synthesize-research

name	synthesize-research
description	Synthesize interview notes, survey data, or support tickets into themes, personas, opportunity areas, and roadmap recommendations. Use when turning raw research into structured findings. Do NOT use for competitive analysis (competitive-brief) or product strategy doc (product).
license	MIT
allowed-tools	Read Write Glob Grep
argument-hint	<research topic or question>
metadata	{"author":"Carinya Parc","version":"0.1.0","owner":"delivery","review_cadence":"quarterly","work_shape":"generate-draft","output_class":"decision-support"}

Synthesize research

You synthesize user research from multiple sources into structured insights and recommendations. Pass the research topic or paste source material after the skill name.

See CONNECTORS.md for feedback/analytics connectors. For thematic analysis, affinity mapping, survey pitfalls, personas, and opportunity sizing, read research-synthesis.md when needed.

Steps

1. Gather inputs

Accept pasted notes, uploads, or connected knowledge base / feedback / analytics / transcripts. Confirm: research type, source/participant count, research question, and what decision this informs.

2. Process each source

Extract: key observations, verbatim quotes, behaviors vs stated preferences, pain points, positive signals, and context (segment, use case, experience).

3. Theme and prioritize

Group into themes; count frequency; assess impact. Priority matrix:

	High impact	Low impact
High freq	Top priority findings	Quality-of-life
Low freq	Important for segments	Note; deprioritize

4. Generate the synthesis

1. Research overview — methods, participants, questions, timeframe
2. Key findings (5–8) — statement, evidence, frequency, impact, confidence
3. Segments / personas — if distinct patterns emerge
4. Opportunity areas — unmet needs, prioritized by impact
5. Recommendations — specific actions tied to findings
6. Open questions — gaps and suggested follow-up research

5. Extend

Offer persona docs, opportunity maps, follow-up research plans, or product implications for the roadmap.

Quality rules

• Let the data speak; do not force a predetermined narrative
• Behavioral evidence beats stated preferences
• Explicit confidence levels (2 interviews = hypothesis, not conclusion)
• 5–8 strong findings beat 20 weak ones
• Recommendations must be specific enough to act on

Output format

Clear headers. Each finding stands alone with supporting evidence and attribution to participant type (not name).