layers-observed-behaviour

/layers-observed-behaviour

Assumes /layers-intro has been loaded. This skill is a library of techniques, not a script — see "How to use these skills" there.

The observed behaviour layer is the closest we can get to reality — what users actually do, not what we think they do or wish they would. Everything above it is interpretation; this layer is the source.

It splits into two situations. Detect which applies and say so:

• Plan — no research yet; design a study.
• Synthesise — research material exists; make sense of it.

With partial research, synthesise what exists first, then plan to fill the gaps.

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The decisions this layer makes

• What specific questions we most need to answer about our users
• What evidence already exists, and how reliable it is
• How to gather what's missing
• What patterns hold with confidence vs. what remains assumption

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Disciplines — what keeps observation honest

• Stay close to raw data. Observations should be specific and near the source — what users said, did, felt — not summarised into conclusions.
• Ground in something seen or heard, not in team beliefs.
• Mark confidence: observed / inferred / assumed. If you mark something observed, the verbatim that supports it should be quotable in the same note — an observed claim with no quotable evidence is really inferred.
• Name research gaps explicitly rather than papering over them.
• Workarounds are signal. A need real enough to motivate improvisation is a strong one.

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Techniques

To plan a study

Technique	Use it when
Define the learning goal	Always start here. Push past "understand users better" to 2–3 specific questions — "what triggers someone to refer a friend, and what makes them hesitate."
JTBD interviews	Understanding triggers, motivations, anxieties. Interview about a real past experience, not hypotheticals. Guide: opening ("tell me about the last time you…"), timeline (what triggered it, what you tried), motivations (what you hoped, what worried you), closing.
Contextual inquiry / observation	What users say differs from what they do — watch real work for tacit behaviour.
Diary studies	Behaviour is distributed over time or infrequent — users self-report as events occur.
Support ticket / review analysis	Existing product with accumulated signal — pain points at scale without recruiting.
Analytics review	What users do (not why). Complements qualitative; doesn't replace it.
Usability observation	Where people struggle or succeed with an existing product.