layers-observed-behaviour

To turn user research evidence into job stories, this Skill transforms interview transcripts, notes, and behavioral data into structured observations and candidate job stories equipped with confidence ratings for actionable product discovery.

Synthesizing user interview notes for product discovery involves separating raw observations from assumptions to identify recurring motivations and extract evidence-backed job stories, preventing product teams from guessing about user needs.

Yes, you can use this to plan user research studies by defining specific learning goals, selecting appropriate participants, and choosing suitable methods such as interviews, observation, diary studies, and analytics review.

Behavioral analysis identifies user needs by processing raw research data to extract specific observations, recognize patterns in real-world signals, and generate candidate job stories that highlight actual user motivations and existing research gaps.

You do not need strictly formatted transcripts to analyze observed behaviour; the Skill processes scattered interview notes, support signals, and behavioral data to separate raw observations from assumptions and produce actionable research outputs.