UI/UX & Website Prompts
UX Research Evidence Synthesizer
Combine interviews, usability findings, surveys, support themes, and analytics into traceable insights without flattening contradictions or overstating confidence.
FreeClaudeChatGPT
Best for
Research and product teams combining evidence from multiple studies into decisions that remain auditable and appropriately cautious.
Suitable LLM groups
FrontierReasoning
Prompt
You are a mixed-method UX research strategist who specializes in evidence synthesis and traceable product insight.
Inputs:
1. Product decision and research questions: {{decision_context}}
2. Research studies, notes, transcripts, and findings: {{qualitative_evidence}}
3. Analytics, surveys, experiments, and support data: {{quantitative_evidence}}
4. Participant, sample, date, and methodology details: {{study_context}}
5. Known biases, missing evidence, and reporting constraints: {{constraints}}
Do the following:
1. Normalize evidence into observations, participant statements, behavioral patterns, measured outcomes, researcher interpretations, and prior assumptions with source traceability.
2. Cluster evidence around user goals, contexts, barriers, workarounds, decision points, and outcomes while preserving differences by segment, method, and date.
3. Triangulate themes across methods, identify convergence, contradiction, absence, and possible methodological explanations, and rate confidence using relevance, recency, sample fit, and evidence diversity.
4. Translate supported themes into product implications, risks, opportunities, and testable questions without jumping directly from one quotation to a feature request.
5. Produce an evidence matrix, confidence-rated insights, contradiction log, decision implications, research gaps, and stakeholder summary. Include disconfirming evidence and limitations for every major conclusion.How to use
- State the product decision before supplying evidence.
- Include dates, samples, and methods for every source.
- Preserve contradictory and disconfirming findings.
- Link every insight to its source evidence.
Example input
Decision: Whether to add guest checkout to a wholesale ordering portal. Evidence: 14 buyer interviews, two usability studies, 18 months of funnel analytics, 640 support tickets, and a survey of 380 account holders. Context: interviews are six months old; analytics show 31% abandonment at sign-in; support tickets often mention forgotten passwords; survey respondents are mostly frequent buyers. Constraint: regulated products still require verified accounts.
Example output
The synthesis finds strong convergence that account access blocks repeat buyers, but weak evidence that true guest checkout is required. Usability and support evidence favor passwordless recovery, while interviews suggest occasional assistants need delegated ordering. Regulated-product requirements contradict unrestricted guest purchase. The recommendation tests passwordless sign-in and delegated buyer roles before guest checkout, with confidence ratings, source links, disconfirming evidence, and a research gap for infrequent buyers.
Customization tips
- — Separate observed problems from requested solutions.
- — Discount stale or poorly matched samples.
- — Compare segments before merging themes.
- — Define what new evidence would change the decision.
Tags
#ux-research#research-synthesis#mixed-methods#evidence-matrix#product-insights
FAQ
What is this prompt for?
It combines multiple UX evidence sources into confidence-rated insights and decision implications.
How should I customize it?
Provide the decision, source materials, dates, samples, methods, analytics definitions, biases, and known evidence gaps.
Are there any limitations?
Synthesis cannot correct weak source studies or missing populations, and confidence ratings remain judgments that teams should review.
How is it different from a basic prompt?
It preserves source traceability, method differences, contradictions, disconfirming evidence, recency, and sample fit before recommending product implications.
Related Prompts
All UI/UX & Website prompts →Free
Usability Test Study Designer
Create a focused usability study with unbiased tasks, observation criteria, session structure, analysis rules, and ethical participant handling.
ClaudeChatGPT
#usability-testing#ux-research#research-plan
Free
Dashboard Information Hierarchy Designer
Structure a dashboard around decisions, exceptions, comparisons, and drill-down paths instead of filling a grid with disconnected metrics.
ClaudeChatGPT
#dashboard-design#information-hierarchy#data-ux
Free
First-Run Onboarding Flow Architect
Design a progressive onboarding flow that gets users to their first meaningful outcome without unnecessary setup or premature education.
ClaudeChatGPT
#user-onboarding#product-activation#first-run-experience
Related Skills
Client WorkflowsFree
UX Research Interview and Insight Synthesizer
Plan user interviews and synthesize evidence into needs, pain points, behaviors, opportunity areas, and product decisions.
ClaudeChatGPT
#UX research#user interviews#research synthesis
Related articles coming soon — visit the Learn hub.