Replicating actual market decisions in a survey choice task is an important design goal. However, given that survey respondents have moved to devices with smaller screens, it has become increasingly difficult to accomplish the goal of realism.

When you need to compare, rate, or optimize a long list of features or attributes, consider using MaxDiff (Maximum Difference Scaling) instead of a grid. MaxDiff forces respondents to make trade-offs (or choices), like they do in the real world.

Leading questions are one among many types of biased survey questions. The problem with biased questions, attributes, and response choices are that they create inconsistent, contradicting, and misleading results.

Choice modeling techniques should be recommended first to assess product pricing. When clients are budget-strapped and time-pressed though methods, such as the Gabor-Granger analysis, can provide sufficient guidance

In an effort to catch survey cheaters, researchers use negatively worded attributes placed in groupings of positively worded attributes. This context switching causes respondent confusion, which creates error.

Typically, market segmentation uses 5 question types in the analysis so that segments differ on many facets (needs, behaviors, psychographics, personality characteristics, and demographics), not just needs.

Marketing Research Article: The Recommendation Question with its well-defined answer choices and the Net Recommendation Score formula give you a much more precise measure of the net influence of customer recommendations than the Net Promoter Score.

Online data collection relies heavily on the honesty of respondents. Key areas of mitigating front-end data vulnerability include correct identification of respondents, constructing surveys that are both cognitively and affectively close to the actual consumer decision-making process.