Qualitative data
Qualitative data is non-numerical information, such as interview transcripts, open-ended answers, notes, recordings, images and documents, that describes qualities, experiences and meanings. It answers why and how, where quantitative data answers how many.
How it works
Qualitative data comes from methods that let people express themselves in their own terms: in-depth interviews, focus groups, observation, diaries and open-ended survey questions. It is rich and contextual, capturing reasons, emotions, language and sequences of events that numbers cannot.
Because it cannot be averaged, it is analyzed by coding: labeling passages, grouping them into themes and interpreting the patterns, through approaches such as thematic analysis or grounded theory. Samples are usually smaller than in quantitative research and chosen for relevance rather than statistical representativeness. Mixed methods research combines it with quantitative data in one study, so a measured change and the accounts behind it are read together.
A worked example
Say a streaming service collects 30 diary entries about weekend viewing after a home-screen redesign. Coding them produces 3 themes. The largest, in 19 of the 30 entries, is losing track of a half-finished show now that the "continue watching" row sits below 3 rows of new releases. The team moves the row back up and runs a second diary round of 30 to check the change.
Related
Automate this in Pulse
Every Pulse interview becomes qualitative data a team can reread, a full transcript kept together with its recording.