Real estate

Using big data to identify the best investment opportunities

Who we work with

  • Real estate developers and investors
  • Proptech companies
  • Real estate consultants

How can we help?

So-called property technology, or proptech, encompasses the application of a wide spectrum of digital technologies to the real estate industry. From the use of online platforms and virtual reality for sales and rental processes to the automation of property management, digitalisation is rapidly transforming the way real estate properties are searched for, bought, sold, rented and managed. One of the areas of proptech that has raised more interest is the use of big data and artificial intelligence to facilitate the identification of investment opportunities and enable a more accurate valuation of real estate properties (e.g., by tracking market metrics in real-time and facilitating valuation by comparables). 

Nommon supports real estate developers, investors and consultants in the identification and assessment of real estate investments by providing them with accurate data on the spatial behaviour of potential customers. When it comes to residential properties, our Mobility Insights and Population Insights solutions help track residential migrations and address questions such as the number, the profile and the primary residence of people who own a second home. In the case of retail stores, we provide detailed information of the number, profile and behaviour of potential customers that are present in the catchment area, and use this information to produce detailed sales forecasts through Nommon’s InSite location intelligence platform.

Our products

Best-in-class origin-destination matrices from mobile network data

Leveraging mobile location data to understand visitor footfall and customer behaviour

Transforming location intelligence through high-resolution mobility data and predictive analytics

Crafting innovative solutions based on geospatial big data and predictive analytics

Related content

Research Projects
2013 - 2016