Cernunnos PropTech Investment Analytics
Context
This project was developed for Cernunnos, a PropTech-focused investment group operating across real estate, technology, and urban innovation. The objective was to analyze investment performance, asset allocation, and risk exposure across a heterogeneous portfolio of PropTech assets.
The challenge lay in combining financial data, asset characteristics, geographic information, and strategic indicators into a single analytical framework that supports investment decisions and long-term portfolio strategy.
Project Type
Professional
Investment Analytics · PropTech Intelligence · Data Storytelling
Goals
- Structure fragmented real estate and PropTech datasets
- Create a unified view of portfolio exposure and performance
- Support strategic asset allocation and risk assessment
- Enable clear communication between investment, strategy, and executive teams
Data
The analysis relied on internal Cernunnos datasets, including:
- Asset-level investment data
- Geographic location and typology of properties
- Financial performance indicators
- Exposure, risk, and concentration metrics
- Selected operational and market indicators
All datasets were cleaned, normalized, and modeled to ensure analytical consistency across assets and time.
Approach
1. Data + Investment Strategy Alignment
The project began with an in-depth review of available datasets and investment objectives. Particular attention was paid to asset granularity, temporal consistency, and cross-comparability.
2. Modeling + Analytical Design
A modular data model was designed to allow:
- Cross-analysis between asset type, geography, and performance
- Scenario analysis and aggregation at portfolio and sub-portfolio levels
- Scalability for future asset acquisitions
Key indicators were selected to reflect both financial performance and strategic positioning.
3. Visualization + Iteration
Interactive dashboards and charts were developed to highlight:
- Portfolio composition by asset class and geography
- Performance evolution over time
- Risk concentration and exposure patterns
- Comparative analysis across PropTech segments
Iterative feedback loops ensured the visuals supported decision-making, not just reporting.
Selected Visualizations
Selected analytics and dashboards developed for the project.
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Key Insights
- Clear concentration patterns across asset classes and regions
- Identification of under- and over-exposed PropTech segments
- Improved visibility on performance dispersion within the portfolio
- Stronger alignment between investment strategy and data-driven insights
Outcome
The project delivered:
- A shared analytical framework for portfolio review
- Clear visual tools for investment committees
- Reduced friction between data, strategy, and decision-making
- A scalable analytics foundation for future PropTech investments
Role
Data Strategy · Analytics · Visualization
End-to-end responsibility from data modeling to dashboard delivery.
About This Work
This project embodies Danki Studio’s approach to investment analytics:
clarity over complexity, structure over noise, and insight over volume.
By designing lean data models and purposeful visualizations, the analytics created for Cernunnos support confident, informed investment decisions.