The Comprehensive Location Data Knowledge Base
Location data, also known as geospatial data, refers to objects present in a geographic space.
Location data, also known as geospatial data, refers to objects present in a geographic space.
Welcome to Unacast’s Location Data Knowledge Base. This free library is collected from resources around the web and compiled for easy use. Use this page to get acquainted with the basics. The links and side navigation will help you to drill-down on different location data types, location data examples, location data providers, location data use cases by industry, and more.
Location data is a modern day natural resource in abundant supply. It is also cost effective, helps to improve decision making, and powers timely investments.
Geospatial technology and location intelligence span a broad expanse of the business landscape but the entire ecosystem is built on one thing: an exhaustless supply of quality location data. Fortunately, the world's location data reserves are loaded. Some types of data are even open sourced. Location data also has natural confluence with many other forms of big data. When one is used to augment the other, the resulting stream is a flow of real world insights that inform investment decisions, detect change sooner, and measure its effects.
Location data is the digital footprint produced by the movements of people and things in the physical world. As physical location can be gathered via IP address from a landline, location data in the form of GPS signals is gathered from common mobile devices. In legitimate markets, location data is collected with opt-in consent from users, aggregated and anonymized. Truly, it is only in this distilled form that the true commercial power of location data can be leveraged.
More than a series of positions and timestamps, location data represents human mobility, or how people move around the world to specific points of interest (POIs).
Location data is collected via mobile GPS pings that are aggregated and contextualized into meaningful insights, such as how many people visited a location and for how long (i.e., foot traffic data); the work and home locations of your visitors (i.e., trade area data); where else your customers shop (i.e., cross-visitation data, and where people are moving to and from (i.e., migration pattern data).
Location data commonly comes from mobile phones, beacons, Wi Fi, raster data (think: satellite images), connected vehicles, and other remote sensing devices that keep track of where people and things are. Once gathered and processed, this data can be studied through spatial analytics tools. Several such options exist, the most powerful being secure platforms crafted for large, first party data owners, such as telecommunications companies.
Location data in business has the power to dramatically improve strategic decision making, customer targeting and business operations. Unlike static data sets that only get reviewed once a quarter during KPI analysis, location data is often based on mobile location data and geolocation technologies such as GPS data, which can unlock enormous insights into customer behavior, departmental successes (or failures) and competitive opportunities. The only remaining question teams have is how to activate it.
No matter the vertical, there are three overarching location data use cases. Each use case covers a fair bit of ground in terms of variants and application. Let’s use the sticky note diagram below as a visual reference.
Within about two months of the start of Covid, we didn't need to rely on anecdotal evidence of urban exodus anymore -- it was in the data. Whole urban centers went dark, while smaller areas lit up for an increase in activity.
At the same time that Florida's southeast and the Miami area were going boom, San Francisco and the Bay Area went bust. Houston got hammered, but its surrounding counties built-up. All of this population movement carried serious economic consequences -- billions of dollars left cities and settled in suburbs or towns, reshuffling the economic landscape of America.
This created new foot traffic patterns in growing communities with evolving needs for public services and spaces. The human reshuffling also meant retailers and restaurateurs were flush with options for store location, reshuffling site selection processes for many real estate investment teams.
This brings us to another common use case for spatial analytics: using different types of location data to inform decision making around different types of investments.
From global banks using migration patterns data to increase return on assets, to insurers using location data to optimize profitability, geospatial analytics inform investment decision making every day.
Location data from GPS signals can be used in the rearview mirror - as in validating real estate investments - or to look ahead to what may be, as in predicting quarterly revenue based on current foot traffic patterns.
Location data and spatial analytics can also be augmented with other data streams to inform investment and business strategies of all types, including how to beat the competition.
Just like you can use geospatial data and analytics to understand your own business, you can also use it to improve what you know about the competition. This is of particular importance for enterprise retailers, restaurateurs, grocers, coffee shops and big box stores.
From a high level, KFC looks like it's whooping chicken butt most everywhere north of Louisiana. But zoom in with a geospatial data visualization tool and you'll see Popeyes is fiercely competitive in major urban markets across the map.
Target is the dominant big box nationally, but Costco has pockets of strength. Location data run through some geospatial analytics tells us that breaking through the Rockies would go a long way to solidifying Costco’s regional presence.
Kroger and Publix fight for much of the Great Lakes region and Atlantic seaboard but it is the urban markets of Georgia where the decisive battle may happen in 2023. All of this competitive intelligence was derived using raw foot traffic data and simple geospatial analytics tools to study the relative mobility patterns of each brand's visitors. This agility of application is why so many new products are being built from geospatial data resources.
Unacast’s Real World Graph can tell the whole story of human activity using just six different kinds of calculations. Our analytics team strategically correlates and sequences these calculations to help answer common and uncommon business questions.
How many people in your area visit your venue?
Where are your visitors coming from?
Where else do your visitors go?
How long do your visitors stay at your venue?
How many people are near your venue?
How many people spend time at your venue?
Get an edge on your competition with Unacast’s location data sets.
While latitudes and longitudes are the only raw ingredients, the products that can be cooked-up through geospatial analytics are endless. One of the more interesting use cases in early 2023 is how location data is being applied to create new products in the parametric insurance industry.
The traditional insurance industry relies on a manual claim event to trigger the payment process. One day, when the red tape has been hacked through, you hopefully get some kind of payout. But that reactive approach is not a formula that works in the wake of a natural disaster.
Enter parametric insurance -> quick, automatic payouts based on fixed thresholds, like the size of hailstones, or the wind speed of a hurricane. When the threshold is met, payment is triggered. The worse the event, the bigger the payout.
Cool 2023 evolution -> insurers are preparing new products for businesses that lose foot traffic temporarily or permanently because of a natural disaster. It’s a fascinating technical and business disruption at the right moment in time, and it's a good use of secure location and mobility data.
Fortune 500 insurers used a set of custom metrics to tie a through line between identified risk and the number of claims submitted. What’s more, they were able to confirm which times, days, and seasons were most likely to result in increased claims.
While location data is one piece of the puzzle, we believe that it paints a holistic picture helping us generate more accurate quotes.
Chief Underwriting Officer, Property and Casualty Insurer
Leading home builders identify income trends across regions, and select areas with prime growth opportunities to understand regional differences in behavior. Digging into residents’ behavioral patterns helps tie a through line across data sources spanning rural, urban, and suburban areas.
We believe we've set ourselves up for success to weather the pending storm regardless of its status as a recession or correction. We feel confident knowing we have the location data we need.
– Market Intelligence Director, National Home Building Company
Retailers use location data to improve the customer experience, increase sales, and understand competitors. Retailers also use location data to track customer movements in their stores and competitors' stores, identify popular products, and optimize store locations and layouts. Additionally, location data can be used to personalize marketing and promotional offers to customers based on their location.
"Location data is more important than ever because it takes data integration to the next level to account for evolving shopping habits and provide retailers the insights to adjust accordingly."
- VP Global Solutions, sensor company
Transportation: Location data is used in the transportation industry to improve efficiency and reduce costs. For example, transportation companies can use location data to optimize routes, reduce fuel consumption, and improve safety. Location data can also be used to track and manage assets, such as vehicles and cargo.
Emergency Services: Location data is used by emergency services to improve response times and save lives. For example, emergency responders can use location data to quickly and accurately locate the source of a 911 call, even if the caller is unable to provide their exact location. Location data can also be used to track the movements of emergency vehicles, improving coordination and communication.
Advertising and Marketing: Location data can be used by companies in advertising and marketing to reach their target audience and personalize their messaging. Advertisers can use location data to track the movement of potential customers and target them with relevant ads or offers. Additionally, location data can be used to track the effectiveness of ad campaigns and optimize them for better results.
Safety and Security: Location data can be used by governments, law enforcement agencies, and private companies to improve safety and security. For example, location data can be used to track the movements of individuals and detect patterns that may indicate criminal activity. Additionally, location data can be used to monitor critical infrastructure and detect potential security threats.
Learn how to leverage custom location data sets to power best-in-class decision making!
There are a number of options to connect geospatial databases to geospatial tools, including solutions for data processing, data analysis and the very important data visualization aspect. ArcGIS Pro from Esri is a powerful GIS software that lets you explore, visualize, and analyze data, create 2D maps and 3D scenes, and share your work online.
Another powerful geospatial solution is CARTO, a location intelligence platform used to optimize and predict future outcomes through the power of geospatial data science. One other category of geospatial tools worth mentioning is in-house processing for first party location data owners, such as telecommunications companies.
In this highly regulated market, privacy-friendly solutions are a must. For first party data owners such as telecommunications companies then, it is worth consulting a category leader such as Turbine, which turns raw location data into valuable, privacy-friendly, human mobility insights, at scale.
While Accuracy and Precision sound like the same thing, in the world of location data, there is a subtle distinction: Accuracy means how close a measured location is to the device that’s pinged. whereas Precision means how close a number of separate pings are.
Quality location data is rich in both the temporal and spatial sense. That is, it provides accurate detail of both time and place, and it can be combined with other data and aggregated at-scale.
Telcos are really the gold standard stewards of first party data. They have the greatest volume of data and it is rich in both the temporal and spatial sense. Telco is arguably the most privacy-friendly industry to begin with also, both by design and regulatory requirement.
Various techniques are used to increase the reliability of insights, including supply correction, bias correction, and extrapolation. Without these, users may end up with phantom fluctuations that skew the location data sets and result in inaccurate human mobility insights.
Unacast gathers aggregated GPS data from +130m smartphones and mobile apps, with opt-in consent from users.*
As we only capture a share of the US population, we need to extrapolate our data to more accurately represent the total US population.
Supply fluctuations occur commonly in the location data industry so it is important to distinguish between trends (peaks and troughs) that are naturally occurring versus a result of changes in supply.
Correlation can get tricky — depending on which method you choose, you can make data say anything you want. But you want to make sure that the data is telling you the truth, not just what you want to hear. Unacast deploys a team of data scientists to make sure that our data is high-quality and reflects real-world events; and to make sure that the deliverable enables our clients’ specific use cases. We work hard to understand which problems our clients are trying to solve, which questions they’re trying to answer, and which audiences they’re trying to reach before we propose specific solutions.
Iteration is the best path to quality. We regularly compare our products to third-party or independent sources to identify where improvements can be made. Unacast employs truth sets such as the number of devices that were connected to a venue’s wifi as a proxy for visits. To learn more, check out this Ground Truth Analysis of Foot Traffic.
The most accurate database of global points of interest, curated to power the most innovative applications, platforms, and analytics. Develop the best products and insights with places data that reflects the changing world, with SafeGraph. Millions of global points of interest (POI) with detailed attributes, such as brand affiliation, advanced category tagging, open hours, and more.
Goodbye Gut Feel, Hello Location Intelligence. Build better products and make smarter decisions with real-world location data. Our clients leverage our products to enhance their decision making and strategies around competitive intelligence, investment decisions, forecasting, and market analysis. This allows our customers to move beyond device-level data, eliminating internal data processing challenges and data privacy risks, to solve real-world challenges with location data.
Find out why best in class companies partner with Unacast for their location data needs.
ArcGIS offers unique capabilities and flexible licensing for applying location-based analytics to your business practices. Gain greater insights using contextual tools to visualize and analyze your data. Collaborate and share via maps, apps, dashboards and reports. Use location as the connective thread to uncover hidden patterns, improve predictive modeling, and create a competitive edge.
Turn raw location data into valuable, privacy-friendly, human mobility insights, at scale. Unacast’s location processing platform - Turbine enables clients to harness the power of their own location data via Unacast's data processing platform. You already own the data. We’ll help you safely monetise it. Extract value from your data sets without having to release it into an unrestricted environment and Accelerate beyond your internal capabilities and quickly iterate on new functionality.
Let the experts at Unacast help you leverage your valuable data with the Turbine first party data platform.
Spatial analytics for the modern data stack. Go beyond asking where things happen to know why they happen there. Location data & geospatial analysis is no longer “something those GIS people do”, it's a core capability of modern Data Science and Analytics teams. The only Location Intelligence platform to offer cloud-native, self-hosted, and hybrid deployments - accommodating the needs of the modern data & GIS professional.
You may picture a “final product” or envision a spy movie where every human is a moving dot. But location information is sourced from existing information systems.
Many people never consider this, but the entire world is mapped. Cities, mountains, roads, bodies of water, highways, byways: all of it is recorded in geographic information systems. This raw data is then represented by two types of location data:
All of these simply provide ways of seeing data, and are often delivered via location intelligence software.
Location based analytics are the outcome of successfully collected location data. Here is an illustration of what this kind of analysis could look like: A measurement of hardware stores in New York, ranked by foot traffic recovery, estimated the following gains and losses year to date (as of April 21, 2021):
An example like this underscores the value of hard facts. Whereas owners of smaller hardware stores may not take the time to analyze big brand competitors, foot traffic gains and losses immediately indicate the success of some mid-sized brands, even against national competitors. Facts tell the right story, and one which can be used to make real decisions.
Harbor Freight Tools
21.1% Foot Traffic Gain Loss
True Value Hardware
19.9% Foot Traffic Gain Loss
Ace Hardware
18.9% Foot Traffic Gain Loss
Do It Best
17.2% Foot Traffic Gain Loss
Surplus Warehouse
17.1% Foot Traffic Gain Loss
Lowe's
9.1% Foot Traffic Gain Loss
The Home Depot
9% Foot Traffic Gain Loss
You may have some questions about location data. We have answers:
An individual's location data can be extracted from their mobile devices by many of the apps they use daily. We understand that the privacy of personal data is incredibly influential on consumers' purchasing decisions.
Unacast passionately believes every consumer deserves the right to maintain control over how their data is captured, stored and used. That's what we consider privacy-friendly data-information obtained with explicit consent from its owner. Just as experts predicted, consumers will always favor privacy-friendly companies with transparent data privacy policies.
We gather data from millions of smart phones across the United States and beyond. We never collect or store any personal data without your explicit, opt-in consent. This ensures the confidentiality of user identity and personal information at all times.
We aggregate mobility data up to the census tract level for the most accurate data possible. This helps to produce actionable insights that drive smarter decisions for a range of governmental, corporate and private organizations.
Location intelligence also helps a business understand migration patterns within specific neighborhoods, across state lines and in the country as a whole.
Reduced incoming migration negatively impacts foot traffic. The more densely populated or heavily trafficked an area is, the more noticeable the reduction. Reduced foot traffic limits opportunities for retailers and restaurateurs, leading to store closures and increased unemployment rates.
For example, reduced mobility poses a challenge for CRE investors and operators because it lowers current and forecasted lease rates. With fewer people in a given area, the need for infrastructure drops. Fortunately, you can use location data for risk assessment, reducing the magnitude of that challenge.
Increased incoming migration boosts foot traffic. Since COVID-19 began, populations and foot traffic ratios in smaller cities and towns are rising. This is most likely due to a perception of safety in less densely populated areas. This inflow is often composed of former urbanites who relocate or temporarily resettle outside urban centers.
