Creating Questionnaire that Works

Creating a survey questionnaire that will deliver effective marketing research data collection is a difficult process with many opportunities for making some of the more common market research errors. Many less experienced market researchers may believe that creating a questionnaire is simply the act of coming up with questions and putting a pen to paper, but that is dangerous assumption (see common research errors).

Creating a questionnaire requires as much science as art, and incorporating those two elements into a high-quality survey that will draw a good response rates while effectively collecting accurate data often takes time and experience.

When creating a survey questionnaire, there are basic types of scale questions to have in your tool box. They are:

    • Nominal — when numbers are used to identify objects, such as social security number, license numbers or daily customers. In this case, the number acts mostly as a data tag, typically for identification.
    • Ordinal — when numbers are used to indicate the relative position, but not indicate the magnitude of the difference between those positions. An example of this would be rankings in which items are listed by priority, say first through fifth, or competitive events where the quantifiable difference in perception between #1 and #2 is unknown.
    • Interval — when a rating scale is used and the zero point is arbitrary. An example of this is satisfaction scores (satisfaction of 3 on a scale of 1 to 5) as well as most other attitude and opinion questions, regardless of the scale used (3, 5, or 10 point). Unlike ordinal, the difference between each data point is fixed.
    • Ratio — the most useful of all of the scales in creating a questionnaire, ratio scales allow the researcher to incorporate each of the above listed scales into one (nominal, ordinal and interval). The key difference with ratio is that unlike the interval scale, it is anchored with an absolute zero point. Examples of ratio questions are market share, income group, age group, etc.

If you are creating a questionnaire from scratch, it is important to be mindful of these scales as each one lends itself to a particular type of data analysis.

Contact Polaris for help in creating a questionnaire capable of effectively and accurately collecting data while avoiding common market research errors.