More companies than ever before are generating location data as a by product of their business operations. Today, location-enabled mobile applications are most often the source of this location data. Many mobile applications capture their users’ location data in order to provide a service that requires location information, such as local weather reports, sports scores, news headlines, dating profiles, or driving directions. It’s also necessary for apps to collect their users’ location information to provide app users with more relevant in-app advertising.

But while many companies are already collecting a wealth of location information during their normal course of business, most of them are still not making the most of this type of first party data. There is a wealth of derivative information just waiting to be gleaned from raw location data. This derivative data can, in turn, be used by your organization to improve marketing programs, streamline business operations, and even shape your business strategy. 

By enriching your company’s raw location data, it is possible to generate new data and analytics that can be used in myriad ways. Here are just a few examples of what you can do.

Location data can reveal the real-world behavior of your customers. This includes the stores they shop at, the restaurants they dine at, and the places they go to see a show or watch a movie. You can understand how far they travel to visit one of your stores, how long they stay, and how frequently they return. You can also derive information about the type of mobile device, browser, or internet connection used. You can even discover which of your customers are most loyal to your brand and which are more likely to visit a competitor. And this is just the start.

Speaking of competitors, location data is an ideal way to understand how your business compares to the competition. Not only can you benchmark customer loyalty, but you can also produce location analytics to understand how your business compares in terms of foot traffic volume, distance traveled, time on site, and more. How does your foot traffic compare by the time of day or day of the week? What share of visits does your company earn in each market? What types of customers do you attract? All of these questions and more can be answered through location analytics.

When you understand the types of places that your customers are apt to go to, you can get a pretty good idea of their interests and habits. Once you’ve identified those interests, you can begin to understand how your customers are similar or different and categorize them into buyer personas. You might discover, for example, that 45% of your customers are probably parents of school-age children; that 32% of your customers are avid exercisers; and that 28% are in the midst of vacation planning. This information can then be appended to customer data in your CRM system and used to customize your marketing messages going forward.

Once you’ve uncovered the places your customers visit and discovered their buyer personas, you might find some new marketing opportunities that you didn’t quite expect. For example, you might learn that 54% of your customer base are live music fans. This might give you the insight you need to decide to sponsor a music festival or partner with local music venues to promote your product or service. Similarly, an athletic clothing manufacturer might discover that its customer base of exercise enthusiasts overwhelmingly visits Hilton-brand hotels. The clothing manufacturer might then approach the hotel chain to revamp its onsite boutiques and feature the brand’s athletic wear.

Perhaps most importantly, processing your raw location data will help to ensure data quality. This is particularly important when you plan to use location-based insights to make important business decisions. Raw location data is rife with problematic signals. If you are already using raw location data for decision-making purposes, understand that many of those signals may be leading your analysis astray. When you process your location data, you can reliably remove both fraudulent devices and signals. You can also filter out valid data that may be lower in quality or from a moving device if it is not relevant to your analysis. By processing your location data, you can work with the resulting insights far more confidently.

It should be mentioned that raw location data is generated not only by apps but in other ways, too. WiFi networks, beacons, drones, autonomous vehicles, and IoT devices are all examples of sources of location data. Each of these sources produces raw location data that can be processed for unique insights. Today’s businesses are sitting on a wealth of location data that can be used for competitive advantage and to help shape your business operations for years to come.

For more information about data enrichment, contact one of our location data experts today.