Our Research Methodology
Rigorous, evidence-based cultural intelligence
Evidence-Based Cultural Intelligence
Our methodology combines primary research, expert validation, and continuous monitoring to deliver accurate, actionable cultural insights for global business success.
"Cultural intelligence isn't just data - it's understanding context, nuance, and the human factors that drive successful cross-border business relationships."
Our 5-Stage Research Process
1
Primary Collection
- Quarterly regional panels (50+ participants each)
- 1:1 expert interviews
- Company case study partnerships
- Anonymous survey programs
2
Cross-Validation
- Every insight verified by 2+ independent sources
- Conflicting data flagged for expert review
- Statistical outlier detection
- Regional expert sign-off required
3
Provenance Tagging
- Source type (interview/survey/case)
- Collection timestamp
- Validator identity
- Confidence score (1-100)
- Expiration date (when outdated)
4
Integration
- Vector embedding for semantic search
- Relational metadata linking
- Cultural context graph updates
- Tool/workflow integration
5
Drift Monitoring
- Automated freshness alerts
- Quarterly accuracy audits
- User feedback integration
- Outcome tracking updates
Our Expert Network
Network Composition
| Regional HR Directors | 85 |
| Cross-Border Recruiters | 62 |
| Employment Lawyers | 28 |
| Cultural Consultants | 15 |
| EOR/PEO Specialists | 10 |
| Total Active Experts | 200+ |
Expert Engagement Model
How we maintain relationships:
- Quarterly panels: Compensated participation in regional discussions
- Case study co-creation: Joint authorship on anonymized failure analyses
- Insight attribution: Experts credited for contributions (with permission)
- Early access: New tools shared with network before public launch
- Revenue sharing: Referral compensation for enterprise clients
Quality Standards
Confidence Scoring
95-100 High Confidence
3+ validating sources, expert verified
75-94 Good Confidence
2 validating sources, consistent patterns
50-74 Moderate
Single source, logical consistency
Below 50 Low
Requires additional validation
Freshness Requirements
- Salary data: Max 3 months old
- Legal/compliance: Max 1 month old
- Cultural insights: Max 12 months old
- Platform pricing: Max 1 week old
AI Reliability Integration
How Our Research Powers ARIA
Our AI assistant (ARIA) doesn't just use generic language models. It's grounded in our proprietary knowledge base with full provenance tracking.
Retrieval-Augmented Generation (RAG)
- Every response grounded in verified data
- Confidence scores displayed to users
- Source attribution for transparency
- Escalation when confidence is low
Reliability Playbook
- Self-check: AI verifies its own outputs
- Cross-exam: Critical decisions verified by second model
- Human escalation: Edge cases flagged for expert review
- Audit trail: Every recommendation logged