Today we're announcing the release of Counterfactually, bringing data-driven impact assessment to web3 funding initiatives. As the ecosystem has deployed over $100M+ through mechanisms like Gitcoin Grants and Optimism's RetroPGF, we're addressing a critical question: How do we measure the real impact of these investments?
The Challenge
Traditional impact assessment relies heavily on qualitative metrics that don't capture the full picture. The fundamental counterfactual question—"What would have happened if this project never existed?"—has remained elusive. Until now.
Technical Implementation
Counterfactually implements synthetic control methodology to construct precise counterfactuals:
Our approach:
- Analyzes key metrics across multiple networks
- Constructs synthetic controls through weighted combinations
- Measures divergence between actual and synthetic baselines
API Access
The platform exposes a comprehensive API for custom integrations:
curl -X POST https://counterfactually-production.up.railway.app/api/analyze \
-H "Content-Type: application/json" \
-d '{"network": "arbitrum", "metric": "daily_active_addresses"}'
Full documentation available at our API docs.
Key Features
Data Pipeline
- Real-time metric processing
- Integration with major L2 networks
- Automated weight optimization
Analysis Dashboard
- Interactive network comparison
- Custom metric selection
- Real-time visualization
Methodology
- Synthetic control construction
- Statistical significance testing
- Robust error estimation
Future Development
Our roadmap includes:
- Advanced metric aggregation
- Custom control parameters
- Extended historical analysis
- Funding platform integrations
Get Started
- Visit counterfactually.org
- Select networks for comparison
- Choose relevant metrics
- Generate synthetic control analysis
By bringing scientific rigor to impact assessment, Counterfactually provides the tools to ensure every dollar spent on public goods creates maximum value for the ecosystem.
