Comprehensive Location Intelligence Across the Globe
How High-Quality POI Data Supports GIS Navigation
Geographic information systems (GIS) have changed how companies from nearly every sector navigate the global market. These systems grant organizations increased competitive intelligence by enabling them to layer, map, manage, and analyze different types of data at the click of a button.
Among the greatest insights made possible by GIS platforms are those rooted in point of interest (POI) data. Having the right POI data is particularly important for two types of businesses: those that provide GIS navigation services (including Google Maps and Apple Maps) and those that leverage such services to make customers’ day-to-day lives easier (think Uber or DoorDash). But how?
In this article, we’ll answer this by first diving into how GIS mapping works. We’ll then discuss how accurate POI data helps companies increase customer satisfaction, avoid costly errors, and scale globally. Along the way, we’ll cover the true costs of bad GIS data and why dataplor is an industry-leading provider of location intelligence for GIS services of all kinds.
What is GIS?
GIS visually layers one or more datasets so that users can analyze each in isolation or together. In other words, GIS platforms link these layers to a map by combining location data with various forms of descriptive data.
These maps provide interactive business insights that raw data cannot generate on its own. GIS map layers allow organizations to see and toggle between different relationships, patterns, and geographic contexts found in their data. By analyzing GIS layers in this way, companies can unlock operational know-how and smarter decision making in real time.
How does location intelligence support GIS platforms?
Though they enable users to visualize more than one type of data, geographic information systems run primarily on location intelligence. This data is the backbone of GIS mapping, since it allows these systems to feature layers focused on specific geographic contexts.
For example, a GIS map could contain a polygon layer for France, an additional one for Paris, then yet another for popular tourist and shopping neighborhoods, such as the Champs Elysées or Marais. The same map might also contain additional layers that detail clusters for demographic skew for these sought-after destinations.
From a business standpoint, this GIS data is crucial for capturing market share. Through it, users are afforded granular insights about points of interest, including their addresses, hours of operation, websites, and phone numbers. As a result, companies can use GIS platforms that contain POI layers to boost competitive advantage, operational savings, and customer satisfaction.
To better understand this, let’s zoom out to consider what GIS providers themselves stand to gain with POI data. GIS mapping companies such as Apple Maps need up-to-date POI layers so that users can access and navigate their way to and from any point of interest, including restaurants, shops, parks, and other popular landmarks.
Imagine, for example, that a tourist using Apple Maps wants to visit a new streetwear brand’s flagship store on the Champs Elysées after a morning of site seeing around the Arc de Triomphe. If the platform has an accurate POI layer, they’ll be able to find reliable transportation to the store and arrive at a time that they know it to be open. Each experience like this leads to repeat use and supports consumer confidence in the GIS provider.
Companies that rely on GIS mapping and navigation also benefit from POI integration—so much that they’ll pay premiums for access to platforms that run on the right geospatial data. Remember our tourist? Hungry after a day of sightseeing and shopping, they decide to order from the hippest restaurant in the Marais using UberEats. Whether the app is relying entirely on another GIS or has integrated additional POI datasets to optimize its algorithms, customer satisfaction hinges on data accuracy: the courier will need the correct addresses, hours of operation, and phone numbers to make sure that the meal delivery is executed seamlessly.
What are the costs of bad GIS data?
Unfortunately, not all data is created equally. While free or out-of-the box data solutions might be less expensive, they’re often out-of-date and lead to unexpected spending down the line. POI datasets that are missing address details, contain inaccurate details about hours of operation, or suffer from duplicate records need to be enhanced if they’re to be reliably integrated into GIS platforms. And on top of all that, much international POI data is simply inaccurate.
The results can be disastrous when GIS platforms integrate bad data. Imagine that Apple Maps has the wrong Parisian arrondissement listed for the streetwear brick-and-mortar on the Champs Elysées or incorrect hours of operation for the restaurant in the Marais. Errors like these cost time, money, and have the potential to do irreparable damage to brand image and consumer confidence. For GIS providers or the companies that rely on their services, these consequences might also stifle efforts to expand globally.
Mapping international growth with dataplor
To avoid these costly errors, it’s important to only use POI data from vendors that 1) specialize in POI data, 2) streamline their places datasets using multiple sources, 3) provide metadata and other indicators for every record, and 4) know the value of local sources.
Thankfully, dataplor checks every one of these boxes. As an industry leader in location intelligence, we offer best-in-class POI data that GIS companies of all kinds can mobilize to gain truly global competitive intelligence. That’s because we use a winning combination of technology—including proprietary AI and machine learning—along with human verification to ensure that your mapping and navigation is always accurate.
Ready to take your GIS mapping to the next level with POI data? We’d love to hear from you!