Survey design

A survey can only measure what interviews have already uncovered, and a badly written one measures the questionnaire instead of the market. This skill builds short, neutral surveys and reads the results with the right caution.

When to use

• After customer-interviews, to measure how common a problem, a habit or a preference is.
• To compare segments or track satisfaction over time.
• Not to discover new problems, and not to forecast sales: "would you buy it?" answers overstate real demand.

Inputs

1. The decision the survey informs.
2. The target population and how to reach it.
3. Constraints: budget, deadline, survey tool.

Method

1. One decision, a few numbers: write the decision and the three to five numbers needed to make it. Every question feeds one of them; cut the rest.
2. Define the population and the sample: who exactly, how they will be reached, and the bias of that channel (a post on the founder's social network reaches the founder's network, not the market).
3. Compute the margin of error for a proportion, and say that it only holds for a random sample: margin = 1.96 × √(p × (1 − p) / n). With p = 0.5, it is about ±9.8 points for 100 answers and ±4.9 points for 400.
4. Write neutral questions: one idea per question, no loaded words, no jargon, a "don't know" or "not applicable" option when it fits, balanced scales (as many positive as negative points), a precise time frame ("in the last 30 days").
5. Order the questionnaire: screening questions first, easy factual questions next, sensitive ones (income, age) last. Keep it under ten minutes and shuffle answer options when their order could matter.
6. Ask about behavior when possible: "What did you use last time?" beats "What would you use?". Treat purchase intent as an upper limit, never as a forecast.
7. Pilot it with five people from the target who think aloud while answering, then fix what confused them.
8. Analyze honestly: report the number of answers, the response rate, the sample's bias and the margins of error; compare segments only when each has enough answers; show the exact wording next to each result.

Output

### Survey plan
Decision: … | Numbers needed: … | Population: … | Channel and its bias: …
Planned sample: n = … (margin of error ±… points, random sample only)

### Questionnaire
| # | Question (exact wording) | Type and scale | Feeds which number |
|---|---|---|---|

### Results
| Number | Result | n | Margin of error | Caveat |
|---|---|---|---|---|

Quality bar

• Every question maps to the decision; none is leading, double or hypothetical without a warning.
• Margins of error are computed, not guessed, and the sampling bias is stated.
• Purchase-intent answers are never presented as a sales forecast.
• The survey says how answers will be used, and personal data is kept to a minimum (GDPR in the European Union).
• Written in the user's language, with the terms below.

Terminology

Sources

• Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method (4th ed.). Wiley.
• Saunders, M., Lewis, P., & Thornhill, A. (2019). Research Methods for Business Students (8th ed.). Pearson.