Welcome to the Location Data Blog!

Last-mile, food delivery, e-commerce, and postal services companies constantly strive to improve their services and operational efficiency to remain competitive. In this highly saturated space, the quality of location data powering delivery apps and platforms can be detrimental to the efficiency of operations. In this post, we will discuss how location data (mobile location and POI data) enables businesses to locate customers accurately, optimize mapping and routing systems, and minimize the waste of time and resources.

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.

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 However, most public maps and widely used POI data sources are outdated.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.

Cities worldwide are dealing with rapid urbanization, changing travel patterns, and most recently the aftermath of a global pandemic. As cities sprawl outwards to form low-density localities, it is difficult and expensive to serve these suburbs. Transit systems were also one of the worst-hit sectors by Covid-19, and post-pandemic recovery has been complicated due to remote and hybrid working. 

Footfall analysis is a powerful form of business intelligence that allows brands to understand the visitation patterns around various POIs (Points-of-Interest). For retail stores, restaurants, and other POSs, footfall analysis can highlight important patterns such as the busiest time of day, competitor traffic analysis, and more. Whereas for government and public agencies, footfall analysis can highlight the consumption and demand of public services for the betterment of citizens’ lives.