Welcome to the Location Data Blog!

 

Learn how companies all over the globe are utilising location data to enhance business operations and improve profitability. Keep up with industry updates, best practices, and key learnings from location intelligence projects we have executed.

How Quadrant prevents fraudulent records within location data supply chains

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. 

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Geolancer database doubles in just 10 weeks - hitting 500,000 POI

A few weeks ago, we announced that Quadrant had collected 250,000 POIs through Geolancer. Today, we are excited to share that we have doubled the size of our database to over half a million POIs!  

The increasing demand for Geolancer's manually collected, recent, and attribute-rich data has encouraged our rapid expansion. Besides hitting the half-million mark, we are happy to report that three of the world's top 5 mapping companies are now leveraging Geolancer's industry-leading POI data.

Besides rapid growth, we also have other exciting news to share.



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Automating in-field POI collection to rapidly deliver high-quality datasets

Quadrant’s POI Data-as-a-Service platform, Geolancer, is superior to conventional POI data collection tools in many ways. Geolancer’s ability to quickly provide high-quality, customizable metadata on demand makes it stand out in a sea of POI data providers. Our bespoke POI datasets allow businesses to increase operational efficiency, build better products, and enhance customer experience.  

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Creating attribute-rich contextual maps for Gojek with Geolancer (Case Study Preview)

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. 

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Mapping a quarter million POIs with Geolancer

This week, we are celebrating collecting a quarter million Points-of-Interest with Geolancer. We have reached the 250,000 POI milestone in just 12 months, starting in two countries in Southeast Asia, and gradually expanding to five. Scaling a new product from zero is something we are proud of; however, our platform’s real strength lies in its quality. There is not a single dataset in the industry that even comes close to Geolancer’s accurate, complete, and rich metadata.

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