How Can Your Business Benefit From Geospatial Data?

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Gain valuable insights by leveraging this lesser-known data

Mobile devices have made it much easier and more convenient to interact with digital platforms remotely. It means that with a smartphone you can access any website or service no matter where you are — even hundreds of miles away from a conventional source.

Regarding digital content and data, mobile has also transformed the way the enterprise world collects and understands information about customers. It comes with several new details. Many deal with the location or positioning of an individual and what that means.

Generally, any data that includes location information is called geospatial data. The most common way to collect this info is via mobile devices and their reporting solutions. However, it can also be obtained by sensors, GPS devices and beacons — wireless Bluetooth transmitters.

The information can be related to an individual’s home or business address, their current location, their travel route, local stores or points of interest, and much more.

As with most forms of analytics, geospatial — an element of big data solutions — deals expressly with the collection, processing and application of said content. It’s often overlooked when businesses consider what forms of data they will collect and use regarding their audience. This is unfortunate, because it can be incredibly valuable.

To understand the inherent value of geospatial data, however, you must first learn how it can be leveraged and what benefits it offers.

What Is Geospatial Data and Why Does It Matter?

The first thing to understand is that even though geographic information systems (GIS) and geospatial data are used interchangeably, they are different. GIS refers to the methods used to collect, process, analyze and manipulate geospatial data. The information itself, on the other hand, pertains only to the term.

Geospatial is commonly used when information contains a geographic component or location details. GPS data, satellite imagery, and geotagging systems all factor into geospatial content. It’s also important to remember that any location data can be included, such as addresses, zip and shipping codes, city or country details, and much more. If and when a customer provides their home address, for example, that’s one form of geospatial data.

Besides the obvious uses for such information — like being able to ship products or goods directly to a customer’s home — there are other ways this data can be used. This is especially true if it’s analyzed using advanced tools.

As Deloitte explains, businesses today can “add the context of timing and location to traditional data, creating maps that show changes over time and exactly where those changes are taking place.”

Like conventional data visualizations, “maps make it easier for the eye to recognize patterns that were previously buried in spreadsheets, such as distance, proximity, contiguity and affiliation.”

That’s a more involved way of saying geotagged information can present an added layer of context, on top of conventional understandings. Not only could a business see what stores and locations a particular customer is shopping at, but also where they might go in the future simply by considering local insights.

More importantly, it helps to elevate digital databases and information to new heights. Where once you had a relatively straightforward series of details about operations, sales, customers and more, now there’s a geographic component to it. You can see why sales are higher in an area, perhaps due to local shortages. You can see why customers prefer one store over another. You can even discern ways to tap into new demographics or customer bases using existing geospatial information.

Available Now More Than Ever

In addition to the fact that geospatial content provides many new insights and opportunities, it’s also available abundantly thanks to mobile and data-centric technologies.

About 80 percent of enterprises have some form of location data, whether it’s addresses, zip codes or something else. Geospatial analysis can be used to delve deeper into the nuances of this information, to do things like identify valid placement for a new shop or warehouse.

Geo-based technologies are already used heavily by most businesses today. Modern transport fleets are likely outfitted with not just GPS and real-time location devices, but also data reporting sensors that can be used to cross-reference a variety of statistics and information. On top of that, the drivers have their own mobile devices that are reporting completely different sets of data. This combined information can be used to learn a great deal about the entire operation, from transport and travel times to surrounding conditions and potential problems. This is how many distributors manage their supply routes.

That is merely one aspect of modern business dealing particularly with logistics. The same technologies can be applied to a swath of applications and processes, effectively creating smarter more efficient operations.

Geospatial data plays a role in nearly every industry, from retail and manufacturing to military and medical.

It’s also important not to overlook the effectiveness, accuracy and usability of said data thanks to modern technologies. It’s not just that information is more abundant than ever, but also that we have many more tools to analyze, process and extract actionable insights.

Machine learning solutions — an offshoot of AI — can be fed incredibly large content stores to analyze, identify and create usable segments of information. This is all done through automated processes with little to no human input.

One provider named HOT, for instance, is using machine learning to help alleviate the complexities of mapping local areas.

Make Geospatial Data Work for You

Collectively, we are merely scratching the surface in terms of what geospatial data can be used for. However, the best place to start is to understand what information is available, compared to what’s needed to move forward. If you’re looking to proceed, the first step is to audit existing data streams to identify incoming geospatial content and go from there.