What’s in a question?

By Ellen Hewitt

Feedback surveys are a vital way of assessing how well training or a service is delivered to a client. The power of anonymity, where a person can give feedback without confrontation, is a vehicle we can use to really understand what a person thinks. We are then able to address the feedback in meaningful and useful ways, tailoring our services to better suit a client’s needs.

However, if we don’t get the collection instrument right (that is, the questions, and how we gather information) then even the best data analysts in the world can’t turn the results into meaningful and useful information.

Here are some things to think about when writing questions:
  • What do you actually need to know? So much data goes completely unutilised, because it’s collected “just in case” it’s needed later. If you spend time working out exactly what information you need, then the survey will be shorter, more succinct and more likely to be completed by a busy respondent.
  • Tailor the wording to who is actually going to be completing the survey. It pays to test wording before a survey goes live, to make sure it’s understood. Leave “management speak” for managers, and cater to the lowest demographic.
  • Be careful not to ask leading questions. “Did you enjoy a free lunch?” is quite a different question to “Did you enjoy the free lunch?”
  • Any variables you want to compare need to have the same answer type. Whether this is open text, a scale of 1-10, or a likert scale (a scale that measures attitudes or behaviours e.g. “How satisfied or dissatisfied were you with the catering during the event? Very dissatisfied, fairly dissatisfied, neither satisfied or dissatisfied, fairly satisfied, very satisfied”).
  • Think about whether you want to force your respondents to answer each question.  A “don’t know” option can often be the easy way out for a respondent, the same as the middle or “average” option in a likert scale answer. It can be useful to force an opinion.

Writing questions that deliver fit for purpose data that meets your needs can be challenging. It is always useful to test your questions on as many people as possible, as it’s amazing how words can be interpreted differently by different people.


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