At Optimal, we believe in the transformative potential of AI to accelerate your workflow and time to insights. Our goal is simple: keep humans at the heart of every insight while using AI as a powerful partner to amplify your expertise. 

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By automating repetitive tasks, providing suggestions for your studies, and streamlining workflows, AI frees you up to focus on what matters most—delivering impact, making strategic decisions, and building products people love.

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That’s why we’re excited to announce our latest AI feature: AI-Powered Question Simplification. 

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Simplify and Refine Your Questions Instantly

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Ambiguous or overly complex wording can confuse respondents, making it harder to get reliable, accurate insights. Plus, refining survey and question language is manual and can be a time-consuming process with little guidance. To solve this, we built an AI-powered tool to help study creators craft questions that resonate with participants and speed up the process of designing studies.

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Our new AI-powered feature helps with:

• Instant Suggestions: Simplify complex question wording and improve clarity to make your questions easier to understand.
• Seamless Editing: Accept, reject, or regenerate suggestions with just a click, giving you complete control.
• Better Insights: By refining your questions, you’ll gather more accurate responses, leading to higher-quality data that drives better decisions.
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Apply AI-Powered Question Simplification to any of your survey questions or to screening questions, and pre- and post-study questions in prototype tests, surveys, card sorts, tree tests, and first-click tests.
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AI: Your Research Partner, Not a Replacement

AI is at the forefront of our innovation at Optimal this year, and we’re building AI into Optimal with clear principles in mind:
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1. AI does the tedious work: It takes on repetitive, mundane tasks, freeing you to focus on insights and strategy.
2. AI assists, not dictates: You can adapt, change, or ignore AI suggestions entirely.
3. AI is a choice: We recognize that Optimal users have diverse needs and risk appetites. You remain in control of how, when, and if you use AI.
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A Growing Suite of AI-Powered Tools

The introduction of Question Simplification is just one example of how we’re leveraging AI to make research more efficient and effective for people who do research.

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In 2024, we launched our AI Insights within our Qualitative Insights tool, summarizing key takeaways from interviews and transcripts. Now, we’re diving even deeper, exploring more ways to use AI to make research more efficient and effective.
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Ready to Get Started? 

Keep an eye out for more updates throughout 2025 as we continue to expand our platform with AI-powered features that help you uncover insights with speed, clarity, and more confidence.

Want to see how AI can speed up your workflow?

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Apply AI-Powered Question Simplification today or check out AI Insights to experience it for yourself!

Inspired by insights from Optimal users, we’ve reimagined study creation to bring you a beautifully streamlined experience with the new Study Flow tab.

With the new Study Flow, you’ll: 

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⚡ Enjoy faster study set up: Messages & instructions and Questionnaire tabs are combined in a single tab - called Study Flow - for faster editing and settings customization.

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✨ See it all at a glance: Easily visualize and understand the participant experience—from the welcome message to the final thank-you screen—every step of the way. 

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🎯 Duplicate questions: Save time and quickly replicate questions for surveys, screening questions, and pre- and post-study questions. 

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⭐ Experience enhanced UI: Enjoy a modern, clean design with intuitive updates that minimize scrolling and reduce mental load.

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🗂️ Collapse and expand sections: Easily navigate studies by collapsing and expanding sections, making it easier to build out specific parts of your study.

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This Study Flow tab is available across all Optimal tools, except for Qualitative Insights. 

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What’s next?

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We’re not stopping there. We have some significant improvements on the horizon designed to give you even greater flexibility and control.

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Advanced logic: Enhanced logic capabilities is one of our most highly requested features, and we’re thrilled to introduce new capabilities to help you build your ideal study experience – available for surveys and other tools. We will first introduce “display logic”, allowing for: 

• If answer is X for Question Y, then hide/show Question Z.
• If answer is X for Question Y, then hide/show specific answer options.

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Customizable sections: Organize your questions into different sections to build a better study experience for your participants. For example, segment your questions into relevant groupings, such as demographics or product usage. With custom sections, you can add new sections, rename, reorder, duplicate, and move questions between different sections.* 

*Note: Questions cannot be moved to/from the screening questions section.

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These upcoming features will empower you to create dynamic, tailored study experiences for different audiences with ease for more valuable insights. 

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Start exploring the new Study Flow now.

At Optimal Workshop, we're dedicated to building the best user research platform to empower you with the tools to better understand your customers and create intuitive digital experiences. We're thrilled to announce some game-changing updates and new products that are on the horizon to help elevate the way you gather insights and keep customers at the heart of everything you do. 

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What’s new…

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Integration with Figma 🚀

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Last month, we joined forces with design powerhouse Figma to launch our integration. You can import images from Figma into Chalkmark (our click-testing tool) in just a few clicks, streamlining your workflows and getting insights to make decisions based on data not hunches and opinions.  

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What’s coming next…

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Session Replays 🧑‍💻

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With session replay you can focus on other tasks while Optimal Workshop automatically captures card sort sessions for you to watch in your own time.  Gain valuable insights into how participants engage and interpret a card sort without the hassle of running moderated sessions. The first iteration of session replays captures the study interactions, and will not include audio or face recording, but this is something we are exploring for future iterations. Session replays will be available in tree testing and click-testing later in 2024.  

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Reframer Transcripts 🔍

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Say goodbye to juggling note-taking and hello to more efficient ways of working with Transcripts! We're continuing to add more capability to Reframer, our qualitative research tool, to now include the importing of interview transcripts. Save time, reduce human errors and oversights by importing transcripts, tagging and analyzing observations all within Reframer. We’re committed to build on transcripts with video and audio transcription capability in the future,  we’ll keep you in the loop and when to expect those releases. 

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Prototype testing 🧪

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The team is fizzing to be working on a new Prototype testing product designed to expand your research methods and help test prototypes easily from the Optimal Workshop platform. Testing prototypes early and often is an important step in the design process, saving you time and money before you invest too heavily in the build. We are working with customers and on delivering the first iteration of this exciting new product. Stay tuned for Prototypes coming in the second quarter of 2024.   

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Workspaces 🎉

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Making Optimal Workshop easier for large organizations to manage teams and collaborate more effectively on projects is a big focus for 2024. Workspaces are the first step towards empowering organizations to better manage multiple teams with projects. Projects will allow greater flexibility on who can see what, encouraging working in the open and collaboration alongside the ability to make projects private. The privacy feature is available on Enterprise plans.

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Questions upgrade❓

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Our survey product Questions is in for a glow up in 2024 💅. The team are enjoying working with customers, collecting and reviewing feedback on how to improve Questions and will be sharing more on this in the coming months. 

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Help us build a better Optimal Workshop

We are looking for new customers to join our research panel to help influence product development. From time to time, you’ll be invited to join us for interviews or surveys, and you’ll be rewarded for your time with a thank-you gift.  If you’d like to join the team, email product@optimalworkshop.com

This is a guest post from our friends over at Askable. Check out their blog.

Writing screening questions is an everyday part of life as a UXer or researcher of any kind, really. And at first glance, they seem straightforward enough. Draft up some questions that help to either qualify or disqualify people from taking part in your research, whether that’s a survey, an interview or something in between.

At Askable, we have seen thousands and thousands of screening questions. Some horrible and some amazing - and everything in between.

So here we go – 5 of the most common mistakes made when writing screening questions – oh and how to avoid them.

1. Using closed-ended questions too often

What’s the quickest way of knowing if someone went on a holiday in the last 6 months… You ask them, right? “Have you been on a holiday in the last 6 months – Yes or No?”. Duh.

But actually, a question worded in this way is signposting the answer you’re looking for, which may lead to false answers! And also, the answer doesn’t give you any extra information about that person’s travel habits, etc.

So, perhaps a better way to ask the question would be: “When was the last time you went on a holiday?” Provide multiple choices. This also gives you that added info, like if it was a month ago or 5 months ago, in this case.

2. Using open-ended questions at the wrong time

Open-ended screening questions can be great, but only for certain info. Avoid using them when you have strict criteria. But instead, use them for getting inside your applicant’s head a bit more. An example would be to ask as a follow up to the example above “Tell me about where you went on your last holiday”.

Open-ended questions are also fine when the answers could vary wildly. A good example is “What is your occupation”. There are simply way too many possible responses to have as a multi-choice.

3. Using industry jargon

How many people in the general public know what EV stands for? It’s Electric Vehicle by the way.

Or how about the term ‘Financial Services’? Are we talking about a bank or payments company or an accountant?

Work off the lowest common denominator, assume the applicant doesn’t know anything about your industry. Because often, they don’t or they think of it differently to you. When we live and breathe a topic, it’s all too easy to forget that others do not.

4. Too many screening questions

We often write too many screening questions for a number of reasons. Sometimes we do it because we forget that screening questions are just that – to screen. Not to survey! Don’t start adding questions in there that are actually part of your research.

Other times it can be because our criteria is just way too narrow. Whatever the reason, a good rule of thumb is to never have more than 15 and the less the better.

5. Not trusting the majority

We have learned this time and time again at Askable – most people are good and honest! We even have a saying now for it – “default to honesty”.

Don’t get overly concerned that your screening questions give too much away. Of course, keep it vague, but don’t go crazy. The 99% of people in our experience won’t take advantage of you. So serve the 99 and not the 1.

Wrap Up

Think about these next time you are writing up some screening questions, setting up your research or trying to figure out who it is you really want to talk with. Do this and you will be on your way to some seriously awesome and accurate insights!

“The art and science of asking questions is the source of all knowledge.”- Thomas Berger

In 1974, Elizabeth Loftus and John Palmer conducted a simple study to illustrate the impact of different wording on responses to a question. The two researchers quizzed their participants on an accident that occurred, asking them to recall the speed that two vehicles were traveling before the incident happened.

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One of the questions Loftus and Palmer asked was: “About how fast were the cars going when they smashed into each other?”, which elicited higher speed estimates than questions containing the verbs ‘collided’, ‘bumped’, ‘contacted’ or ‘hit’. Unsurprisingly the ‘smashed’ group was also more likely to recall seeing broken glass at the scene, without there being any glass present.Small wording changes can impact your data in a big way. The way you ask a question not only frames how a person responds to it, but it can introduce unintended bias in your findings. If you intend to use the data you collect in meaningful ways — to identify issues, deepen your understanding or make evidence-based decisions — you want to ensure your data is of the highest possible quality. The best way to be confident that you’re collecting quality data and not wasting your time and resources is knowing how to avoid the common mistakes that plague question design.

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Regardless of whether you’re adding some pre- or post-survey questions to your Treejack, OptimalSort or Chalkmark survey, or simply aiming to ask your questions on paper, in person or your website, there are some basic principles you should follow. But first…

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Questionnaire = survey?

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Questionnaire and survey are terms that are frequently used interchangeably, and it is often tempting to use them synonymously. Unless you’re a word purist, chances are people will understand what you’re saying regardless of the term you use, however, it’s good to be aware of their differences in order to understand how they relate.A survey is a type of research design. It’s the process of gathering information for the purpose of measuring something, which encompasses everything from design, sampling, data collection and analysis. Surveys involve aggregating your data to reveal patterns and draw conclusions.

A questionnaire is a method of data collection.

Traditionally, questionnaires are used to collect information on an individual level, and have use cases such as job or loan applications, patient history forms etc. Think of questionnaires as an instrument you can use within conducting a wider survey, alongside other methods such as face-to-face interviews.There are differences involved in collecting survey information by post, email, online, telephone or face to face, and each method comes with its own set of advantages and disadvantages to consider. For now, however, let’s keep things simple, and focus on the very basic principles that will hold true regardless of the method you choose.

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Here are some practical tips to help you become a confident question writer.

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1. Think clearly about your needs 🤔💭

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Clearly define your objectives. Start by asking yourself “What do I really need to learn?”When planning research, it’s tempting to jump right into writing your questions. However, taking a step back can save you a lot of time and frustration later down the road. Start by thinking about what you want to get out of your questions. Understand your information needs, draft your research questions and review them with your team or stakeholders before proceeding. Once you know what you want to get out of your study, you can narrow your focus and start to think about your objectives in greater detail. Being precise about the data you want to get out of your questions means it will be easier to plan how to organize and filter your findings.

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2. Choose your words wisely 💬

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Badly worded questions lead to poor quality data. To help you write better questions it’s good to be aware of seemingly obvious, yet common mistakes that can plague question writing. Here are some tips to follow.

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Use clear, plain language.

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Avoid technical descriptions, acronyms and jargon. If necessary, add a definition or some help text around your question to avoid confusion.

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Be specific.

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Avoid ambiguity in what you are asking. The more specific your question is, the more likely people are to understand it in the same way. “Where do you usually shop?” will likely be interpreted differently by each respondent.

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Ensure your questions are neutral and unbiased.

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Bias can be introduced into your questions in many ways:

• Avoid asking double-barrelled questions, e.g., “How satisfied are you with the use and visual feel of our website?”. Instead, stick to asking one question at a time.
• Leading or loaded questions use assumptions and emotional language to elicit particular responses. They (intentionally or unintentionally) bias respondents towards certain answers, e.g., “How happy are you with our service?” would become “How do you feel about our service?”

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Set realistic timeframes.

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Utilizing appropriate timeframes in your questions leads to better estimates and more reliable data from your respondents. When providing timeframes, be sure to keep them reasonable — some behaviors can be asked on a yearly basis (e.g., switching internet providers), while others are easier to think of over the space of a week (e.g., supermarket visits).It is also important to be realistic about how much people are able to remember over time. If asking about satisfaction with a service in the past year, people are most likely to remember either their most recent, or their worst experiences. Sticking to reasonable recall periods will lead to better quality data.

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Don’t assume.

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The way we experience the world influences our thinking, and it is important to be aware of your own biases to avoid questions that make assumptions, e.g., “How many UX Researchers do you have at your company?”.

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Don’t play the negatives game.

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Avoid the use of negatives and double negatives when writing your questions. On a cognitive level, negative questions take more time to comprehend and process. Double negatives include two negative aspects within a question e.g., “Do you agree or disagree that it is not a good idea to not show up to work on time”. Negatives and double negatives can lead to confusion and contradictory responses.

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3. Think about your audience 👨👩👦👦

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Who is likely to answer your questions? What are the characteristics of the people you are trying to target? Consider the group you are writing for, and what kind of language and terminology they may be familiar with. Remember that not everyone is a native speaker of your language and no matter how sophisticated your vocabulary might be, plain language is going to lead to a better result.Context is important and knowing your audience can impact their willingness to contribute to your research. Questions written for a sample of academics will differ in tone from those intended for high school students. Don’t be afraid to give your questions a casual feel if you’re trying to connect to a group that may otherwise be unwilling to provide their answers.

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4. Don’t burden your participants 😒😖😩

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No matter how great your questions are, if they are too long, complex or repetitive, it’s likely your respondents will quickly lose interest. Bored respondents lead to not only poor quality data, but also higher nonresponse rates. Some subject areas lend themselves to higher respondent burden by nature, for example insurance, mortgages, or medical histories.Generally if it’s not an immediate priority, avoid unnecessary details. A shorter set of high quality data is more valuable than a whole stack of potentially erroneous data collected via a lengthy questionnaire. One way to remedy respondent burden is to offer incentives like vouchers, discount codes or competition entries. Giving people a good reason to answer your questions will not only make it easier for you to find willing respondents, but may increase engagement and lead to higher quality data.

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5. Consider your response options (and avoid data insanity) 📊 🤪

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It is important to be pragmatic when choosing your response options to avoid being swarmed with data that’s difficult to handle and analyze.Open questions invite respondents to elaborate and can help in identifying themes that closed questions may overlook. So, on the one hand they can provide a wealth of useful information, but on the other it is important to consider their practicality. If you want to collect 1,000 responses but don’t have the time or resources to review a multitude of varying open-ended data, consider whether it’s worth collecting in the first place. Open ended questions can be useful when you’re not quite sure what you’re looking for, so unless you’re running an exploratory study on a small group of people, try to limit their use.

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Closed questions force respondents to select an existing option from a list. They are quick to fill in, and easy to code and analyze. Closed questions can include tick boxes, scales or single choice radio buttons. When asking closed questions it’s important to ensure the response options you provide are balanced, exclusive (they don’t overlap) and exhaustive (they contain all possible answers), even if this means adding an ‘other — please specify’ or a ‘not applicable’ option. For potentially sensitive questions, it’s important to give your respondents a ‘prefer not to say’ option, as forcing responses may lead to higher dropout rates and poor quality data.

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6. Think carefully about order ➤➤➤
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Question order is important as it can impact the truthfulness of the responses you collect.The general rule to follow is to start simple with easy, factual questions that are relevant to the objective of your survey. Additionally, it’s good to start with closed questions before introducing open-ended questions that may require more consideration. Once you get the basics out of the way, you can then introduce questions that are more specific, difficult, or abstract. Situate unrelated or demographic questions at the end. Once a rapport has been established your respondents will be more likely to answer these questions without dropping out.

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7. If in doubt, test 🧪🕵️

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Pretesting your questions before you go out to collect your data is a great way to identify any immediate issues. In a lot of cases, a simple peer review by a friend or colleague will help identify the things that are likely to cause problems for respondents. For evaluating your questions more thoroughly, you may want to observe people as they make their way through your survey. This is a good time to see whether respondents are understanding and interpreting your questions in the same way, and will help identify issues with wording and response options. Getting your participants to think aloud is a useful technique for understanding how people are working through your questions.

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8. Remember the basics! 🔤

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Always explain the purpose of your research to your participants and how the information you collect will be used. Provide a statement that guarantees confidentiality and outline who will have access to the information provided.Above all, remember to thank your participants for their time. We’re all human, and people want to know that their contribution is valuable and appreciated.

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Further reading 📚

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• The psychology of survey respondents - Our CEO Andrew discusses the different kinds of motivation people have to respond to surveys.
• How to ask about user satisfaction in a survey - An article by Caroline Jarrett on UXMatters talks about how to gauge the satisfaction of your users.
• Keep online surveys short - Jakob Nielsen from Nielsen Norman Group explains how to get high response rates and great results by using shorter surveys.
• Avoiding bias in user testing - Our very own Agony Aunt explains how to avoid bias in your user testing.
• Reconstruction of automobile destruction: An example of the interaction between language and memory - The original study from Loftus and Palmer showing the different questions and responses.