When a survey is the better tool
Spryng asks people for a story about something that happened, and then asks them to interpret that story. That is a poor fit for some questions. Saying so at the start saves a review cycle.
Use a survey instead when
- You need a benchmark. The decision is a score against a fixed scale, a previous year, or an external standard. A story collection does not produce that score.
- You are tracking the same items over time. The point is whether a known question moved, not what a question failed to ask.
- You need large-n statistics on a closed question. The population, the sample, and the estimator are the design. Participant-interpreted stories are not a substitute for that sample.
If the answer you will act on is a number you already know how to ask for, a survey is the better tool.
Where Spryng fits instead
Use Spryng when the question is open, when the people least likely to answer a survey are part of the answer, and when the people who will act need to see the stories behind a pattern. Participants interpret their own stories. A pattern that cannot be opened onto those stories is not a result.
A low response rate on a survey is not, by itself, proof that the survey was biased, and it is not proof that a story collection would have been better. That argument is in Does a low survey response rate mean the results are biased?.
A short test
- Is the decision a comparison of scores? If yes, use a survey.
- Do you already know every answer worth hearing? If yes, use a survey.
- Do you need to learn what you did not think to ask, from people who may not reach the default channel? If yes, a story prompt is the better start.
The three situations Spryng is built around are public service, academic and health research, and practitioners.