Welcome to the Location Data Blog!

Business Intelligence (BI) and data science companies harness location data to help their clients understand target audiences better. Insights derived from analyzing human mobility patterns can help retailers, FMCG, online services, and many other companies conduct effective marketing campaigns, expand to new areas, measure ROI, find underserved consumers, and more. 

A screenshot of Mapoteca’s analytics platform showing O-D analysis for specific POIs based on mobility data. 

Countless platforms are powered by Point-of-Interest (POI) datasets that are outdated. More importantly, these datasets are not even tailored to the unique requirements of different businesses. For instance, even though a restaurant represents one POI, a specialised search engine will need information on the dietary restrictions that are catered to by the establishment while a food delivery platform needs to know if it has a drive through – data that represents distinct, custom attributes.  

Out-of-Home (OOH) advertising or outdoor media is integral to the multi-pronged marketing strategies adopted by consumer-facing businesses. Research has found that OOH drives more online activity per ad dollar spent than any other media. It is 382 percent more effective than TV, 200 percent more effective than print, and 63 percent more effective than radio ads in driving customers to an online platform. Outdoor media is instrumental for businesses to increase awareness of products and services - both online and offline. The market size is expected to reach US$ 33 Billion by 2027, exhibiting a CAGR of 13.41% during 2022-2027. 

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the locations in the city’s database were incorrect, and more than 11% of the data from a popular mapping platform was outdated.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.