Companies embarking upon digital transformation strategies are spending billions to ensure that customers have positive experiences across their digital platforms, including websites and mobile apps. But some of the most advanced companies are also finding creative ways to apply real-time location data into their decision-making processes, providing an even richer view of potential customers across physical and digital realms.
We’re in the beginning of a new age when it comes to geo-location data. Thanks to the ubiquity of smart phones and the growing presence of IoT devices, businesses are able to capitalize on streams of data flowing from apps and sensors. The smartest companies are figuring out how to leverage these streams of location data to maximize revenue and profitability of products and services.
Starbucks is one of these forward-looking companies engaging with location analytics. When a consumer is using an application has location services turned on – such as through Facebook or Twitter – they can be targeted by Starbucks to receive a discount when they enter a geo-fenced boundary around a particular Starbucks location.
Two leaders in this emerging field are Pitney Bowes and Dun & Bradstreet, which collectively have more than 270 years of experience with collecting, aggregating, and re-selling data to businesses. As the technology has improved, the potential uses for location data have expanded too, executives with the two companies tell Datanami.
According to Rob Minaglia, vice president of OEM sales for Pitney Bowes, D&B is critical for providing context around the basic location data — usually expressed as a latitude and longitude position — that’s collected and validated by Pitney Bowes. “Lot/Lon doesn’t tell you anything, so you want to match that data to a business or other category,” Minaglia says. “You typically want to enrich it, and that’s our partnership with D&B.”
A retailer could work with Pitney Bowes to take validated location data and then have it enriched via pre-built connections into the D&B database of business information. That essentially allows the Pitney Bowes customer to match a place to a person — for instance a mobile subscriber who’s just a block away from a coffee shop.
“We use that information to enable journey mapping, geo-fencing, attribution, in the moment targeting — services like that which are provided by companies who purchase our data and software,” Minaglia says. “We provide the fundamental element to convert location as defined by a lat/long into the intelligence in order to take those kinds of actions.”
Pitney Bowes and D&B buy and sell their respective location data and services to each other, and offer customers pre-built hooks into the others data services in such a way that it’s a seamless experience no matter which company you deal with. Customers could try to build their own location intelligence system, but unless you’re a Web giant, you’re probably better off tapping into the location data systems that others have built, says Anudit Vikram, D&B senior vice president and chief product officer of Audience Solutions.
“Any single business or single entity trying to do this on their own, it would be extremely difficult for them to do that. At the very minimum, you need to be able to have access to a footprint that’s large enough and represents a portion of the population that would be representative of the people you’re trying to reach,” Vikram says. “Most brands or most organizations have a very small view of the universe, which is their own view.”
Location data is not all about texting ads for discounted lattes or finding the closest pizza joint. As Vikram explains, getting insight into the demographic makeup of a neighborhood could help a growing retailer generate higher revenues.
“Let’s say that you are a retail business and you’re planning to open up a new store and you want to know what would be the potential traffic that you’d be able to get into that store. What’s the risk profile or the actual biz profile of the area where your store is going to open?” Vikram asks.
“Working with us and with Pitney, we’re able to identify other businesses in that same area,” he continues. “We’re able to identify the time it would take somebody from a highly populated downtown areas or certain other geographic area to reach that store. And therefore you’re able to use that location intelligence we provide, as well as the demographic, psychographic, and technograhic information that we have available about businesses and people at business in that location to then help the retail business make decision on what kind of a footprint should we have, when should the store be open, and what kinds of output we should expect from that store.”
Companies are finding new ways to use location data that weren’t widely available just a few years ago, Minaglia says. “The tools and capabilities have evolved to the point where they can be consumed by business analysts and business people,” he said. “You see that with BI products from Cognos, Tableau, and others, which have excellent geospatial capabilities, in some cases using our data inside to render that.
“The second reason is that the technology has evolved to the point where you can rapidly and very cost effectively enrich geo-enabled applications with your data and third party data to do machine learning, to do modeling, to do predictions,” he continues. “Those two factors in parallel have been important accelerators.”
While companies focus on digital transformation initiatives to maximize their footprint in cyberspace, the advent of new location analytics techniques can help them make the most out of their physical presence, too.
“The more information you can string tougher about their physical behavior, where a person is, their digital behavior, what they’re accessing, and the context surrounding the place that they’re in,” Minaglia says, “the more relevant, engaging and personalized that experience will be, whether it’s through a recommendation app like Yelp or an advertisement or some other localized experience on an app.”