Define your goals: Start by outlining the key objectives of your study. Are you looking to test a new product prototype, gather feedback on existing features, or understand user preferences? This ensures that every question or task serves a purpose and contributes to your overall research objectives.

Define your target audience: Clarify who your ideal participants are. Knowing this will help in designing relevant screening questions and ensuring the responses you collect come from individuals who match your research criteria.

Recommended length: Keep your study to a maximum of 10 minutes. This timeframe is ideal for preventing cognitive overload in participants, helping maintain their focus and providing more reliable responses.

Test the timing: Use the Preview link in Draft mode to share the study with a colleague and confirm the time it takes to complete.

Closing rules: Set the study's closing rule to manual to prevent unexpected issues with participant access. While some users may choose to set a participant limit or specify a closing date, these restrictions could inadvertently block participants from joining.

Pre-screening and questions: If participant data is necessary for segmentation or analysis (e.g., age range, geographic information), include pre-study or post-study questions to collect this information. This is crucial because while pre-screening can filter for certain attributes like income, no personally identifiable information (PII) is provided by panels. To access specific data such as age or location, make sure these questions are embedded within your study.

Task clarity: Ensure each task is clear, concise, and directly related to your research goals. Tasks should guide participants without ambiguity to avoid misinterpretation.

Prototype Testing tips: When writing tasks for prototype testing, phrase them in a way that mimics real-world scenarios participants would encounter. This helps obtain authentic feedback on the usability of your product or prototype.

Card labeling for Card Sorting: Use simple, intuitive labels for each card to enhance comprehension and accuracy. Clear labels reduce confusion and make it easier for participants to complete the task confidently.

Avoid leading or suggestive language: Some leading language might prime participants on how to perform a task or sway a participant’s response. For example, instead of asking, Frame questions in a way that doesn’t imply a “correct” answer or suggest how participants should feel. For example, in a survey, instead of "What did you think of the fast loading time?" use "How would you rate the loading time?"

Collect feedback from diverse group: Recruit a varied group of participants to ensure that your findings represent a wide range of users and perspectives, helping to reduce demographic biases.

Why randomize? Randomizing the order of tasks can help minimize bias, as earlier tasks might otherwise influence responses to later ones. This ensures participants approach each task independently, enhancing the integrity of your data.

Additional options: When enabling random task order, consider the available options for customizing the sequence to suit your study's needs.

Pilot your study: Before launching, conduct a pilot test with a small group of colleagues or a limited sample of participants. This helps you identify any potential issues with task clarity, timing, or study structure.

Adjust based on feedback: Use feedback from the pilot to make necessary adjustments that improve the overall experience for participants and the quality of the data you collect.