登录查看更多内容

How do you align your prototyping and testing goals with your research questions and hypotheses?

由人工智能和领英社区提供技术支持

Prototyping and testing are essential steps in UX research, but they can also be challenging and time-consuming. How do you make sure that your prototypes and tests are aligned with your research questions and hypotheses? In this article, we will explore some tips and best practices to help you plan and execute effective prototyping and testing sessions.

在这篇协作文章中查找专家回答

由社区从 2 条内容中精选。了解更多

1 Define your research goals

Before you start prototyping and testing, you need to have a clear idea of what you want to learn from your users. What are the main questions or problems that you are trying to solve? What are the assumptions or hypotheses that you want to validate or invalidate? How will you measure the success or failure of your prototypes and tests? Having well-defined research goals will help you focus your efforts and avoid wasting time and resources on irrelevant or unnecessary features.

添加您的观点

Skot Carruth

is working on something new
举报内容
At Philosophie Group, we ensured that our prototypes aligned with research questions by cross-referencing the research hypothesis with the relevant interface or flow. It takes discipline, but it's actually very simple and introduces intellectual rigor to design decisions. Try this: ? keep your research hypotheses in a spreadsheet and link them to specific screens or flows in your prototype ? use comments in your design files to reference which ideas relate to an untested hypothesis ? always contextualize presentations by clarifying which aspects of the design are validated and which are testing a hypothesis

已翻译

赞

2 Choose the right level of fidelity

Prototyping and testing can be done at different levels of fidelity, from low-fidelity sketches or wireframes to high-fidelity mockups or interactive prototypes. The level of fidelity that you choose depends on your research goals, your available resources, and your user expectations. Generally, low-fidelity prototypes are faster and cheaper to create and test, but they may not capture all the details or interactions that you want to evaluate. High-fidelity prototypes are more realistic and engaging, but they may also be more costly and complex to build and test. The key is to find the right balance between fidelity and feasibility, and to match the level of fidelity to the stage of your research process.

添加您的观点

Skot Carruth

is working on something new
(已编辑)
举报内容
When thinking about fidelity, consider these different dimensions depending on what you want to learn: ? *Content fidelity,* or how realistic the copy and images are. Critical for testing comprehension and value. ? *Interaction fidelity,* or how realistic the flow of the app is. Critical when you're testing for usability. Too often designers create polished prototypes that only have a "happy path"! ? *Visual fidelity,* or how detailed the UI design is. Important when you're testing for accessibility or brand perception. No matter what you're testing, consider adopting "minimum responsible fidelity" as a goal for your prototype. With this mindset, designers can help lead their product teams to faster learning.

已翻译

赞

3 Plan your testing scenarios and tasks

Once you have your prototypes ready, you need to plan how you will test them with your users. Testing scenarios and tasks are the scripts or instructions that you give to your users to guide them through the prototype and elicit feedback. They should be realistic, relevant, and specific, and they should align with your research goals and hypotheses. For example, if you want to test the usability of a checkout process, you may ask your users to complete a purchase with a given product and payment method, and observe how they navigate the prototype, what difficulties they encounter, and what suggestions they have.

添加您的观点

4 Collect and analyze your data

The final step of prototyping and testing is to collect and analyze the data that you get from your users. Depending on the type and level of fidelity of your prototypes and tests, you may collect different kinds of data, such as qualitative data (e.g., user feedback, comments, reactions, preferences) or quantitative data (e.g., completion rates, error rates, time spent, clicks, conversions). You may also use different methods or tools to collect and analyze your data, such as surveys, interviews, observations, analytics, or heatmaps. The goal is to extract meaningful insights and actionable recommendations from your data, and to compare them with your research questions and hypotheses.

Prototyping and testing are not isolated activities, but rather iterative and collaborative processes that involve constant learning and improvement. By aligning your prototyping and testing goals with your research questions and hypotheses, you can ensure that you are building and testing the right solutions for the right problems, and that you are delivering the best possible user experience.

添加您的观点

User Research

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

How do you align your prototyping and testing goals with your research questions and hypotheses?

1

2

3

4

1 Define your research goals

2 Choose the right level of fidelity

3 Plan your testing scenarios and tasks

4 Collect and analyze your data

User Research

给文章评分

感谢您的反馈

更多User Research相关文章

更多相关阅读内容

How do you align your prototyping and testing goals with your research questions and hypotheses?

1

2

3

4

1 Define your research goals

2 Choose the right level of fidelity

3 Plan your testing scenarios and tasks

4 Collect and analyze your data

User Research

给文章评分

感谢您的反馈

查看其他技能