In the real estate industry, price adjustments are crucial for reflecting the true value of properties. Special settings are in place to account for the specifics of each building, including the diversity of unique apartment groups.

Previously, these settings were static and established at the beginning of revaluations. They acted as “stabilizers,” smoothing the impact of initially low model training and preventing sharp price fluctuations. While beneficial, these settings sometimes reduced the system’s ability to respond to new demand trends, especially due to unique building characteristics.

Enhancing Flexibility with New Algorithms

To improve this process, we developed an algorithm that adjusts the dynamic model settings based on building parameters, sales rates, and emerging trends (e.g., increased demand for specific apartment types, floors, or views). This algorithm accelerates the system’s response to trend formation, reducing the need for manual adjustments, though this option remains available for operators.

Key Advantages

• Accurate Value Representation: dynamic settings ensure prices accurately reflect property values, considering market trends and competitive prices.
• Flexibility and Adaptability: the new algorithm enhances the system’s ability to adapt to market changes quickly.
• Minimized Manual Adjustments: automated settings reduce reliance on manual interventions, making pricing management more efficient.

By implementing these improvements, Maxify helps developers successfully navigate the pricing process, enhancing the accuracy and efficiency of decision-making.