Surveys play a crucial role in understanding user preferences, identifying pain points, and optimizing product experiences. They enable product teams to gather valuable insights, make informed decisions, and ultimately create successful products that resonate with users.
In Lyssna, you can create a survey using the design surveys feature or by using the questions test type in the test builder (which we explore in this article).
To get the most out of your surveys, it comes down to choosing the right question types – Short/Long text, Single/Multiple Choice, Linear scale, or Ranking. In this article, we delve into each question style, highlighting their respective use cases and explaining the rationale behind their selection. By understanding the right context for each question type, you can maximize the value of your surveys.
6 design survey question styles: How to choose the right style for optimal insights
Below, we explore the six different survey question styles in Lyssna and explain when to use each style to get the most out of your usability tests.
1. Short text survey questions
Short text questions allow participants to provide succinct open-ended responses, giving them the freedom to express their thoughts, ideas, or suggestions in their own words. This type of feedback is valuable in understanding users' perspectives and uncovering insights that may not be captured by predefined answer options.
By using short text survey questions strategically in your surveys, you can collect rich qualitative feedback, gain a contextual understanding, and refine your designs based on user input.
Examples of when to use short text survey questions:
Gathering user feedback on specific design elements: Ask participants to provide short text responses about their impressions, likes, or dislikes regarding specific design elements, such as color schemes, typography, or navigation menus.
Collecting qualitative data for user testing: For example, gathering feedback on usability issues, task completion difficulties, or overall user satisfaction.
Capturing user expectations or goals: This is useful when asking participants to interact with the design. For example, asking users to describe what they hope to achieve or what particular outcomes they’re looking for.
2. Long text survey questions
Long text questions allow participants to provide detailed and comprehensive responses, enabling them to express their thoughts, ideas, or suggestions more elaborately. This type of feedback can uncover nuanced insights and provide rich qualitative data for analysis.
Examples of when to use long text survey questions:
Conceptual feedback: Use long text questions to gather participants' in-depth thoughts and suggestions regarding conceptual aspects of a design. For instance, asking participants to explain their understanding of a design concept or provide detailed feedback on the overall user experience.
Exploring complex user scenarios: Asking participants to describe their interactions with a design in detail. For example, sharing the steps they took, any challenges they encountered, and suggestions for improvements.
Collecting user testimonials: Long text questions can be used to capture user testimonials or success stories. Ask participants to share their positive experiences, any outcomes they've achieved, or how your product has positively impacted their goals.
3. Single-choice survey questions
Single choice questions offer a straightforward format for participants to provide their feedback. Respondents simply select one option from a list of predefined choices, making it easy and quick to respond.
Examples of when to use single choice survey questions:
Feature prioritization: When seeking input on prioritizing features or functionalities, use single choice questions to present a list of options and ask participants to select the most important or desirable feature from the provided choices.
Demographic or background information: Single choice questions can be used to collect demographic data or gather information about participants' backgrounds, such as their age range, industry, likes/dislikes, habits, or level of experience. This helps in segmenting and analyzing survey responses based on specific user characteristics.
Preference testing: Use single choice questions to gather participants' preferences among different design options. For instance, present multiple variations of a design element (e.g. color schemes, layout options, or button styles) and ask participants to choose their preferred option.
4. Multiple-choice survey questions
Multiple choice questions allow participants to select more than one option, making them ideal for assessing preferences among various design features or elements. For example, you can present a list of adjectives and ask participants to choose all the options they find relevant.
Take your results and analysis beyond the confines of the Lyssna platform and share them with your stakeholders. This feature enables the flexibility to work with the data in external tools, such as spreadsheets or statistical software, facilitating more advanced and customized analysis where you can dive deeper into the data and generate visualizations.
How to export test results as a CSV
At the top of the test results, select the Export results as CSV button. Your CSV will automatically download.
Pro tip: If you want to use Excel to open the CSV export, set the 'File origin' to '65001: Unicode (UTF-8)' to ensure all characters appear correctly.
Sharing your results allows you to effectively communicate and collaborate with team members, stakeholders, and clients, fostering a deeper understanding and alignment around your findings.
How to share your results
Once you’ve received all the results, click on the Share button in Lyssna and grab the link. Just make sure the toggle is set to ‘Link active’.
Anybody you share the link with can access the results for that particular test – they don't need a Lyssna account.
The benefits of filtering results
Make the most of the filtering functionality when you’re next analyzing your data in Lyssna.
This feature empowers you to extract meaningful conclusions, make data-driven improvements, and optimize the user experience.
Whether you’re examining the results by demographics, analyzing individual participant responses, or exploring user behavior based on participant answers, the filtering capabilities in Lyssna provide a versatile and effective toolset for extracting actionable insights.
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