Welcome to the Location Data Blog!

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.  

Point-of-Interest (POI) data is critical for executing operations in a host of industries. Even companies that do not directly rely on POI data utilise it for deriving actionable intelligence to improve performance.

The challenge most of these businesses have is that off-the-shelf and web-scraped POI datasets are riddled with outdated and inaccurate information. Most POI data providers offer one-size-fits all datasets and fail to provide data that is relevant to different types of use cases and applications.

We've put together a solution brief discussing these challenges and solving them using Geolancer, Quadrant's very own POI Data-as-a-Service platform.

Point-of-Interest (POI) data is instrumental in facilitating the operations of businesses such as food and last-mile delivery companies, those that develop mapping and navigation software, ridesharing companies, and many others. In other industries, such data is harnessed to derive insights to inform decision-making around site selection and supply chain optimisation.  

However, procuring good quality POI data is a significant challenge.  

For businesses of various scales across a range of industries, the fundamental goal stays the same: to increase profit while keeping costs to a minimum. Location data, already utilized by marketing teams and agencies, can help increase the ROI when it comes to marketing. 

Location data has proven beneficial in solving various business and social problems. Researchers and analytics firms leverage location intelligence to identify target audiences for businesses, measure ROI of operational spend, assess competition, and address grave issues like climate change, social inequalities, and human migration. In reality, most business models in delivery, transportation, navigation, healthcare, and real estate depend on location data for day-to-day operations.