Claude Prompt for Research
Create a Observational data gathering plan for UI/UX design research targeting tech leads.
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You are a senior data analyst with extensive technical knowledge in financial literacy. You write clear, precise, and implementation-ready content. Create a structured Observational data gathering plan for researching UI/UX design. **Target audience:** tech leads **Research goal:** improve team productivity **Industry context:** co-working **Tone:** casual and friendly ## Data Gathering Objectives - Primary data need: What specific information must we collect? - Secondary data needs: Supporting information to validate findings - Data quality requirements: Accuracy, recency, completeness standards - Timeline constraints and delivery milestones ## Observational Methodology ### Approach Design - Detailed methodology for Observational data collection - Step-by-step process from planning to execution - Quality control measures at each stage - Ethical considerations and compliance requirements ### Instrument Design Create the data collection instrument: #### If Survey/Questionnaire: - 15-20 well-crafted questions covering key research areas about UI/UX design - Mix of question types (Likert scale, multiple choice, open-ended) - Skip logic and branching recommendations - Estimated completion time (target under 10 minutes) - Pre-test and pilot process #### If Interview: - Semi-structured interview guide with 10-12 questions - Probing questions for deeper exploration - Opening and closing scripts - Recording and consent protocols #### If Observational/Secondary: - Data points to collect and their definitions - Observation framework and checklist - Secondary source evaluation criteria - Data extraction template ### Sampling Strategy - Target population definition - Sample size calculation or justification - Sampling method (random, stratified, purposive, convenience) - Recruitment strategy and incentive approach - Inclusion/exclusion criteria ## Data Management ### Collection Infrastructure - Tools and platforms for data collection - Data storage and security protocols - Backup and version control procedures - Access permissions and team roles ### Data Cleaning Protocol - Common data quality issues to check for - Cleaning rules and transformations - Handling missing data strategy - Outlier identification and treatment ### Data Organization - Codebook or data dictionary template - Variable naming conventions - File naming and folder structure - Documentation requirements ## Analysis Preparation - Pre-analysis checklist - Statistical tests or analytical methods aligned with Observational - Visualization approaches for UI/UX design data - Tools and software recommendations ## Reporting Framework - Key metrics and findings format - Visualization standards - Audience-appropriate communication for tech leads - Limitations and confidence intervals ## Timeline and Resources - Phase 1: Design and preparation (Week 1-2) - Phase 2: Data collection (Week 2-4) - Phase 3: Cleaning and analysis (Week 4-5) - Phase 4: Reporting and presentation (Week 5-6) - Resource requirements and budget estimate Present as numbered steps. Each step should have: a clear action title, detailed instructions, expected outcome, and common pitfalls to avoid.