Welcome to the Location Data Blog!

In an era where data is at the heart of decision-making, the property insurance industry is no exception. Assessing risk, underwriting policies, and even mitigating adjacent property risks all lean heavily on accurate and contextually relevant geospatial data. In this article, we delve into how Geolancer's (Quadrant's POI-as-a-Service) accurate, up-to-date, and customizable datasets are revolutionizing property insurance at every turn – using real-world examples from multiple successful projects.   

Researchers have been utilizing location data to produce actionable intelligence that allows governments to save and improve the quality of citizens’ lives. Mobility-based studies continue to gain traction in academia and are being leveraged to unearth the hidden effects of various urban issues. One such problem is traffic congestion.  
 
As the size of the global population increases, so does vehicle ownership. As a result, traffic congestion is only going to get worse with time. Policymakers must have a thorough understanding of the true impact of traffic jams so that they can undertake suitable interventions to address them.  
 
Minoru Higa, a scholar from Simon Fraser – one of Canada’s leading research universities – used Quadrant’s mobile location data to determine if traffic congestion influenced the time people spent at work. This is a unique research focus that has not been explored in existing studies. Here, we discuss how they utilized our data alongside other third-party data to answer this question. 

Mobile location data is a valuable resource for retailers, as it provides insights into the movement patterns of consumers in the physical world. By analyzing this data, retailers can gain a deeper understanding of human mobility and use it to improve their marketing campaigns, gain a competitive edge, and identify and address operational inefficiencies. In this article, we explore several ways in which retailers can use location data to enhance strategic decision-making, reduce costs, and boost profitability. 

The ride-hailing industry is characterized by stiff competition and new businesses are entering the fray every year. By 2026, the market size for ridesharing services is expected to more than double compared to 2021. For companies to thrive in this fiercely competitive landscape, they must optimize their routing systems to expedite pick-ups, match demand, and deliver more rides per driver for maximum profitability.  

Ridesharing services need accurate and up-to-date POI data to function. However, the underlying maps that enable their operations are outdated, and changes in the physical world are not reflected nearly as quickly as needed. A lack of current and contextual information can cost rideshare companies in terms of lost driver productivity, rider churn, and overall operational inefficiency. 

Urban planners and transport economists need location data to build better cities and facilitate equitable and convenient access to public transit. The movement of people within an area and between various Points-of-interest (POI) can provide valuable insights for city administrations, governments and businesses. Inaccessible facilities and public transit networks impact the socio-economic conditions of people living in an area, and therefore, affect the quality of their lives.