10 User Surveys Interview Questions and Answers for ux researchers

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If you're preparing for ux researcher interviews, see also our comprehensive interview questions and answers for the following ux researcher specializations:

1. What is your process for designing and conducting user surveys?

My process for designing and conducting user surveys is methodical and data-driven. Firstly, I always start with a clear research objective or hypothesis, which is refined through reviewing previous research, examining product metrics and reviewing industry reports. I then design my survey questions and answer options carefully, ensuring they are clear, unbiased, and will produce actionable data.

  1. Next, I conduct pilot testing with a small group of users to identify and address any issues that may arise while taking the survey, as well as to ensure that the questions gather the precise information I was looking for. During this phase, I usually pay close attention to the reaction time and completion rates for each individual question.
  2. Following the pilot testing, I send the survey to a sample of users that reflects our target user group. For example, if we are trying to understand how first-time users interact with our app, I will ensure that the sample is representative of this user persona.
  3. After analyzing the data from the user survey, I usually create a summary report with clear, concise insights that can be quickly and easily shared with my team. I also make it a point to map these insights to specific product and business objectives, to help inform and shape future development efforts.

A recent example of my process in action was a survey I designed and conducted last year for a mobile app client. The research objective was to understand the motivations and behaviors of users in relation to a new feature we had just launched. Following standard survey protocols and careful design, the data we received enabled us to identify pain points in the new feature's user experience, which our team quickly addressed with updated designs. Within one month, user engagement with the feature had increased by 40%, which directly contributed to a positive impact on the overall conversion rate of the app.

2. What are some of the challenges you’ve faced while conducting user surveys?

One of the biggest challenges I've faced while conducting user surveys is getting a representative sample of participants. For example, when conducting a survey for a healthcare app, I found it difficult to get enough responses from older adults, who are a key demographic for the app's use.

To address this challenge, I tried several tactics. First, I reached out to specialized communities and organizations that cater to older adults, such as senior centers and retirement communities, to get them involved in the survey. I also adjusted the survey language and format to make it more accessible and easier to understand for that audience. Additionally, I offered incentives, such as gift cards, to encourage participation.

Another challenge I faced was getting honest and insightful feedback from participants. While some respondents were candid about their experiences and opinions, others were not as forthcoming. To overcome this challenge, I employed a mix of open-ended and closed-ended questions in the survey. I also made sure to provide a safe and anonymous environment for participants to share their thoughts.

Overall, these tactics were successful in improving the quality and diversity of the survey results. For example, we saw a 20% increase in the number of responses from older adults, and a higher proportion of respondents provided detailed and honest feedback. This helped us to make more informed decisions about the app's development and better cater to our users' needs and preferences.

3. How do you decide on the sample size for your user surveys?

Before deciding on the sample size for my user surveys, I consider several factors:

  1. Purpose: What is the purpose of the survey? If the survey is meant to provide a general overview or to validate assumptions, a smaller sample size may suffice. If the survey is meant to provide detailed insights or support decision-making, a larger sample size may be necessary.
  2. Population size: What is the size of the population I am targeting? A larger population would require a larger sample size to ensure representativeness.
  3. Margin of error: What level of precision do I need? A smaller margin of error would require a larger sample size.
  4. Confidence level: What level of confidence do I need in my results? A higher confidence level would require a larger sample size.
  5. Budget and resources: How much budget and resources do I have available? Conducting larger surveys with larger sample sizes may require more time, money, and personnel resources.

Once I have considered these factors, I use a sample size calculator to determine the appropriate sample size. For example, if my target population is 10,000 with a margin of error of 5% and a 95% confidence level, the sample size calculator would recommend a sample size of 385 respondents.

However, I also ensure that the sample size is large enough to provide meaningful insights into any subgroups within the population. For example, if I am targeting a specific age group, gender, or geographic region, I would need to ensure that the sample size for that subgroup is large enough to draw meaningful conclusions.

Ultimately, the goal is to strike a balance between statistical accuracy and practicality to ensure that the survey results are reliable and actionable.

4. What are some best practices that you follow when designing survey questions?

When designing survey questions, I ensure that they are clear, concise, and specific. One best practice I follow is to avoid using jargon or technical language that may confuse participants. To gauge the effectiveness of my survey questions, I conduct pilot tests on small groups before distributing them widely.

  1. Clear and Concise Questions: The wording of survey questions should be simple, direct, and easily understood by all participants.
  2. Specific Questions: The questions should be specific enough to gather the intended information accurately.
  3. Scaling: Utilizing a balanced number scale, i.e., having an equal number of positively and negatively put questions, makes it simple for participants to answer and understand the questions.
  4. Pretesting: Once the survey questions are ready, testing them with a small participant and identifying problems or difficulties they might encounter may save your time and provide better results.
  5. Avoiding Biased Questions: Any questions with bias or attempting to lead participants towards a specific answer should be avoided.
  6. Consistency: Steps should be taken to guarantee uniformity in questions and response categories used in a survey. This makes it easy for the participant to complete the survey and ensures consistent responses from each participant.
  7. Open-Ended Questions: If you want to hear how participants feel truly, utilize open-ended questions. Carefully worded open-ended questions may offer significant insight into participants' opinions.
  8. Question Flow: Proper arrangement of questions leads to better results. Questions should be arranged such that they follow a logical flow that makes sense to the participant.
  9. Limiting Answer Choices: Offer clear, distinct answer possibilities that are easy to comprehend, such as a single-choice or multiple-choice question.
  10. Testing for Length: The survey's total length should not exceed more than 10 or 15 minutes, typically no more than 20 questions, or else the participant may get bored or uncomfortable.

5. How do you ensure that your survey questions are unbiased and don’t lead users to a particular answer?

As a researcher, the last thing I want is to lead users to a particular answer. That is why I follow the following steps to ensure all my survey questions are unbiased:

  1. I always start by defining the research problem and objectives. This helps me create questions that are impartial and do not steer the user to a particular conclusion.
  2. I often use open-ended questions that allow users to express their thoughts in their words. This way, users are not constrained by pre-defined responses, and I avoid any bias inherent in closed-ended questions.
  3. I also avoid leading questions that suggest a particular answer. For example, instead of asking, "How much do you love our product?" I would ask, "What are some of the things you like about our product?"
  4. Before the survey goes live, I conduct pilot testing and gather feedback on the wording and order of the questions. This enables me to refine the questions to eliminate any unintentional bias.
  5. Finally, I use statistical tests to identify and remove any biased responses. For example, if I see that a particular demographic is more likely to respond positively to a question, I would investigate and see if there is anything in the question or sample design that is leading to that result.

By following these steps, I have been able to ensure all my survey questions are unbiased, and I can rely on the results to drive data-driven decision-making. For instance, in a recent survey conducted to determine customer satisfaction, these strategies ensured that the results were independent, and it was discovered that customer satisfaction index rose from 60% in 2022 to 85% in 2023.

6. What are some of the most common mistakes companies make when conducting user surveys?

After analyzing survey data from over 1,000 companies, we have found that some of the most common mistakes companies make when conducting user surveys are:

  1. Asking leading questions that bias the respondent's answers. For example, asking "Don't you think this product is great?" instead of "What are your thoughts on this product?" This can result in inaccurate data that does not truly represent the user's opinion. In a survey we conducted, 43% of participants reported encountering leading questions in user surveys.

  2. Survey fatigue - sending too many surveys to the same group of users, which results in low response rates and the risk of disengaging users from participating in future surveys. Our research showed that 62% of respondents stated that they receive too many surveys from the same company, leading to a high likelihood of disinterest and errors in their answering.

  3. Complicated surveys - creating long surveys with complex questions that confuse participants and result in incomplete or inaccurate data. In one survey we researched, 73% of participants reported that they found the survey too long and lost focus or interest towards the end.

  4. Unrepresentative samples - conducting surveys with participants that are not representative of the user base, resulting in skewed data. For example, only surveying customers who have purchased a particular product, whereas there are customers who are yet to purchase the product, producing data that is not completely reliable. In a recent study, 28% of surveyed users stated that they believe companies do not survey a diverse enough set of customers.

  5. Ignoring feedback - collecting survey feedback but failing to act on it or respond to users, which can lead to discouragement and a lack of trust in the company. In one study we conducted, 67% of participants reported feeling frustrated when their feedback was ignored, leading to overall dissatisfaction with the company.

By avoiding these common survey mistakes, companies can maximize the accuracy and effectiveness of their surveys and better understand their users.

7. How do you analyze and interpret the data collected from user surveys?

When analyzing and interpreting the data collected from user surveys, I follow a structured approach. First, I clean the data to eliminate any errors or inconsistencies. After that, I segment the data based on different criteria such as demographics, user behavior or location.

  1. Quantitative data:
  2. For quantitative data, like satisfaction rating on a scale of 1-10, I use statistical analysis to calculate the mean, standard deviation and range to get a better understanding of the distribution of data. For instance, in a user survey I conducted for a food delivery app company, I analyzed the data to find that 70% of the users rated their satisfaction level as between 8-10 out of 10. Based on that result, the company decided to focus on improving the delivery times for the remaining 30% of users to improve their satisfaction.

  3. Qualitative data:
  4. For qualitative data, like open-ended survey questions, I use thematic analysis to identify recurring themes in the responses. In a survey for a fashion e-commerce site, users commented about the expensive prices of products. By analyzing the clients'answers, I noticed a recurring request for more special deals or discounts.

This structured approach helps me understand the voice of the user, and gain insights into the users' needs, desires, and pain points. These insights can then be used to inform product design decisions and improve the overall user experience.

8. What are some of the key metrics you typically include in survey results?

When analyzing survey results, I typically include a range of key metrics to gain insight into user behavior and preferences. Some of the metrics I commonly use include:

  1. Net Promoter Score: This measures customer loyalty and satisfaction. In our latest user survey, we found that our NPS had improved from 70 to 80 over the past year.
  2. Customer Effort Score: This measures how easy or difficult it is for users to accomplish their goals. Our CES improved by 20% since our last survey.
  3. Conversion Rate: This tracks the percentage of users who complete a desired action, such as signing up for a free trial. Our conversion rate increased by 15% after implementing a more intuitive user interface.
  4. Churn Rate: This measures the rate at which users cancel or unsubscribe from a service. Our churn rate decreased by 10% after improving our customer support capabilities.
  5. Customer Lifetime Value: This measures the total value a customer brings to a company over the course of their relationship. Our CLV increased by 25% due to higher retention and upsell rates.

By analyzing these metrics in detail, we can better understand user needs and preferences, and make data-driven decisions about product strategy and improvements.

9. How do you communicate survey findings to stakeholders in a way that is impactful and actionable?

In my previous role, I was responsible for conducting user surveys for a SaaS platform. Our surveys generated a wealth of valuable data that we presented to stakeholders in a way that was impactful and actionable. Here are a few strategies that we used:

  1. First and foremost, we made sure that our reports were visually appealing and easy to understand. We presented our findings using charts, graphs, and other visual aids that made it easy for stakeholders to see and interpret the data;
  2. We focused on the most important findings first. At the beginning of each report, we included a summary of the key takeaways to ensure that our stakeholders would know what the most important findings were before diving into the details;
  3. We provided concrete examples to illustrate our findings. For example, we might include quotes from survey respondents or screenshots of user behavior that backed up the data;
  4. We made sure that our reports included actionable insights. For instance, if we discovered that users were struggling to find a certain feature, we would provide recommendations for how to improve the user experience;
  5. We tailored our reports to the audience. Depending on who we were presenting to, we might highlight different findings or emphasize different aspects of the data.

These strategies helped us to effectively communicate our survey findings to stakeholders in a way that drove action and improvement. As a result, we saw a 20% increase in user satisfaction and a 15% decrease in customer churn.

10. What new methodologies or technologies have you explored recently to help improve the quality and efficiency of user surveys?

I have recently explored the use of AI-powered chatbots to improve the quality and efficiency of user surveys. Specifically, I used a chatbot platform to administer surveys to a sample group of users. The chatbot collected and analyzed user responses in real-time, allowing for quick adjustments to the survey questions to improve user engagement and comprehension.

The results of this approach were impressive. The response rate increased by 20% as users found the chatbot interface more engaging and user-friendly. Additionally, the time it took to conduct the survey decreased by 30%, as responses were captured and analyzed instantaneously, reducing the need for manual data entry and analysis.

  1. Explored the use of AI-powered chatbots
  2. Administered user surveys to a sample group of users
  3. Collected and analyzed user responses in real-time
  4. Quick adjustments made to improve user engagement and comprehension
  5. Increased response rate by 20%
  6. Reduced time to conduct survey by 30%

Conclusion

Completing user surveys is an essential part of being a UX researcher, and these questions and answers will help you to be better prepared for interviews. But, finding a job involves more than just interviews. You will need to write an intriguing cover letter that makes you stand out from other applicants. Take a look at our guide on writing a cover letter for UX researchers, which will help you to get started. And don't forget to prepare an impressive CV before you start applying for jobs. Our guide on writing a resume as a UX researcher can be found here. Finally, if you're searching for remote UX researcher jobs, Remote Rocketship is the perfect place to start. Check out our job board, which is filled with exciting opportunities for you to explore.

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