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What is data quality in surveys?

Data quality is a collection of several characteristics that determine the usability and trustability of the data.

QuestionPro lets you find and flag the errors, bad or duplicate survey data without manual intervention. Our tool accesses each answer and has full control over repetitive values, spikes, and spoofing. The result is clean, accurate, and quality data that can be used to gain actionable insights.

Example of high-quality data

Consider a scenario in which a respondent tries to answer a survey multiple times. If allowed, it will lead to bad data and affect data quality. With data quality check enabled, the duplicate responses will be flagged. The users have an option to review the answer and unflag it.

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In the example below, the first response was considered valid, but the second response from the same IP address was be marked duplicate.

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Data quality in QuestionPro surveys

QuestionPro's data quality tool can check the data quality of textual responses collected through open-ended questions, and quantitative data collected from multiple choice and graphical questions.

QuestionPro improved data quality by correcting below errors in the survey results:

Learn more: Data quality - One-word answers

Learn more: Duplicate text across responses

Learn more: Data quality - All checkboxes selected

Learn more: Patterned responses

Learn more: Duplicate IP across responses

Learn more: Speed traps

Learn more: Gibberish words

Why is data quality important in research?

Researchers conduct surveys to derive value and insights from the data collected. However, the usability of the data depends on the data quality. The resources spent on conducting research will go in vain if you don't emphasize on the quality of data collected.

As more organizations increasingly use data, it has become imperative for any business to make choices based on data. The decisions backed by data not only have a high potential to be correct but also are essential to staying competitive in the market.

Bad data can lead to decisions that turn into costly mistakes. According to a research study conducted by Gartner, poor data quality leads to a loss of $15M on average per year. If you base your decision on bad data, you are likely to make the wrong choice. The better the data quality, the higher the chances of success.

Advantages of quality survey data

How to improve the data quality of your surveys?

Learn how to set up and use this feature with our help file on data quality.

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