Data-driven Real Estate Analysis and Matching

The research project enables data driven insights to build optimal, and vibrant neighbourhoods filled with life and activity. With new machine learning and optimisation techniques, together with data on movement and spending patterns, demography and business data the project aims to understand what constitutes an optimal city floor. This can foster better decisions for shops, restaurants and property companies which makes up the city floor. Functionality enabled by the research gives shops, restaurants and service companies insights into where their business is best suited for success, maximising their profitability and drawing people and activity to the area. Through optimisation of the city floor, retail companies can also benefit from synergies with nearby business, and the inhabitants will in time have a better and more deliberate service offering in their neighbourhood. The research may increase revenue and profitability for a large part of the Norwegian economy, and positively affect the people living and using the city through increased activity, better service offering and quality of life.

Tasks related to data analysis, ML model development, and optimization were partially completed. The project achieved the delivery of the Dream Matching Optimizer, which demonstrated practical applications of optimization techniques for tenant assignment. However, the development of the revenue prediction model remained incomplete (in terms of the required quality of the predictions) due to significant data constraints. The absence of a robust revenue prediction model limited the integration and deployment of optimization and collaboration solutions within the Plaace platform. CRE partners will see improved utilization of their properties, and the participating RHS businesses will be able to use the platform to establish new, successful locations, if new quality data appears that can be used for the models. If better data is acquired the ground work of the project is ready for new results that could significantly improve outcomes for actors in the CRE and RHS industries, which today have an annual gross revenue of 735 BNOK in Norway, and far higher abroad. Enabling cooperation between CRE companies will also enable better coordinated city districts, which will be more attractive to inhabitants and visitors.

The DREAM project will establish an entirely new way of operating the retail commercial real estate market. The Plaace platform lets retail, hospitality and service businesses match their needs with available retail space. Supported by new tools enabled by the DREAM project, these businesses will be able to make smarter location decisions, generate more revenue and attract more customers. This benefits property companies owning retail space directly by increasing rent and property value. Using AI and optimization techniques, the project will build algorithms for (i) evaluating the location-based performance of a business, (ii) finding good business mixes for a group of available locations and (iii) helping commercial real estate companies collaborate to build better commercial areas. These approaches will significantly improve the current market, reducing the risk of wrong. The results will be prototyped and piloted in the Plaace platform, and tested and evaluated by participating partners, ensuring their real-life applicability and preparing for their availability to the sector at large.