to hear from you.
Today, we’re thrilled to announce the arrival of the latest member of the Optimal family: Prototype Testing! This exciting and much-requested new tool allows you to test designs early and often with users to gather fast insights, and make confident design decisions to create more intuitive and user-friendly digital experiences.
Optimal gives you tools you need to easily build a prototype to test using images and screens and creating clickable areas, or you can import a prototype from Figma and get testing. The first iteration of prototype testing is an open beta, and we’ll be working closely with our customers and community to gather feedback and ideas for further improvements in the months to come.
When to use prototype testing
Prototype testing is a great way to validate design ideas, identify usability issues, and gather feedback from users before investing too heavily in the development of products, websites, and apps. To further inform your insights, it’s a good idea to include sentiment questions or rating scales alongside your tasks.
Early in the design process: Test initial ideas and concepts to gauge user reactions and feelings about your conceptual solutions.
Iterative design phases: Continuously test and refine prototypes as you make changes and improvements to the designs.
Before major milestones: Validate designs before key project stages, such as stakeholder reviews or final approvals.
Usability Testing: Conduct summative research to assess a design's overall performance and gauge real user feedback to guide future design decisions and enhancements.
How it works 🧑🏽💻
No existing prototype? No problem. We've made it easy to create one right within Optimal. Here's how:
Import your visuals
Start by uploading a series of screenshots or images that represent your design flow. These will form the backbone of your prototype.
Create interactive elements
Once your visuals are in place, it's time to bring them to life. Use our intuitive interface to designate clickable areas on each screen. These will act as navigation points for your test participants.
Set up the flow
Connect your screens in a logical sequence, mirroring the user journey you want to test. This creates a seamless, interactive experience for your participants.
Preview and refine
Before launching your study, take a moment to walk through your prototype. Ensure all clickable areas work as intended and the flow feels natural.
The result? A fully functional prototype that looks and feels like a real digital product. Your test participants will be able to navigate through it just as they would a live website or app, providing you with authentic, actionable insights.
By empowering you to build prototypes from scratch, we're removing barriers to early-stage testing. This means you can validate ideas faster, iterate with confidence, and ultimately deliver better digital experiences.
Or…import your prototypes directly from Figma
There’s a bit of housekeeping you’ll need to do in Figma in order to provide your participants with the best testing experience and not impact loading times of the prototype. You can import a link to your Figma prototype into your study, and it will carry across all the interactions you have set up. You’ll need to make sure your Figma presentation mode is made public in order to share the file with participants. If you make any updates to your Figma file, you can sync the changes in just one click.
When you set up your study, you’ll create tasks for participants to complete.
There are two different ways to build tasks in your prototype tests. You can set a correct destination by adding a start screen and a correct destination screen. That way, you can watch how participants navigate your design to find their way to the correct destination. Another option is to set a correct pathway and evaluate how participants navigate a product, app, or website based on the pathway sequence you set. You can add as many pathways or destinations as you like.
Adding post-task questions is a great way to help gather qualitative feedback on the user's experience, capturing their thoughts, feelings, and perceptions.
Prototype testing offers a variety of analysis options and metrics to evaluate the effectiveness and usability of your design. By using these analysis options and metrics, you can get comprehensive insights into your prototype's performance, identify areas for improvement, and make informed design decisions:
Task results
The task results provide a deep analysis at a task level, including the success score, directness score, time taken, misclicks, and the breakdown of the task's success and failure. They provide great insight into the usability of your design to achieve a task.
Success score tells you the total percentage of participants who reached the correct destination or pathway that you defined for this task. It’s a good indicator of a prototype's usability.
Directness score is the total completed results minus the ‘indirect’ results.
A path is ‘indirect’ when a participant backtracks, viewing the same page multiple times, or if they nominate the correct destination but don’t follow the correct pathway
Time taken is how long it took a participant to complete your task and can be a good indicator of how easy or difficult it was to complete.
Misclicks measure the total number of clicks made on areas of your prototype that weren’t clickable, clicks that didn’t result in a page change.
Clickmaps
Clickmaps provide an aggregate view of user interactions with prototypes, visualizing click patterns to reveal how users navigate and locate information. They display hits and misses on designated clickable areas, average task completion times, and heatmaps showing where users believed the next steps to be. Filters for first, second, and third page visits allow analysis of user behavior over time, including how they adapt when backtracking. This comprehensive data helps designers understand user navigation patterns and improve prototype usability.
Participant paths
The Paths tab in Optimal provides a powerful visualization to understand and identify common navigation patterns and potential obstacles participants encounter while completing tasks. You can include thumbnails of your screens to enhance your analysis, making it easier to pinpoint where users may face difficulties or where common paths occured.
Coming soon to prototyping 🔮
Later this year, we’re running a closed beta for video recording with prototype testing. This feature captures behaviors and insights not evident in click data alone. The browser-based recording requires no plugins, simplifying setup. Consent for recording is obtained at the start of the testing process and can be customized to align with your organization's policies. This new feature will provide deeper insights into user experience and prototype usability.
These enhancements to prototype testing offer a comprehensive toolkit for user experience analysis. By combining quantitative click data with qualitative video insights, designers and researchers can gain a more nuanced understanding of user behavior, leading to more informed decisions and improved product designs.
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.
Comments left by your participants can be viewed in the “Participants” tab in your results section, and are indicated by a grey speech bubble.
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.
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”.
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”.
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.
#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.
