Point of interest (POI) data is the collection of information on a public place. From geographical to functional information, POIs can be anything from everyday places like shops, parks, and tourist attractions to unique places like statues, monuments, or natural landmarks. They can be temporary, like food carts or marketplaces, or permanent, like a public park or a river. Due to their convenient location or a unique service, product, or experience, customers and passersby visit them.
Public institutions and private companies use POI data to learn more about a location and the people who visit it. This in turn enables them to improve their experience of the location.
One of the primary sources for POI data is on-site data collection. Since it comes from first-hand information, this method is fairly accurate and comprehensive because, though it’s also less efficient, less scalable, and more costly than other methods. It is also more difficult to update data for many locations frequently using only first-hand information collected on-site.
Geocoding is another source of POI data, although this usually only provides location information and disregards other attributes. Information can also be collected through social media platforms but, while this means frequent updates, accuracy is not as reliable.
Other methods of data collection include governmental sources and geographic platforms like Google Maps that specialize in this type of information. Their data is usually accurate but they update infrequently and may be limited by privacy restrictions.
The primary POI data attributes are location (coordinates, address, or both), name, function (restaurant, natural landmark, store, etc.), contact information, and franchise information. Other common attributes include ratings and reviews, foot traffic data, images, hours of operation, natural or environmental information, and current updates issued by management or local government about the location.
Organizations mostly use point of interest data to assess a location and study the public’s behavioral trends. Businesses also use the data to track the performance of their brick-and-mortar stores as well as those of their competitors by recording store location alongside store visit counts and neighborhood foot traffic data to ensure that stores are ideally located.
Other businesses use POI data, as well. Marketing and ad-tech companies create geofences around points of interest to create location-based audiences. Real estate investors use POI data to predict how the real estate market might perform in certain areas. Transportation companies use it to determine the most efficient routes and number of vehicles to allocate to an area.
Local governments use POI data to plan better resource distribution to support local tourism and business opportunities as well as to identify and fill gaps in public service establishments like hospitals, schools, public libraries, etc. Governments can comprehend neighborhood movements to see where families are suffering from insufficient resources and make the needed modifications.
The most important factors to test for quality in POI data are accuracy, scale (coverage width), and update frequency. As such, understanding the method of collection enables you to assess the data quality as every method has its advantages and disadvantages. Data that includes different sources better makes up for the disadvantages of different methods while taking on their advantages.
Finally, in addition to research on sources and collection methods, you should consider previous references and recommendations.
Your questions for data providers should follow quality testing factors such as:
ResearchGate: Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone
Science Direct: Identifying and evaluating poverty using multisource remote sensing and point of interest (POI) data: A case study of Chongqing, China
Google Maps is perhaps the most famous service which relies heavily on POI data. In August 2013, it was determined to be the world’s most popular app for smartphones, with “over 54 percent of global smartphone owners using [it] at least once in the month preceding the [GlobalWebIndex 2013] survey.”
Statista: Google Maps is the Most-Used Smartphone App in the World
Geospatial and geographic data make up the majority of Kadaster Data. However, attendant categories like land use, legal ownership, property, and even international development data also appear.
Premise Geospatial Data supports transportation, logistics, and other applications with millions of points of interest data worldwide
Physical Characteristics assists your business with problems that probably require you to understand what a building looks like, or what its key statistics are.