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Survey: General

Collect quantitative information (opinions, attitudes, characteristics, behaviors).

What it is

Main objective

Collect quantitative information (opinions, attitudes, characteristics, behaviors).

Detailed description

Surveys are a quantitative methodology that allows collecting structured information from a large number of users through standardized questionnaires. This technique is fundamental for obtaining data about opinions, attitudes, behaviors, and demographic characteristics at scale, providing statistically significant insights for design decision-making. Academic research demonstrates its effectiveness for validating hypotheses and segmenting users (Interaction Design Foundation). It is advisable to combine with qualitative methods to obtain a comprehensive understanding of user behavior.

When it fits

Discovery or post-launch evaluation.

•Hypothesis validation
•Satisfaction measurement
•Market research
•Post-launch feedback

Effort level

Low to Medium

Recommended number of users

Hundreds or thousands; pilot with 3–5

What you gain and what you give up

Advantages

Reach and scale: They let you reach a large number of people (hundreds or thousands) with low resources and effort compared to interviews.
Quantifiable data: They provide numerical results that allow statistical analysis and generalizations about a population (if the sampling is correct).
Ease of administration: Online tools make it easy to distribute and automatically collect data.
Anonymity: Being anonymous, they can encourage more honest answers about sensitive topics compared to face-to-face interaction.

Disadvantages

Self-reporting bias: Participants may lie, rationalize their actions, have poor memory, or answer according to "social desirability" (what they believe is the correct thing to say) rather than the truth.
Lack of context ("why"): Surveys say what is happening or what users prefer, but rarely explain why in depth (the underlying reasons).
Rigidity: Once launched, a survey cannot be adapted or dig deeper into an interesting response the way an interview can.
Sampling bias: If the sample is not randomly selected or is not representative, the results can be completely wrong and not generalizable.