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EU Real Estate Investment Strategies

Targeting high-value industries and predicting office space demand for real estate development

EU Real Estate Investment Strategies


Aretian worked with a leading European real estate development Company to provide data-driven recommendations and strategies for real estate investments in Paris, Madrid, and Barcelona. Our project aimed to reduce the Company’s uncertainty in real estate decision-making by offering precise, predictive insights on urban development patterns and their impact on property valuation, industry growth, and overall city performance.

Madrid Real Estate Predictions

The Challenge

Traditional methods lacked the precision required to understand the intricate relationships between urban design patterns, property valuation, and economic performance at a granular level.  The Company wanted to improve its decision-making by understanding:

  1. The advantage of investing in assets in each city’s knowledge economy centers (e.g., central business districts)

  2. How to identify which high-value industry sectors (e.g., tech, life sciences, manufacturing) were locally competitive and

  3. How to measure, track, and predict the future office space demand by sector for each city

Aretian’s Solution

Aretian proposed a city science-led analysis of several case studies to validate the Company’s needs. By applying advanced urban modeling techniques, Aretian provided quantitative and qualitative descriptions of urban development patterns, measured urban performance through our established globally benchmarkable KPIs, and offered predictive insights to inform high-quality real estate development projects. This systematic approach enabled the Company to make data-driven decisions aligned with their strategic goals.

Barcelona Real Estate Predictions


  1. Validated the Company’s premium office property hypothesis in Paris, Madrid, and Barcelona with strong statistical significance, demonstrating the correlation between knowledge economy factors (e.g., Central Business Districts) and real estate prices.

  2. Identified target industries in the three target cities with local comparative advantages to shape city-specific real estate investment strategies

  3. Predicted future office space demand by sector in the three cities, aiding in precise demand forecasting.

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