We talk a lot about advanced methods - and for good reason. Advanced methods are a means of research that go beyond the 'what' to get at the 'why'.
In this report, we focus on how advanced methodologies (like Conjoint, Key Driver Analysis, TURF, and so many others) generate richer, more actionable findings than standard usage and attitude questions alone.
Advanced research methods add a layer to existing U&A insights by uncovering underlying consumer preferences, reactions, needs, or motivations. With AI-based algorithms built into the backend, consumer data goes beyond simple multi- or single-select questions to put context behind consumer decisions (i.e. a respondent may like several fast food restaurants - but which do they like more than others?).
Still not yet convinced? Access the report below for an example of how a MaxDiff (a type of advanced method) produces a much more actionable and telling takeaway for grocery brands than a descriptive rating or ranking scale question.
