Attitudinal data
Attitudinal data records what people say: their opinions, beliefs, preferences, intentions and feelings, collected through interviews, surveys and focus groups. It captures what cannot be observed directly, from why someone chose a brand to how they feel about a price.
How it works
Attitudinal research asks people to report on themselves, which makes it the route to motivations, mental models, emotional reactions and stated priorities. Surveys collect it at scale with rating scales and closed questions; interviews collect it in depth, with follow-up questions that uncover the reasons behind an answer.
Its limit is the gap between what people say and what they do: memory is imperfect, people want to appear reasonable, and they rarely know every influence on their own behavior. Researchers reduce the gap by asking about specific recent experiences instead of general habits, avoiding leading questions, and pairing attitudinal data with behavioral data such as analytics or observation.
A worked example
A streaming service asks 2,500 subscribers why they stay, and 68 percent pick price. Its viewing logs tell a second story: of the subscribers who reached the cancel page last quarter, 3 in 5 were midway through a series and did not leave. The survey captured the attitude and the logs the behavior, and a retention plan needs both.
Related
Automate this in Pulse
An attitude stated in a Pulse survey, such as always paying by card, can be checked in the same study's interviews by asking about the last purchase, where stated preference and behavior can part.