In today’s rapidly evolving world, Point-of-Interest (POI) data has become the lifeblood for various sectors including retail, logistics, and travel. Whether you are a data scientist creating predictive models or an operations manager overseeing a distribution network, the quality of your POI data can make a world of difference. That’s why we took it upon ourselves to put our POI datasets to the test against two of the world’s largest mapping providers, especially focusing on the dynamic markets in Asia. What we found not only reassures our faith in our data quality but also reveals glaring gaps in some of the most trusted mapping databases today.

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.   

Point-of-Interest (POI) data has become a key component in driving innovation, efficiency, and personalized user experiences across diverse industries. From enabling ride-sharing services to identify pick-up and drop-off locations and ensuring timely last-mile deliveries, to enriching real estate insights and supporting state-of-the-art AI models and Large Language Models (LLMs), POI data is reshaping how businesses operate.  

In this fast-paced global economy, supply chain and logistics businesses must constantly innovate to optimize operations, reduce costs, and boost efficiency. We recently published an eBook that delves into the use of Point of Interest (POI) and mobile location data as tools to streamline supply chain operations.

By leveraging location data, businesses can optimize navigation and route planning, and gain insights into their facilities to address disruptions and promote operational efficiencies. The eBook also covers real-world examples, challenges, and best practices for effectively harnessing POI and mobile location data.

Picture this: You're sitting in an Uber or Grab car, and you notice that the driver's screen shows more than just a standard map. It's filled with additional information like pick-up and drop-off points, traffic jams, and accident locations. These are known as thematic layers, and they play a crucial role in enhancing the operations of location-based businesses by overlaying them onto base maps.