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 (Geographic Information Systems) visually layers multiple datasets onto a map, letting users analyze location-based data in isolation or together to uncover patterns and support smarter decisions.

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 data rows cannot generate on their 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?

Location intelligence is the backbone of GIS mapping. It powers the layered, geography-specific views (like POI details, demographics, or boundaries) that let businesses turn raw location data into competitive insight.

Though they enable users to visualize more than one type of data, geographic information systems run primarily on location intelligence.

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.   

Why does POI quality matter for navigation?

Navigation and delivery apps depend on accurate POI data—addresses, hours, and phone numbers—to guide users correctly. Even small errors can break the experience and cost providers real revenue, as seen in Uber paying Google millions annually for reliable map data.

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?

Bad GIS data—missing addresses, wrong hours, duplicate records—leads to failed deliveries, wasted time, and lasting damage to brand trust, especially when scaling into new international markets.

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.

Errors can increase operational costs 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, we check 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.

Key Takeaways

• Why POI quality matters: GIS platforms run on location intelligence, and accurate POI data (addresses, hours, phone numbers) is what lets navigation and delivery apps guide users correctly and keep them coming back.
• Primary risks of bad data: Missing address details, incorrect hours of operation, and duplicate records lead to failed deliveries, wasted time, and lasting damage to brand trust and consumer confidence, especially when scaling internationally.
• Vendor selection checklist: Look for providers that (1) specialize specifically in POI data, (2) source from multiple streams rather than one feed, (3) provide metadata and indicators for every record, and (4) draw on local, on-the-ground sources for accuracy.
• How Dataplor addresses this: We combine proprietary AI and machine learning with human verification, checking all four vendor criteria above to deliver globally accurate, reliable POI data for GIS mapping and navigation.

Ready to take your GIS mapping to the next level with POI data? Contact us.