RetailWatch will monitor the number of cars in the car parks of selected retail outlets to estimate footfall, in an effort to predict the financial performance of retailers. The RetailWatch project uses high resolution satellite imagery and artificial intelligence techniques to provide an additional service to retail companies in a competitive market. RetailWatch will provide investors in retail stocks with an early indicator of equity performance before the publication of retailer’s quarterly reports.
The project will draw upon Geospatial Insight’s vast knowledge of satellite imagery, innovative machine-learning capabilities and experience within the financial markets. Couple this with Deimos Space UK’s new machine-learning approaches to feature classification of high resolution satellite imagery, and a formidable partnership is formed.
Dave Fox, CEO of Geospatial Insight comments:
“We’re looking forward to strengthening our relationship with the Deimos Space UK team by collaborating on RetailWatch. The awarding of funding by the ESA for this project demonstrates their commitment to investing in satellite technology and machine-learning both in Europe and globally.”
Michael Lawrence, Business Development Director of Deimos Space UK added:
“We’re excited to be working alongside the Geospatial Insight team in developing RetailWatch. This represents a fantastic opportunity to use our machine learning capability to provide an extra analytical dimension to the world of retail.”
Since 2007, UK space companies have grown at an average rate of 10% a year, with employment also growing 15% year on year (1). The launch of RetailWatch opens up another avenue of commercial opportunity within this industry and represents an opportunity for various stakeholders (such as hedge fund managers, commodity traders and retailers) to gain a detailed insight into retail performance.
Key to the RetailWatch project is the use of machine-learning algorithms developed by both Deimos Space UK and Geospatial Insight to automate the car counting process. As a service global machine learning had an estimated worth of US$1.07 billion in 2016, rising to US$19.86 billion by the end of 2025 (2). RetailWatch seeks to marry together two flourishing sectors; space and machine learning, to provide a unique insight into the retail sector.