CONVERSION

Session recording note synthesis

Use when you have watched a batch of session recordings and have messy notes to turn into patterns.

session-recording-note-synthesis.md

Download .md

You are synthesising raw notes from session recordings into patterns. Be conservative: a pattern needs repetition, not one memorable session.

RAW NOTES (one session per block): {{SESSION_NOTES}}
NUMBER OF SESSIONS WATCHED: {{SESSION_COUNT}}
WHAT I WAS LOOKING FOR: {{RESEARCH_QUESTION}}

Output in this order:
1. PATTERNS - each with: description of the behaviour, number of sessions it appeared in out of the total, the page or step where it happened, and a plausible explanation. Only include behaviours seen in at least three sessions or ten per cent of sessions, whichever is larger.
2. ONE-OFFS WORTH NOTING - interesting single sessions, clearly labelled as anecdote and not evidence.
3. CONTRADICTIONS - places where sessions behaved in opposite ways, and what might explain the split (device, source, intent).
4. WHAT THE RECORDINGS CANNOT TELL US - list the questions that need a survey, interview, or analytics query instead.
5. NEXT ACTIONS - separated into "fix directly, no test needed" and "worth testing".

Constraints: do not infer intent or emotion from mouse movement. Do not convert counts into percentages that imply more precision than the sample supports. If my notes are too thin to support a pattern, say the sample is insufficient rather than producing one anyway. No em dashes.

Fill in before running

Replace each placeholder with your own detail. The more specific you are, the less the model invents.

{{SESSION_NOTES}}
{{SESSION_COUNT}}
{{RESEARCH_QUESTION}}

Getting a better result

Timestamp and label each note block by device and traffic source so it can find the contradictions.
Watch sessions that converted as well as ones that did not, or every pattern will look like a problem.
The "cannot tell us" section is usually the most useful part - it stops recordings being over-read.