Technical Questions Flashcards
Describe p-value
The p-value is a statistical measure that helps determine the significance of the findings or observed effects in a study. It quantifies the probability of obtaining the observed data or more extreme results if the null hypothesis is true.
In the context of UX research, the p-value can be used to evaluate the statistical significance of various metrics or outcomes related to user experience. For example, it can help determine if there is a significant difference in task completion time, user satisfaction scores, or click-through rates between different design variations or conditions.
When interpreting the p-value in UX research, keep the following in mind:
Null Hypothesis (H0): The null hypothesis represents the assumption that there is no significant difference or effect between the compared groups or conditions in the study. It assumes that any observed differences are due to chance or random variation.
Alternative Hypothesis (H1): The alternative hypothesis states that there is a significant difference or effect between the compared groups or conditions in the study.
Significance Level (α): The significance level, typically denoted as α, is the predetermined threshold set by the researcher to determine the level of evidence needed to reject the null hypothesis. Commonly used values for α are 0.05 (5%) or 0.01 (1%).
Interpreting the p-value: If the p-value obtained from statistical tests is less than the chosen significance level (α), it suggests that the observed differences or effects are unlikely to have occurred by chance alone. In this case, the null hypothesis is rejected, and the alternative hypothesis is supported. If the p-value is greater than the significance level, it indicates that the observed differences or effects could plausibly be due to random chance, and the null hypothesis cannot be rejected.
It’s important to note that a p-value alone does not indicate the magnitude or practical significance of the observed differences or effects. Therefore, as a UX researcher, it’s crucial to consider the practical implications and the effect size (e.g., Cohen’s d, eta-squared) when interpreting the findings and making informed decisions.
Suppose that you are using eye tracking on a cross-eyed participant and the calibration cannot be successful. What do you do?
Adjust the setup: Ensure that the eye tracking equipment is properly positioned and adjusted for the participant’s unique eye characteristics. This may involve modifying the distance, angle, or height of the eye tracking device or adjusting the participant’s position to optimize calibration conditions.
Explore alternative calibration methods: Some eye tracking systems offer alternative calibration methods that can accommodate individuals with certain eye conditions. These methods may include manual calibration, where the participant fixes their gaze on specific points or performs specific eye movements guided by instructions. Consult the eye tracking system’s documentation or contact technical support to explore any available options.
Consider supplementary data collection: If achieving accurate eye tracking data proves challenging, consider utilizing additional data collection methods to gather insights about the participant’s experience. This can include conducting interviews or observation-based research to capture qualitative feedback and behavioral patterns that may provide valuable insights even without precise eye tracking measurements.
Adapt the research approach: Depending on the specific objectives of your study, you may need to adjust your research approach to accommodate the participant’s unique eye condition. This could involve focusing on other aspects of the user experience, such as task performance, subjective feedback, or other physiological measurements like facial expressions or mouse tracking.
Document the limitations: It’s crucial to transparently document any challenges or limitations encountered during the eye tracking process with the cross-eyed participant. This will help ensure the validity and reliability of your research findings and allow for appropriate interpretation and consideration of potential biases.
How would you conduct user interviews if you were trying test a particular interaction?
Define your objectives: Clearly articulate the goals and objectives of the user interviews. Determine the specific interaction you want to test and what aspects you aim to evaluate or improve.
Recruit participants: Identify and recruit participants who represent your target user base or have the relevant experience with the interaction you want to test. Aim for a diverse sample to capture a range of perspectives. Consider the number of participants based on the resources and time available for conducting interviews (typically 5-8 participants can provide meaningful insights).
Prepare an interview guide: Develop an interview guide that includes a structured set of questions and prompts specifically focused on the interaction you want to test. Start with broad questions to establish context and then progress to more specific inquiries about the interaction itself, usability, challenges, and suggestions for improvement.
Set up the interview session: Schedule interview sessions with each participant at a convenient time. Choose a quiet and comfortable location where the participant feels at ease. Ensure you have the necessary recording equipment, consent forms if required, and any prototypes or materials relevant to the interaction being tested.
Build rapport and introduce the session: Begin the interview by building rapport with the participant, explaining the purpose of the interview, and ensuring they understand their role. Emphasize that there are no right or wrong answers, and their honest feedback is crucial for improving the interaction.
Explore participant experiences: Encourage participants to share their experiences and thoughts related to the specific interaction you are testing. Ask open-ended questions to uncover their perceptions, attitudes, and behaviors. Prompt them to provide specific examples or scenarios where they have encountered the interaction.
Observe and probe: Actively listen to participants’ responses and take notes. Pay attention to both verbal and non-verbal cues. Seek clarification or ask probing questions to dig deeper into their thought processes, motivations, and any challenges they may have encountered during the interaction.
Test scenarios and gather feedback: If possible, present participants with realistic scenarios or tasks that involve the interaction you are testing. Observe how they approach the tasks and gather their feedback on the usability, clarity, and effectiveness of the interaction. Encourage participants to think aloud during the process to capture their decision-making and problem-solving.
Wrap up the interview: Conclude the interview by giving participants the opportunity to provide any additional feedback or raise any concerns not covered in the previous questions. Thank them for their participation and assure them that their insights will be used to improve the interaction.
Analyze and synthesize data: Review and analyze the interview data, looking for patterns, recurring themes, and key insights. Synthesize the findings to identify common pain points, areas of success, and opportunities for improvement related to the tested interaction.
**Imagine you have 3 different UIs and you want to know which one is best. What would you do?
Define the research objectives: Clearly articulate the goals and criteria for evaluating the UIs. This could include factors such as usability, efficiency, learnability, satisfaction, and overall user experience.
Recruit participants: Identify and recruit a diverse group of participants who represent the target user base or have similar characteristics. Aim for a sample size that provides enough data to draw meaningful conclusions.
Develop test scenarios: Create realistic and relevant tasks or scenarios that participants will perform using each of the UIs. These tasks should cover key features and interactions.
Conduct usability testing: Ask participants to interact with each UI while observing and taking notes on their behaviors, challenges, and feedback. Encourage participants to think aloud to capture their thought processes.
Collect quantitative data: Consider incorporating quantitative measures such as task completion time, error rates, and user satisfaction surveys (e.g., System Usability Scale - SUS) to provide measurable metrics for comparison.
Gather qualitative data: Conduct interviews or surveys to obtain participants’ subjective feedback, opinions, and preferences about each UI. Probe deeper to understand their thoughts on specific aspects like layout, navigation, visual design, and overall usability.
Analyze the data: Review and analyze both quantitative and qualitative data collected during the research study. Look for patterns, common themes, and key insights related to the strengths and weaknesses of each UI.
Compare and evaluate: Compare the findings across the different UIs, considering the research objectives and user feedback. Identify patterns or trends that indicate which UI performed better in terms of user experience and satisfaction.
Make recommendations: Based on the research findings, provide actionable recommendations for improving or refining the UIs. These recommendations should address the identified weaknesses and build on the strengths of the preferred UI.
Iterate and validate: If time and resources permit, consider incorporating the recommendations and conducting further testing or validation to ensure the improvements are effective.
Imagine that a team of engineers want to know why certain users aren’t engaging with a particular push feature. They plan to conduct a survey with six yes/no questions and one question that can be answered via [a] text box. What would you tell them about their plan?
If you had two products and had to ask one question of users to determine which they preferred more, what would you ask?
“Which product better meets your needs and provides a more satisfying user experience?”
This question allows users to express their overall preference based on their needs, expectations, and the experience they have had with both products. It provides an opportunity for participants to weigh different factors, such as usability, features, aesthetics, ease of use, and any other aspects relevant to their specific context.
Additionally, it is essential to encourage participants to elaborate on their response and provide specific reasons for their preference. This will help uncover valuable insights about the specific strengths and weaknesses of each product from a user perspective.
While this single question captures users’ preference, it is also important to consider other research methods and gather additional data points to gain a more comprehensive understanding of user preferences and the factors that drive them. Combining this question with usability testing, user feedback, and behavioral analytics can provide a more robust foundation for making informed design decisions.
What are the weaknesses of personas? How do you overcome those weaknesses?
Generalizations and stereotypes: Personas may be based on assumptions and generalizations about user groups, leading to stereotyping and overlooking individual differences. To overcome this weakness, conduct thorough user research to ensure personas are based on real user data and behaviors. Use qualitative and quantitative research methods to gather insights and validate assumptions.
Lack of real-time updates: Personas can become outdated over time as user behaviors and needs evolve. To address this weakness, regularly review and update personas based on ongoing user research and feedback. Continuously collect and incorporate new data to ensure personas remain accurate and representative.
Limited representation: Personas may not capture the full diversity of users, potentially excluding important user segments. To overcome this weakness, actively seek diverse participants during the research process and create personas that represent different user characteristics, including demographics, goals, attitudes, and behaviors. Consider intersectionality and ensure that personas reflect a wide range of user perspectives.
Emotional and motivational aspects: Personas often focus on demographic and behavioral data, but may not capture emotional or motivational aspects that drive user decision-making. To address this weakness, incorporate qualitative research methods like interviews or observation to gain deeper insights into users’ emotions, motivations, and underlying needs. Supplement personas with user stories or empathy maps to capture the emotional aspects of the user experience.
Limited context and dynamic interactions: Personas may not fully capture the context in which users interact with a product or service. They might overlook the dynamic nature of user interactions, such as different devices, environments, or scenarios. To overcome this weakness, consider incorporating contextual information into personas, such as the user’s physical environment, time constraints, or social influences. Conduct usability testing or field studies to observe and understand users’ interactions in real-world contexts.
Potential for bias and assumptions: Personas can be influenced by the biases and assumptions of the research team, leading to skewed representations. To mitigate this weakness, involve a diverse team in the persona creation process to bring multiple perspectives and challenge assumptions. Validate and refine personas through user feedback and ensure that they accurately reflect the actual user base.
By acknowledging these weaknesses and employing strategies to address them, personas can be strengthened and become more reliable and actionable tools for understanding users and informing design decisions. Regular updates, inclusive research methods, and an ongoing commitment to user-centered approaches can help overcome the limitations and enhance the effectiveness of personas in UX research and design.
Think about an app you like to use. Suppose the product manager tells you that he wants you to find the top 10 UX issues. How would you go about this?
Define the scope and objectives: Start by clearly defining the scope of the evaluation. Determine which specific areas or features of the app you will focus on. Align with the product manager to understand their goals and expectations for the evaluation.
User feedback analysis: Gather existing user feedback from various sources, such as app store reviews, customer support tickets, and user feedback channels. Analyze this feedback to identify recurring themes, pain points, and areas of dissatisfaction expressed by users. Pay attention to both positive and negative feedback to understand what is working well and what needs improvement.
User journey mapping: Map out the typical user journey within the app, identifying key touchpoints and interactions. Visualize the user flow to understand the overall user experience. Identify any steps or transitions that users may find confusing, frustrating, or time-consuming.
Usability testing: Conduct usability testing sessions with representative users who are the target audience for the app. Create specific tasks that cover the key features or interactions you want to evaluate. Observe and collect feedback on usability issues, navigation challenges, clarity of information, and any other factors impacting the user experience. Note common problems and areas where users struggle or express frustration.
Heuristic evaluation: Perform a heuristic evaluation of the app’s interface and user interactions based on established UX principles and best practices. Evaluate the app against a set of usability heuristics (e.g., Nielsen’s heuristics) and identify any violations or areas where the app could be enhanced.
Analytics and quantitative data analysis: Utilize app analytics and quantitative data to gain insights into user behavior and identify patterns. Analyze metrics such as user flow, click-through rates, drop-off points, and conversion rates. Look for areas where users exhibit high abandonment or encounter obstacles in accomplishing tasks.
Collaborative brainstorming: Organize brainstorming sessions involving UX designers, developers, and other stakeholders. Encourage participants to share their observations, insights, and ideas for improving the app’s user experience. Capture the identified issues and prioritize them based on their impact on the user experience.
Create a ranked list: Consolidate the findings from the different evaluation methods and create a ranked list of the top 10 UX issues. Prioritize the issues based on their severity, frequency, and impact on user satisfaction, business goals, and the overall user experience.
Present findings and recommendations: Prepare a comprehensive report or presentation that outlines the identified UX issues, their impact, and potential solutions or recommendations. Clearly communicate the user insights, supporting evidence, and suggested improvements to the product manager and relevant stakeholders.
Suppose you come forward with a usability recommendation, and the engineers counter that with, “All the usage data we have from millions of people suggest that is not a problem.” How would you respond?
Design a study for an in-vehicle phone keypad
**How would you determine a metric for engagement?
Define the concept of engagement: Start by clearly defining what engagement means in the context of your product or service. Engagement can vary depending on the nature of the application, such as social media, e-commerce, or productivity tools. Identify the key behaviors or interactions that reflect active usage, involvement, or meaningful participation by users.
Identify relevant user actions: Identify the user actions or behaviors that align with the concept of engagement you defined. These actions should be measurable and indicative of users’ active involvement with the product. For example, it could be the number of logins, content creation, interactions with specific features, time spent on the app, or social interactions.
Set goals and objectives: Determine the goals and objectives related to engagement. Consider the desired outcomes and the business or product objectives you want to achieve. Align the engagement metric with these goals to ensure it reflects the desired user behavior and contributes to the overall success of the product.
Quantify the metric: Determine how you will quantify the engagement metric. It could be a simple count or frequency of the identified user actions, a cumulative measure over a specific period (e.g., weekly or monthly), or a ratio or percentage based on relevant user activities. Choose a metric that is meaningful, easy to track, and aligns with the context and goals of your product.
Validate the metric: Assess the validity and reliability of the chosen engagement metric. Ensure it accurately reflects user involvement and aligns with user perceptions of engagement. Conduct user research, gather feedback, and validate the metric against other key performance indicators (KPIs) or user satisfaction measures to ensure it provides meaningful insights into user engagement.
Continuously refine and iterate: As you collect data and observe user behavior, continuously refine and iterate on the engagement metric. Monitor its effectiveness in capturing user engagement and consider adjusting or adding additional metrics if necessary. Analyze trends, conduct A/B testing, and gather qualitative insights to refine and optimize the engagement metric over time.
Remember that engagement can be multifaceted, and no single metric can fully capture it. It’s often valuable to consider a combination of quantitative and qualitative measures to gain a comprehensive understanding of user engagement. Regularly review and reassess the engagement metric to ensure it remains relevant and aligned with evolving user needs and product objectives
**Define metrics for measuring fun and satisfaction for a mobile maps product
User ratings: Track user ratings and reviews on app stores or review platforms. Look for specific mentions of fun and satisfaction in user feedback to gauge overall sentiment.
Net Promoter Score (NPS): Conduct periodic NPS surveys to measure overall user satisfaction and likelihood to recommend the mobile maps product to others. NPS provides a high-level indicator of user satisfaction and loyalty.
User satisfaction surveys: Design and administer user satisfaction surveys with targeted questions related to fun and satisfaction. Include Likert scale or rating-based questions to quantify users’ subjective experiences.
Fun factor rating: Include a specific question in surveys asking users to rate the fun factor of using the mobile maps product. Provide a rating scale or options to measure the level of fun experienced by users.
Time spent in-app: Analyze the average time users spend within the mobile maps app. Higher engagement and longer sessions can indicate that users find the app enjoyable and engaging.
User engagement metrics: Track user engagement metrics such as the number of interactions, searches performed, routes planned, or saved locations. Higher engagement levels suggest users find the app useful and enjoyable.
Gamification metrics: If the mobile maps product incorporates gamification elements, track metrics specific to those elements. This could include achievements, badges earned, levels completed, or competition with other users.
User feedback and sentiment analysis: Conduct sentiment analysis of user feedback and reviews using natural language processing techniques. Identify positive sentiment keywords related to fun, enjoyment, and satisfaction.
Qualitative user research: Conduct in-depth interviews or focus groups with users to explore their experiences and perceptions of fun and satisfaction. Use open-ended questions to elicit detailed insights into what aspects of the mobile maps product contribute to their enjoyment and satisfaction.
User retention and churn rate: Monitor user retention rates and the rate of churn (users who stop using the app). Higher retention rates indicate that users are finding value, enjoyment, and satisfaction in the mobile maps product.
Remember to interpret these metrics in conjunction with other performance indicators and user feedback to gain a holistic understanding of fun and satisfaction. It’s important to regularly analyze and review these metrics, identify areas for improvement, and make iterative enhancements to enhance user enjoyment and overall satisfaction with the mobile maps product.
What’s the difference between a Persona and a Market Segment?
Persona:
Definition: A persona is a fictional representation of an ideal user or customer based on research and data.
Focus: Personas are primarily focused on understanding individual users at a detailed level, often with a specific name, background, goals, behaviors, and characteristics.
Purpose: Personas help humanize and personalize user research by creating archetypal individuals to represent different user groups. They provide a deeper understanding of users’ needs, preferences, motivations, and pain points.
Usage: Personas are widely used in user-centered design and product development processes to inform decision-making, guide design choices, and ensure user-centric solutions.
Granularity: Personas typically delve into the specifics of an individual user, highlighting their unique traits and experiences.
Example: A persona could be “Sarah,” a 30-year-old working professional who travels frequently, values convenience and efficiency, and uses mobile apps for trip planning and navigation.
Market Segment:
Definition: A market segment is a group of individuals or organizations with similar characteristics, needs, or buying behaviors within a larger market.
Focus: Market segments are broader in scope and focus on aggregating and categorizing individuals or organizations based on shared attributes, such as demographics, psychographics, behaviors, or preferences.
Purpose: Market segments help businesses identify and target specific groups of customers who are likely to respond similarly to marketing efforts or have similar needs and preferences.
Usage: Market segments are commonly used in market research, marketing strategy, and customer segmentation to tailor marketing messages, product offerings, and communication channels to specific target groups.
Granularity: Market segments consider groups of users at a higher level, categorizing them based on shared characteristics rather than diving into individual details.
Example: A market segment could be “Frequent Travelers,” which includes individuals who travel frequently for business or leisure, have higher income levels, value convenience and seamless experiences, and are more likely to adopt technology-driven solutions.
In summary, personas focus on understanding individual users in depth to inform design and development, while market segments group users together based on shared characteristics to guide marketing strategies and targeting efforts. Personas provide more detailed and personalized insights, whereas market segments provide a broader view of user groups for marketing purposes.
How do you know if you are asking the right research questions for a project?
Alignment with project goals: Ensure that your research questions are directly aligned with the goals and objectives of the project. Clearly understand the problem you are trying to solve or the insights you need to gather, and frame your questions to address those specific objectives.
User-centric perspective: Formulate research questions from a user-centric perspective. Focus on understanding user needs, behaviors, motivations, and pain points. Ensure that your questions are relevant to the target audience and will provide insights that inform the design and development process.
Open-ended and exploratory: Craft questions that encourage open-ended and exploratory responses. Avoid leading or biased questions that may influence participants’ answers. Allow participants to share their experiences, thoughts, and opinions freely, enabling you to gain deep insights and uncover unexpected findings.
Clear and concise: Ensure that your research questions are clear, concise, and easy to understand. Use simple and straightforward language to avoid confusion or misinterpretation. If necessary, provide context or clarification to help participants better understand the question.
Research method suitability: Consider the research methods you plan to use and ensure that your questions are appropriate for those methods. Different research methods, such as interviews, surveys, usability testing, or observational studies, may require different types of questions to gather the desired insights effectively.
Avoid assumptions: Be mindful of your own biases and assumptions when formulating research questions. Take an objective and neutral stance to gather unbiased insights. Avoid leading questions that may unintentionally guide participants towards certain responses.
Iterative approach: Recognize that research questions may evolve and refine throughout the research process. Embrace an iterative approach, where you continuously review and refine your research questions based on initial findings, user feedback, and emerging insights. Remain flexible and open to adjusting your approach as you learn more during the research process.
Peer review and collaboration: Seek feedback from peers, colleagues, or stakeholders on your research questions. Collaborate with other team members to validate the relevance and clarity of the questions. Engaging in discussions and getting input from others can help ensure that you are asking the right research questions.
By considering these factors, you can increase the likelihood of asking the right research questions that yield valuable insights and contribute to the success of your project. Regularly review and refine your questions as you progress through the research process, remaining adaptable to the evolving needs and objectives of your project.
How do you know when a project is “done”?
