Welcome to the Location Data Blog!

As a proxy for human mobility within the physical world, raw location data provides unparalleled insights into people’s behaviors and needs. Businesses harness such intelligence to boost performance while governments and non-profit organizations leverage it to execute people-centric development programs.   

However, the location data industry is teeming with issues (obscure supply chains, poor quality control, inflexible business practices, an abundance of non-compliant data, etc.). These factors make it extremely challenging for data scientists and analysts to generate actionable intelligence.   

We’ve crafted a solution brief that details all these problems and elaborates on how Quadrant is solving them through our industry-leading location data offering. The brief also contains use cases and customer success stories with proven results for various use cases.   

In the insurance business, many decision-making processes hinge on location intelligence and real-world geospatial information. Point-of-Interest (POI) data in particular is used for building contextual profiles of neighborhoods and determining precise risk scores for commercial and residential properties - which enables the creation of better policies. 

Many insurance businesses use satellite and aerial imagery to guide risk assessment and underwriting. However, neither of these tools can offer the comprehensive insights that can be unlocked through ground level geospatial data.  

The location data industry is characterised by opaque supply chains, making it challenging for buyers to procure high-quality datasets. Quadrant’s mission to instill transparency into the industry starts with how and where we source the data. We have been successfully working on acquiring data right where it is created, incentivizing developers to ethically monetize their mobile apps.

One way of doing this is SDK integration, which we have covered in detail. The other, increasingly popular method is Server-to-Server (S2S) integration; in this piece, we give readers a peek behind the curtain so that they can understand how S2S works.  

As users, we are not surprised to discover that a restaurant or a store on the map does not exist in the real world. It might have closed, moved, or never existed in the first place. Low quality POI datasets might be a mere inconvenience in our personal lives; however, this is a multi-million dollar issue for businesses.

Until recently, we couldn't even tell how big the problem is. After collecting and verifying 5,000 electric vehicle charging stations in Amsterdam in person, we have an answer: it is enormous.

We discovered that more than 14% of the locations in the city’s database were incorrect, and more than 11% of the data from a popular mapping platform was outdated. And this is just the tip of the iceberg. 

For years, Quadrant has been offering high-quality, authentic, and reliable mobile location data. In our interactions with customers and prospects, we discovered that many of them seek Point-of-Interest (POI) data to go with their mobility analysis. Good quality POI data is critical for operational efficiency, especially in sectors like transportation, delivery of consumer services, supply chain logistics, freight, and many others.

However, existing off-the-shelf POI databases are plagued with issues. They are not updated frequently enough, and the way they are assembled -- most often through web scraping -- leads to inevitable inaccuracies.