Location intelligence has a wide variety of use cases and can add rich context, accuracy, and depth to your research and business strategies. Increasingly, businesses are using human mobility insights and geospatial data for purposes other than targeted marketing and advertising. Nearly every day, a company approaches us for assistance with an issue that can only be resolved with the kind of big data we offer. Often, these cases impress us with their innovative uses of location data.

Our data occasionally confirms the findings of prior research projects, but more frequently, human movement data enriches and contextualizes earlier studies and other consumer datasets, giving us a richer understanding of consumer behavior and habits. Here are some of the most cutting-edge applications of location intelligence as examples.

Infrastructure and community planning are two of the most promising uses of location intelligence. People prefer to live in well-planned communities that include a mix of housing, employment, and recreational opportunities. What can city planners do to ensure their communities appeal to current and potential residents? How can they determine what working, shopping, dining, and playing options the ideal neighborhood needs?

Lake Nona, a forward-thinking master-planned community outside of Orlando, FL, recently used location intelligence to guide its next development phase. The community had thorough survey data from its residents but needed more information about visitors who came to the area for work, to shop, or to dine at one of the many stores and restaurants in the town center. Using human mobility data, Lake Nona could first differentiate between residents and visitors to the area by observing the data over time. Then, by analyzing only the data associated with visitors, Lake Nona could determine from where the visitors traveled and the types of businesses they frequented—both inside and outside the Lake Nona community. Lake Nona used this information to fine-tune its advertising outreach and commercial leasing strategy and lay the groundwork for future community programming that would appeal to residents and visitors in this vibrant community.

Learn more: Lake Nona Case Study

Did you know that location intelligence can provide insights to help boost local economies? Here’s how one organization accomplished this on the island of Nantucket, a popular summer vacation destination off the coast of Massachusetts. Nantucket’s economy relies heavily on tourism, and each incremental visitor contributes approximately $1,400 to the local economy during their stay. By making it easier for tourists to come and go from the island, Nantucket could bring in more visitors more often and grow its tourism-related revenue.

To fuel tourism, Nantucket Memorial Airport sought to expand air services but needed analysis and data to convince the airlines that increased services would be a good business decision. The research team used human mobility data to understand the routes travelers took to visit the island. The team quickly discovered tourists often took a combination of flights, ferries, and personal vehicles during their travels. With few options for direct flights, visitors had to take connecting flights to Nantucket or fly to larger airports in surrounding areas like Philadelphia, Pennsylvania, before completing their journeys via ferry and rental car. Using the results of this research, Nantucket Memorial Airport doubled its air capacity in less than 24 months and opened a new direct route from Philadelphia.

This new strategy increased efficiency, resulting in further investment and growth for Nantucket Memorial Airport.

Learn more: CDP & Nantucket Case Study

Thanks to human mobility analytics built on location data, researchers can better understand what happens when disaster strikes. Researchers can better understand human behavior at a scale that would have been nearly impossible without this data. How do people behave during wildfires, storms, or other natural disasters? Where do they go, when do they leave, and what routes do they take to get there? Researchers would once have relied on surveys for answers to these questions, but surveys are limited in sample size and subject to errors in consumer recall. When assisting rescue efforts and saving lives, getting the most accurate answers to these questions can make a world of difference.

In recent years, wildfires have become a growing threat to communities across the U.S.,  particularly in western states like California, Oregon, and Washington. Researchers at the University of Florida Transportation Institute recently used Gravy’s Observations data to understand how residents responded to evacuation orders during the 2019 Kincade Fire in Sonoma County, CA. In contrast to survey data, location data gave researchers the real-world insights they needed at scale to determine the number of residents that evacuated each day and the percentage of residents that evacuated both inside and outside mandatory evacuation zones. With these insights, researchers gained a better understanding of natural disaster evacuation behaviors, which could support more effective emergency management and help vulnerable communities prepare and mitigate risks in the future.

Learn more: University of Florida Transportation Institute Case Study

There’s no better way to understand how far people travel to access key services than through location intelligence. Businesses have always sought to get their goods and services in front of consumers with plenty of expendable income. Residents of affluent communities are also usually well-represented by their elected officials. Unfortunately, this is often not the case in our more vulnerable communities. Economically disadvantaged neighborhoods are often underserved when it comes to critical services like public transportation, medical care, and even food stores.

Mobility data lets researchers examine consumer movement en masse by calculating how far people travel, how fast they get there, and how long they stay at a place of interest. On the commercial front, it’s the same analysis techniques that you’d use to know where your customers are traveling from (so that, among other things, you can decide where to place more advertisements for your business) or to figure out where you should be building a new supermarket. But when used in community planning, it can help pinpoint the need for critical services like grocery stores, schools, or hospitals. In short, human mobility analytics can help to ensure that well-to-do communities aren’t inundated with options while working-class areas remain overlooked.

In 2018, the Office of Planning GIS published a polygon dataset of low food access areas in the District of Columbia. To learn more about these food deserts, our analysts examined consumer location data in the area to better understand food deserts and the behavior of residents of food deserts, such as how far they travel to reach a full-service grocery store. This is very relevant information for anyone planning to open a new business, or for established businesses that are looking to expand. Beyond commercial applications, local governments and city planning organizations can also use this information to guide long-term development.

Learn more: How Can Location Data Address the Issue of Food Deserts in the U.S.?

If there’s one thing we’ve learned from COVID-19, it’s that we were all woefully unprepared for a global pandemic. From initial shutdowns that brought the economy to a grinding halt to debates over social distancing and mask-wearing, COVID-19 forced a shift in our society. The coronavirus behaved in ways we’d never seen before and continues to pose new challenges with each subsequent mutation.

Early in the pandemic, scientists at the Johns Hopkins Whiting School of Engineering observed that most cases were concentrated in and around the biggest cities in the nation, including Seattle, New York, and San Francisco. Since population density and COVID-19 transmission are directly correlated, researchers investigated how transmission rates might change in a small town where consumer behavior and population density are very different.

The research team created a simulation model to show how the movement of people under various circumstances could affect COVID-19’s progression in a small community using human mobility data from a model town in the Midwest. The resulting simulation, dubbed Anytown, U.S.A., is now used to help people understand how a pandemic can spread in their community and how specific interventions and public health policies can make a difference.

Learn more: Johns Hopkins’ Anytown, U.S.A. Case Study

It seems like every business has a mobile app these days. Whether you’re running a high-end cruise line, a chain of 24-hour gyms, or a nationally known discount retail store brand, a branded app can enhance the customer experience. An app might share information about upcoming sales or new store openings in your area or provide contact information for your local store. Other apps might incorporate customer loyalty program features, such as coupons or discounts for frequent customers. The list of services supported through branded apps is ever-changing.

What do all of these features have in common? They require that app users share their location information with the app to create the best user experience. Consumer location data is necessary to host features that direct consumers to the right store and provide information about available inventory. Plus, when businesses have access to this type of consumer data, they can enrich it to glean more insights about their customer base. By working with a company like Gravy Analytics, for example, businesses can use the data they’ve already collected to better understand how far their customers travel, how frequently they visit, and which other businesses they stop at. You can also learn about your customers’ affinities and interests. Are they sports fans, foodies, or frequent shoppers? Businesses can use these customer personas to better inform their offers as well as improve their targeted marketing and advertising based on consumer interests.

The list of innovative uses for location data and human mobility insights continues to grow, so let us know if you’d like to learn more about location intelligence—our experts are ready to help. Schedule your no-obligation consultation today.