Home » Gain New Intelligence About Consumers Based on an Accurate Dataset of Real-World Places That Matter
Gain New Intelligence About Consumers Based on an Accurate Dataset of Real-World Places That Matter
September 28, 2018
There’s that hot new corner coffee shop where all the in-crowd gathers. Or, maybe you’ve heard about the wildly popular upscale retail store selling all those gotta-have holiday cocktail dresses. Then there’s the must-see exhibit at the city’s most visited museum. All of these locations have something in common. They’re bona-fide Points of Interest (POIs) where heavy foot traffic is almost guaranteed.
There’s been a growing demand for Point-of-Interest (POI) data in today’s highly mobile marketplace where companies are starved for any type of reliable intelligence that could give them a competitive advantage in terms of engaging with consumers in real time. While marketers have long recognized the value of knowing consumers’ geographic locations, they are coming to realize how other geo-contextual data points can accentuate and extend their marketing efforts. Utilizing IP-to-POI datasets can help marketers identify consumers in the immediate vicinity of nearby points of interest such as retail stores, restaurants, gas stations, hospitals, churches, etc.
We’ve written a lot over the years about how geo-textual data and proximity intelligence will be integral for more personalized “human” marketing, especially in today’s highly mobile society. Understanding customers’ context around their current location helps in delivering more relevant, timely messages as a result. Location is especially powerful when it’s combined with an awareness of what customers see as important and what information they value receiving at different points in time. The success of online marketing will come for those brands that capitalize on customer engagement in real-time, using a highly context-based targeting approach to deliver information, merchandise and/or promotions that are appealing and valuable to customers in a particular moment.
Digital Element pricing is based on two variables: data requested and estimated monthly volumes. Please contact us so that we can learn more about your specific needs.