Welcome to the Location Data Blog!

Big data is a powerful tool for tackling climate change – humanity’s greatest challenge in the 21st century. Geospatial data is a form of Big Data that is drastically improving mitigation/adaptation strategies for climate change and increasing the likelihood that we collectively accomplish the Sustainable Development Goals. By giving businesses and governments a firm understanding of evolving mobility patterns and spatial relationships, geospatial intelligence can decrease resource consumption, lower pollution and carbon emissions, enhance our resilience to climate-induced natural disasters, and more.  

Researchers, businesses, and government agencies leverage mobile location and Point-of-Interest (POI) data to advance sustainability. Let's look at some of these use cases. 

Aqfer, a leading provider of big data marketing solutions, has announced a new partnership with Quadrant, a global leader in raw mobile location data, point-of-interest (POI) data, and corresponding compliance services.

The partnership provides Aqfer clients and their customers access to Quadrant’s raw location data feed, where they can access all of Quadrant’s anonymized and privacy-compliant movement data. Quadrant also offers manually verified and customized POI datasets on demand, along with an off-the-shelf POI data feed. This wealth of data will help Aqfer’s clients and their customers augment their existing first-party identity graphs with additional audience identifiers, allowing them to perform hyper-targeted, location-based marketing and advertising initiatives.

Geospatial data and technology offers great opportunities for the development of modern tourism applications and businesses. Accurate Point-of-Interest (POI) data is crucial for effective trip planning, online bookings, and location-based services such as digital maps and navigation systems. On the other hand, analysis of mobile location data can offer comprehensive insights into travellers' movement and behavior, allowing businesses to derive actionable business intelligence and improve their offerings.

Location-based technology and services, such as ride-hailing, online marketplaces, and food delivery have become a vital part of daily life. The effectiveness of these services depends on accurate, recent, and comprehensive point-of-interest (POI) data. However, most public maps and widely used POI data sources are outdated.

Experts predict that the need for location-based services will continue to increase, with a projected growth rate of 24.3% and to an industry market cap of over $300 billion by 2030. As the demand for these services grows, the need for reliable mapping solutions becomes increasingly important.

Good quality data is crucial for the operational efficiency of location-based businesses. Location-based analyses used in critical decision-making processes rely on the quality and accuracy of data powering them.

However, location data supply chains are characterized by a lack of transparency and authenticity, because data vendors prioritize volume over quality. To ensure that our customers make the most of their data purchase, we have made significant strides in identifying and erasing fraudulent data within our datasets. One way we achieve this is by examining our own data sources and constantly monitoring activity within our mobility and POI data feeds. We use data visualisation and proprietary AI models to spot instances of low-quality or fraudulent data and remove them before reaching customers.