Every time someone opens a maps app to search for restaurants, a list of names, addresses, opening hours, reviews, and directions appears on the screen. That instant, seamless experience happens because of Point of Interest data, or location data. Collected from sources like business listings, GPS signals, and user contributions, POI data transforms real-world locations into structured, searchable digital information. And it’s not just for navigation because the same data that helps users find places also helps businesses make smarter decisions.
Every point of interest is packed with attributes that, when analyzed together, reveal meaningful patterns about consumer behavior, market trends, and geographic demand. This guide will be your POI handbook because we will tell you all about
- What is Point of Interest data, and how is it defined?
- Main attributes that define a POI dataset
- Reasons why POI data is valuable and how it’s used
- Overview of the top providers offering POI data today
So, let’s first get started with the basics.
What is a POI data?
POI stands for Point of Interest data, and it refers to details about specific physical geolocations that people may find useful or meaningful. They can include restaurants, schools, gas stations, hospitals, parks, and retail stores. These points of interest are basically used by businesses to understand market patterns, gain POI-based insights, and perform geospatial analysis to make data-backed decisions. Each point of interest is tied to key attributes that add deeper context to it.
What is a POI data attribute?
POI data that is high in quality has numerous descriptive and spatial attributes that add context and usability. Point of interest attributes include,
- Name: Business or location name (e.g., “Starbucks”)
- Category: Type of POI (e.g., Café, Retail Store)
- Address: Full street address
- Latitude/Longitude: Geolocation coordinates
- Phone Number: Contact details
- Opening Hours: Business hours (e.g., 9 AM – 5 PM)
- Website URL: Link to business site or social media
- Brand Affiliation: Whether the POI is part of a franchise or chain
Point of Interest data also includes additional details such as amenities, customer ratings, historical status, and various other contextual information. Special geospatial features like these can also be requested from location data providers based on your specific needs.
Also, these POI attributes are usually delivered in a structured data schema (like JSON or CSV), making them easy to integrate into your applications or analytics workflows. The schema makes sure the POI dataset maintains consistency, clarity, and usability across different systems and use cases.
What are the examples of POI data?
Here are some real-world examples to get a deeper understanding.
What are the important use cases of POI data?
Location-based insights derived from Point of Interest (POI) data or place-based metadata play an important role across a wide range of sectors. But dynamic POI data, which captures key attributes and contextual details about physical sites, gives far more insights than what we call static data.
Now, what is static data? Static is fixed or unchanging information. For example, a place’s name, address, or category (like “restaurant” or “museum”). While helpful, static data alone can’t tell you everything.
On the other hand, dynamic data refers to constantly changing details such as whether a place is currently open, how crowded it is, what its latest customer ratings are, or if it has any ongoing promotions. These attributes are especially valuable for real-time decision-making in navigation apps, delivery services, and marketing.
All of these services rely on up-to-the-minute information to function effectively. That’s why Point of Interest data often combines both static and dynamic attributes for maximum utility. Here are some impactful use cases where POI intelligence drives real-world decisions and digital experiences.
1. Local search & maps:
Some businesses, like tourism agencies, use navigation apps and rely on location data to keep their databases up to date. For example, a marina navigation app can add POIs like docks, fuel stations, and repair spots. This helps users find nearby places, making it easier and safer for boating and water sports lovers to find what they need while out on the water.
2. Retail & site selection:
Brands use location data to find optimal store locations based on proximity to competitors and neighborhood demographics. They do this by analyzing surrounding businesses and population patterns to identify high-potential areas.
3. Logistics & delivery:
Logistics companies make use of location data to optimize delivery routes and maintain last-mile accuracy. Point of interest data also helps them map precise drop-off points, serviceable zones, road access constraints, and peak delivery times.
4. Urban planning:
Cities and municipalities analyze POI data to plan infrastructure, zoning, and community services. They also study the distribution of amenities like schools, hospitals, and transit hubs to identify gaps and prioritize development, with the help of POI data.
5. Market analysis:
Analysts use POI data to evaluate business clusters, accessibility to essential services, and shifts in retail or service presence over time to gain insights. This helps them to better understand geographic trends, competition positions, and customer behavior.
What are the types of POI data?
POI data is categorized in a variety of ways, each specialized for different use cases and industries. If you are using it for developing a location-based app or analyzing consumer behavior, understanding the various types of POI datasets is essential for making use of their full potential. Here are some common Point of Interest types.
How is POI data collected?
Businesses open and close daily, change addresses, and update hours. So, the location data collected can easily become stale. Stale data can lead to poor decisions and user experiences. Therefore, collecting accurate POI based data is not an easy process because it involves multiple sources and quality checks. Here are some methods for collecting POI data before they are validated.
- Web scraping is a method used to automatically extract POI based data from websites. The location data is automatically pulled from public websites or online directories. It’s a fast way to gather lots of information that’s already out there.
- APIs are tools that allow software to communicate with location data providers. APIs like Google Places let you fetch Point of Interest data directly from trusted sources.
- Manual surveying is a field-based method where teams sometimes go out in the field to confirm locations manually. It is a time-consuming process, but it can be very accurate.
- Business listings are official submissions about a company. The company details are submitted to online platforms such as Yelp, Google My Business, or Yellow Pages. POI attributes are extracted from these listings, and this type of listing makes sure the info is up-to-date and straight from the source.
- Crowdsourcing is a community-driven data-gathering process that helps keep maps and apps up to date by adding or updating places. This real-time input from users makes sure that location info stays fresh and current. Also, a bit of moderation will be needed to keep it accurate.
What is a POI database?
A POI database is basically an organized collection of points of interest. They are usually stored in tables or geospatial formats like GeoJSON, Shapefile (.shp), etc. It contains not only the location coordinates but also metadata (POI attributes) that make it meaningful.
For example, in a navigation app, a POI database might include millions of places from all over the world. They’re sorted into categories, tagged with exact GPS coordinates, and can be searched by area or what’s nearby. This makes it easy to find what you’re looking for. Here’s what typically constitutes a POI database.
Defines what kind of details each place should have, like its name, category, address, or contact info. A clean and consistent schema makes the POI based data easier to use and integrate into different apps or tools.
This is how physical addresses are converted into geographic coordinates (latitude and longitude). Also, accurate geocoding lets businesses map store locations, analyze spatial relationships, calculate distances, and derive location-based insights.
Regularly refreshed Point of Interest data makes sure business information stays accurate and visible on navigation apps and maps. Periodically updating POI data keeps it current and reliable in dynamic environments.
This is the behind-the-scenes info that gives context, like the source of the location data (e.g., scraped from a website, submitted by a business), timestamp (when it was last updated), and confidence scores (how reliable or verified each data point is). This information is important, as it assesses trustworthiness and relevance.
What to look for in a POI data provider?
Accuracy and coverage remain the most critical factors when evaluating a POI data provider. Since international data collection often lacks consistency, verification and manual validation are essential steps that cannot be overlooked. These processes help prevent misdirected users or deliveries and ensure that the dataset fully represents all intended regions. The key question then becomes, what qualities should a Point of Interest data provider have to deliver both accuracy and comprehensive coverage?
1. Freshness:
Is the location data up to date? Not all providers refresh the data. Every day, some POI attribute keeps changing, and so to keep things up to date, we need to at least refresh data once a month.
2. Attribute Depth:
Some companies have the point of interest that they need, but the attribute depth is missed. Businesses need in-depth attributes because more metadata means better analysis and usability.
3. Ease of Integration:
Just providing the POI based data in a particular format does not suffice. It should be convertible to formats that can integrate with your current app.
4. Support & Documentation:
Good documentation should include details on schema, update frequency, integration steps, and sample queries. It helps by giving teams clear, accessible answers about the dataset’s structure, usage, and limitations, so they can work efficiently without repeated clarifications. This speeds up onboarding, reduces errors, and helps your staff make better, faster decisions.
Top 8 Point of Interest data providers
Here is a roundup of the top POI data providers, commonly known as location data sources, mapping data partners, or geospatial info experts, to help you choose the best fit for your business.
1. Xtract.io
Xtract.io offers millions of POIs across categories, and many are manually drawn for accuracy. Their datasets are refreshed every 30, 60, or 90 days, depending on your needs. It’s a great choice for use cases like site selection, competitor mapping, or location intelligence. Not only that, it’s fully customizable and delivered in the format you prefer.
2. SafeGraph
SafeGraph delivers clean, precise location data for over 40M+ locations. They update monthly and include rich attributes. Nearly half the entries also come with building footprints and spatial hierarchy, which is great for advanced geospatial analysis.
3. Foursquare
Foursquare pulls from its own apps, using check-ins and user contributions to keep POI information fresh. It has strong global coverage, but accuracy and completeness can vary depending on the region.
4. Precisely
Precisely provides granular POI classification and building footprints. It’s a solid choice if you’re combining point of interest data with other datasets. Please note that it may include duplicates and lack hierarchical data. Also, it’s one of the pricier options.
5. HERE Technologies
With a massive database of over 120 million POI based data, HERE makes it easy to find and filter places, even along a travel route. It’s especially useful for navigation, fleet management, and logistics apps.
6. TomTom
TomTom offers wide point of interest coverage and useful location attributes at competitive prices. One catch is that the coordinates are based on addresses, not always exact building locations. So it may not be precise enough for all use cases.
7. Google Places
Google’s Places API is packed with information, such as place names, photos, business hours, and user reviews. It’s one of the most complete and trusted sources out there, but it can get expensive, and usage comes with strict limitations.
8. OpenStreetMap (OSM)
OSM is a great free resource, but as it’s community-driven, quality can vary, and working with the data takes some technical skill (and attention to licensing). But if you know what you’re doing, it’s a fantastic resource.
Common FAQs about POI data
What are the point of interest data representation techniques?
POIs are usually represented as points (latitude/longitude), often within GIS systems or vector maps. Some use polygons for large venues like malls or stadiums.
What’s the difference between a POI and a geofence?
A point of interest is the location itself. A geofence is a virtual boundary set around an area for analytics or triggering actions.
What is a POI dataset?
A POI dataset is a structured collection of multiple POIs, typically including POI attributes like,
- Name of the place
- Address
- Coordinates (latitude & longitude)
- Category/type (e.g., restaurant, bank, clinic)
- Opening hours
- Ratings or popularity metrics
Why does POI data deserve your attention?
If you are looking for delivery accuracy or want to improve customer insights, Point of Interest data is foundational for businesses that operate in physical space. Also, to build an app, analyze market trends, or choose your next store location, high-quality POI data gives you the competitive edge.
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