455 lines
14 KiB
Markdown
455 lines
14 KiB
Markdown
# Research Workflow - Multi-Type Research System
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## Overview
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The Research Workflow is a comprehensive, adaptive research system that supports multiple research types through an intelligent router pattern. This workflow consolidates various research methodologies into a single, powerful tool that adapts to your specific research needs - from market analysis to technical evaluation to AI prompt generation.
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**Version 2.0.0** - Multi-type research system with router-based architecture
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## Key Features
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### 🔀 Intelligent Research Router
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- **6 Research Types**: Market, Deep Prompt, Technical, Competitive, User, Domain
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- **Dynamic Instructions**: Loads appropriate instruction set based on research type
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- **Adaptive Templates**: Selects optimal output format for research goal
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- **Context-Aware**: Adjusts frameworks and methods per research type
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### 🔍 Market Research (Type: `market`)
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- Real-time web research for current market data
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- TAM/SAM/SOM calculations with multiple methodologies
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- Competitive landscape analysis and positioning
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- Customer persona development and Jobs-to-be-Done
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- Porter's Five Forces and strategic frameworks
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- Go-to-market strategy recommendations
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### 🤖 Deep Research Prompt Generation (Type: `deep_prompt`)
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- **Optimized for AI Research Platforms**: ChatGPT Deep Research, Gemini, Grok DeepSearch, Claude Projects
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- **Prompt Engineering Best Practices**: Multi-stage research workflows, iterative refinement
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- **Platform-Specific Optimization**: Tailored prompts for each AI research tool
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- **Context Packaging**: Structures background information for optimal AI understanding
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- **Research Question Refinement**: Transforms vague questions into precise research prompts
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### 🏗️ Technical/Architecture Research (Type: `technical`)
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- Technology evaluation and comparison matrices
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- Architecture pattern research and trade-off analysis
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- Framework/library assessment with pros/cons
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- Technical feasibility studies
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- Cost-benefit analysis for technology decisions
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- Architecture Decision Records (ADR) generation
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### 🎯 Competitive Intelligence (Type: `competitive`)
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- Deep competitor analysis and profiling
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- Competitive positioning and gap analysis
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- Strategic group mapping
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- Feature comparison matrices
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- Pricing strategy analysis
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- Market share and growth tracking
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### 👥 User Research (Type: `user`)
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- Customer insights and behavioral analysis
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- Persona development with demographics and psychographics
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- Jobs-to-be-Done framework application
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- Customer journey mapping
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- Pain point identification
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- Willingness-to-pay analysis
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### 🌐 Domain/Industry Research (Type: `domain`)
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- Industry deep dives and trend analysis
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- Regulatory landscape assessment
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- Domain expertise synthesis
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- Best practices identification
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- Standards and compliance requirements
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- Emerging patterns and disruptions
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## Usage
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### Basic Invocation
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```bash
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workflow research
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```
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The workflow will prompt you to select a research type.
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### Direct Research Type Selection
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```bash
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# Market research
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workflow research --type market
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# Deep research prompt generation
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workflow research --type deep_prompt
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# Technical evaluation
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workflow research --type technical
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# Competitive intelligence
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workflow research --type competitive
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# User research
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workflow research --type user
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# Domain analysis
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workflow research --type domain
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```
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### With Input Documents
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```bash
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workflow research --type market --input product-brief.md --input competitor-list.md
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workflow research --type technical --input requirements.md --input architecture.md
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workflow research --type deep_prompt --input research-question.md
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```
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### Configuration Options
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Can be customized through `workflow.yaml`:
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- **research_depth**: `quick`, `standard`, or `comprehensive`
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- **enable_web_research**: `true`/`false` for real-time data gathering
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- **enable_competitor_analysis**: `true`/`false` (market/competitive types)
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- **enable_financial_modeling**: `true`/`false` (market type)
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## Workflow Structure
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### Files Included
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```
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research/
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├── workflow.yaml # Multi-type configuration
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├── instructions-router.md # Router logic (loads correct instructions)
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├── instructions-market.md # Market research workflow
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├── instructions-deep-prompt.md # Deep prompt generation workflow
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├── instructions-technical.md # Technical evaluation workflow
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├── template-market.md # Market research report template
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├── template-deep-prompt.md # Research prompt template
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├── template-technical.md # Technical evaluation template
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├── checklist.md # Universal validation criteria
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├── README.md # This file
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└── claude-code/ # Claude Code enhancements (optional)
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├── injections.yaml # Integration configuration
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└── sub-agents/ # Specialized research agents
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├── bmm-market-researcher.md
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├── bmm-trend-spotter.md
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├── bmm-data-analyst.md
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├── bmm-competitor-analyzer.md
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├── bmm-user-researcher.md
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└── bmm-technical-evaluator.md
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```
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## Workflow Process
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### Phase 1: Research Type Selection and Setup
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1. Router presents research type menu
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2. User selects research type (market, deep_prompt, technical, competitive, user, domain)
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3. Router loads appropriate instructions and template
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4. Gather research parameters and inputs
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### Phase 2: Research Type-Specific Execution
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**For Market Research:**
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1. Define research objectives and market boundaries
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2. Conduct web research across multiple sources
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3. Calculate TAM/SAM/SOM with triangulation
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4. Develop customer segments and personas
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5. Analyze competitive landscape
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6. Apply industry frameworks (Porter's Five Forces, etc.)
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7. Identify trends and opportunities
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8. Develop strategic recommendations
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9. Create financial projections (optional)
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10. Compile comprehensive report
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**For Deep Prompt Generation:**
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1. Analyze research question or topic
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2. Identify optimal AI research platform (ChatGPT, Gemini, Grok, Claude)
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3. Structure research context and background
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4. Generate platform-optimized prompt
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5. Create multi-stage research workflow
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6. Define iteration and refinement strategy
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7. Package with context documents
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8. Provide execution guidance
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**For Technical Research:**
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1. Define technical requirements and constraints
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2. Identify technologies/frameworks to evaluate
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3. Research each option (documentation, community, maturity)
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4. Create comparison matrix with criteria
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5. Perform trade-off analysis
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6. Calculate cost-benefit for each option
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7. Generate Architecture Decision Record (ADR)
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8. Provide recommendation with rationale
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**For Competitive/User/Domain:**
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- Uses market research workflow with specific focus
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- Adapts questions and frameworks to research type
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- Customizes output format for target audience
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### Phase 3: Validation and Delivery
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1. Review outputs against checklist
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2. Validate completeness and quality
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3. Generate final report/document
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4. Provide next steps and recommendations
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## Output
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### Generated Files by Research Type
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**Market Research:**
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- `market-research-{product_name}-{date}.md`
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- Comprehensive market analysis report (10+ sections)
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**Deep Research Prompt:**
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- `deep-research-prompt-{date}.md`
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- Optimized AI research prompt with context and instructions
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**Technical Research:**
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- `technical-research-{date}.md`
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- Technology evaluation with comparison matrix and ADR
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**Competitive Intelligence:**
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- `competitive-intelligence-{date}.md`
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- Detailed competitor analysis and positioning
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**User Research:**
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- `user-research-{date}.md`
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- Customer insights and persona documentation
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**Domain Research:**
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- `domain-research-{date}.md`
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- Industry deep dive with trends and best practices
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## Requirements
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### All Research Types
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- BMAD Core v6 project structure
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- Web search capability (for real-time research)
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- Access to research data sources
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### Market Research
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- Product or business description
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- Target customer hypotheses (optional)
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- Known competitors list (optional)
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### Deep Prompt Research
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- Research question or topic
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- Background context documents (optional)
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- Target AI platform preference (optional)
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### Technical Research
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- Technical requirements document
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- Current architecture (if brownfield)
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- Technical constraints list
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## Best Practices
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### Before Starting
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1. **Know Your Research Goal**: Select the most appropriate research type
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2. **Gather Context**: Collect relevant documents before starting
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3. **Set Depth Level**: Choose appropriate research_depth (quick/standard/comprehensive)
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4. **Define Success Criteria**: What decisions will this research inform?
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### During Execution
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**Market Research:**
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- Provide specific product/service details
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- Validate market boundaries carefully
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- Review TAM/SAM/SOM assumptions
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- Challenge competitive positioning
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**Deep Prompt Generation:**
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- Be specific about research platform target
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- Provide rich context documents
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- Clarify expected research outcome
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- Define iteration strategy
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**Technical Research:**
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- List all evaluation criteria upfront
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- Weight criteria by importance
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- Consider long-term implications
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- Include cost analysis
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### After Completion
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1. Review using the validation checklist
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2. Update with any missing information
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3. Share with stakeholders for feedback
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4. Schedule follow-up research if needed
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5. Document decisions made based on research
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## Research Frameworks Available
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### Market Research Frameworks
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- TAM/SAM/SOM Analysis
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- Porter's Five Forces
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- Jobs-to-be-Done (JTBD)
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- Technology Adoption Lifecycle
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- SWOT Analysis
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- Value Chain Analysis
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### Technical Research Frameworks
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- Trade-off Analysis Matrix
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- Architecture Decision Records (ADR)
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- Technology Radar
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- Comparison Matrix
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- Cost-Benefit Analysis
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- Technical Risk Assessment
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### Deep Prompt Frameworks
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- ChatGPT Deep Research Best Practices
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- Gemini Deep Research Framework
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- Grok DeepSearch Optimization
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- Claude Projects Methodology
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- Iterative Prompt Refinement
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## Data Sources
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The workflow leverages multiple data sources:
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- Industry reports and publications
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- Government statistics and databases
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- Financial reports and SEC filings
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- News articles and press releases
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- Academic research papers
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- Technical documentation and RFCs
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- GitHub repositories and discussions
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- Stack Overflow and developer forums
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- Market research firm reports
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- Social media and communities
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- Patent databases
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- Benchmarking studies
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## Claude Code Enhancements
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### Available Subagents
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1. **bmm-market-researcher** - Market intelligence gathering
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2. **bmm-trend-spotter** - Emerging trends and weak signals
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3. **bmm-data-analyst** - Quantitative analysis and modeling
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4. **bmm-competitor-analyzer** - Competitive intelligence
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5. **bmm-user-researcher** - Customer insights and personas
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6. **bmm-technical-evaluator** - Technology assessment
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These are automatically invoked during workflow execution if Claude Code integration is configured.
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## Troubleshooting
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### Issue: Don't know which research type to choose
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- **Solution**: Start with research question - "What do I need to know?"
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- Market viability? → `market`
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- Best technology? → `technical`
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- Need AI to research deeper? → `deep_prompt`
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- Who are competitors? → `competitive`
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- Who are users? → `user`
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- Industry understanding? → `domain`
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### Issue: Market research results seem incomplete
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- **Solution**: Increase research_depth to `comprehensive`
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- **Check**: Enable web_research in workflow.yaml
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- **Try**: Run competitive and user research separately for more depth
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### Issue: Deep prompt doesn't work with target platform
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- **Solution**: Review platform-specific best practices in generated prompt
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- **Check**: Ensure context documents are included
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- **Try**: Regenerate with different platform selection
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### Issue: Technical comparison is subjective
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- **Solution**: Add more objective criteria (performance metrics, cost, community size)
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- **Check**: Weight criteria by business importance
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- **Try**: Run pilot implementations for top 2 options
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## Customization
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### Adding New Research Types
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1. Create new instructions file: `instructions-{type}.md`
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2. Create new template file: `template-{type}.md`
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3. Add research type to `workflow.yaml` `research_types` section
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4. Update router logic in `instructions-router.md`
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### Modifying Existing Research Types
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1. Edit appropriate `instructions-{type}.md` file
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2. Update corresponding `template-{type}.md` if needed
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3. Adjust validation criteria in `checklist.md`
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### Creating Custom Frameworks
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Add to `workflow.yaml` `frameworks` section under appropriate research type.
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## Version History
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- **v2.0.0** - Multi-type research system with router architecture
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- Added deep_prompt research type for AI research platform optimization
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- Added technical research type for technology evaluation
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- Consolidated competitive, user, domain under market with focus variants
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- Router-based instruction loading
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- Template selection by research type
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- Enhanced Claude Code subagent support
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- **v1.0.0** - Initial market research only implementation
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- Single-purpose market research workflow
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- Now deprecated in favor of v2.0.0 multi-type system
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## Support
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For issues or questions:
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- Review workflow creation guide at `/bmad/bmb/workflows/create-workflow/workflow-creation-guide.md`
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- Check validation against `checklist.md`
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- Examine router logic in `instructions-router.md`
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- Review research type-specific instructions
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- Consult BMAD Method v6 documentation
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## Migration from v1.0 market-research
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If you're used to the standalone `market-research` workflow:
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```bash
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# Old way
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workflow market-research
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# New way
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workflow research --type market
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# Or just: workflow research (then select market)
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```
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All market research functionality is preserved and enhanced in v2.0.0.
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---
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_Part of the BMad Method v6 - BMM (BMad Method) Module - Empowering systematic research and analysis_
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