Surveys are the easiest and most cost-effective way to gather data from a large group of people. However, you need to follow strict guidelines and carefully analyze the survey data to make valid conclusions.

One of the most effective ways to improve the quality and efficiency of surveys is to use survey paradata and process data. Process and para data are survey-related data, such as completion time, the number of attempts to reach respondents, and the types of questions they skip.

Let’s explore why paradata and processing data are important and how to use them to improve your survey design.

Understanding Survey Paradata

Survey paradata is any data you collect about the survey process itself. You can collect it from different sources, including the survey respondent, the interviewer, and the survey platform.

The main goal of collecting paradata is to improve the quality and accuracy of the survey. Paradata gives you insight into who participants are and how they interpret questions.

Types of Paradata Collected During Survey

• Timestamps: The date and time of each stage of the survey (e.g. when the survey began, when each question was answered, and when it was completed)
• Response times: The time it took respondents to answer specific questions.
• Device information:  device type, operating system, browser, etc.
• Interviewer notes: interviewer’s notes on the respondent’s behavior, types of questions asked, and respondent’s responses.

Potential Insights from Analyzing Paradata

• Survey response rates: You can use paradata to identify reasons for low response rates, such as the time of day the survey is sent, survey duration, and survey invitation type (text, email, in-app, etc).
• Survey accuracy: Paradata enables you to identify factors that are associated with measurement error, such as the respondent’s level of attention and question difficulty.
• Survey bias: You can also use paradata to pinpoint reasons for survey bias such as respondent demographic and survey delivery method.

For You: How To Correct Biased Survey Results

Process Data in Surveys

Process data allows you to identify and fix potential sources of error or bias in the survey design or administration. It collects information about how the respondents interacted with the survey.

Types of Survey Process Data

• Interviewer notes: These are interviewers’ observations during the survey, such as respondent mood, attitude, understanding, cooperation, or interruptions during the interview.
• Survey progress indicators: This documents respondent progress through the survey. For example, the time spent on each question, the number of response modifications, the number of breaks or pauses taken, and the completion status of the survey.
• Survey abandonment data: This documents why participants stopped taking the survey – was it because it was too short, the questions were too long, or it was just too hard?

Importance of Paradata and Process Data

• Improved Survey Design and Administration

Paradata allows you to track and evaluate survey processes, uncover biases, and improve survey design and administration. For example, if you see that many respondents drop off the survey after one question, you can change the question or move it to another part of the survey for a better completion rate.

• Increased Data Quality

Process data helps you to identify and fix potential data quality problems, which increases your measurement validity and reliability. For example, if you find that a lot of respondents are answering questions inconsistently, you can revise the questions or provide more detailed instructions.

• Enhanced Insights

You can also use process data to gain insights into how respondents interpret the questions and respond to the survey. This helps you to improve the survey design, invitation type, and sample demographics.

Analyzing and Utilizing Paradata and Process Data

Methods and Techniques for Analyzing Paradata and Process Data

• Descriptive Statistics: Summarizing survey data using responses’ mean, median, or standard deviation.
• Inferential Statistics: This tests a hypothesis about your data. For example, if you think different income levels answer the same question differently, you can use simply compare the average response varies between two groups of people.
• Data Analytics:  Identify patterns and trends in the data to understand the relationship between respondents and their responses.

Detecting Nonresponse, Break-Off, and Response Patterns With Paradata

You can use paradata to identify respondent progress through the survey- did they start the survey, started but didn’t finish, or completed the survey? This information allows you to identify areas for improvement in the survey design and reduces survey break-off rates.

Enhancing Survey Data Quality and Validity with Process Data

You can also use process data to find anomalies in the survey such as inconsistent or missing responses. This allows you to improve data quality by tracking respondents to find missing data, investigate discrepancies, and eliminate outliers.

Ethical Considerations and Data Privacy

• Informed consent

Ensure respondents know what they’re consenting to, how their data will be collected, and what the benefits and risks are. This ensures you respect their privacy and dignity.

Also, give participants the option to opt out or withdraw their consent at any time.

• Confidentiality and Anonymity

Ensure you encrypt, anonymize, or aggregate the data to prevent unauthorized access or publication.

Paradata and process data may contain sensitive information, such as personal health information or financial information. This information could be used to identify, track, or discriminate against respondents.

• Data Security

Paradata or process data is often stored in an electronic format, making it susceptible to unauthorized access, use, or disclosure. Ensure respondent data are encrypted and comply with local data protection laws and privacy regulations.

Related: What are Ethical Practices in Market Research?

Best Practices for Handling and Storing Process and Paradata

• Be transparent about your data collection practices– Let respondents know what data you are collecting, how you will use the data, and how you will protect their privacy.
• Allow opt-out of data collection– Respondents should have the right to choose whether or not to participate in a survey. They should also be able to withdraw their consent at any point during the survey.
• Use data responsibly– You should only collect and use the data for legitimate purposes that are consistent with your research objectives and ethical principles. Do not sell or share data with third parties without the consent of respondents.

Future Directions and Advances

Improving Survey Research With Process and Paradata

Processes and paradata can help you figure out which people are likely to leave a survey and how to get them to stay. For example, you can introduce extra incentives for completing the survey.

Process data also helps you identify questions that are difficult for respondents to answer and provide additional instructions or clarification. You can also use it to identify respondents who are providing inconsistent or inaccurate information and follow up with them to obtain accurate data.

New Methods for Collecting and Analyzing Process and Paradata

As technology improves, so do the ways we collect, analyze, and process data. For example, machine learning techniques can help to identify patterns and trends faster in large datasets.

Emerging Technologies and Methods

• Web analytics– This provides you with rich paradata on respondents’ behavior and interaction with the survey, such as mouse movements, response times, scrolling patterns, etc. This data can help you identify problems with the survey design or administration.
• Natural language processing– With the help of natural language processing (NLP), you can analyze open-ended survey responses, eliminating the need for a manual review of the survey questions.
• Machine learning: Machine learning can help you spot trends and patterns in paradata, which can help you make sure your survey results are accurate and reliable.

Potential Benefits Integrating Paradata and Processing Data with Other Data Sources

Paradata and processing data can be combined with other sources of data, including social media and sensor data. This gives you a holistic view of respondents and their environment.

Conclusion

Using paradata and process data can significantly improve your survey data quality and accuracy. It also allows you to understand your respondents better and find the most optimized way to reach them.

With Formplus Analytics and Responses dashboard, you can access your survey paradata and process data, giving you the insights you need to build better surveys and administer them more effectively.