What's In the Building Accurate Consumer Segments with Offline World Data Whitepaper?
As the boundaries between the online and the offline world blur, businesses today are looking for information about places and consumer behavior at those places to drive effective marketing.
This paper highlights how Near’s Staypoint Algorithm solves the performance and accuracy issues by automatically classifying location pings for the device user is stationary or mobile. The algorithm can work in real-time or batch depending on the use case. We use this foundational data science model to enable our flagship product Allspark, where we retain useful location-based information and provide characteristic insights on individual behavior in the real-world.