Viral geofencing: An exploration of emerging big-data driven direct digital marketing services

This paper explores approaches for the effective integration of several focal areas of advanced analytics on currently achievable big data platforms to enable timely, and maximally effective, geofence-triggered interventions (push marketing) that leverages viral or exponential returns. The viral or exponential growth behavior of modern social media-based interactions has garnered much attention in both public and private circles. The potential for harnessing and controlling these epidemic-like dynamics of spread or diffusion represent a significant and, as yet, underdeveloped marketing approach. This is especially true in the context of geo-fencing strategies and designs. Despite the potential for highly-leveraged returns for location-based services (LBS) several barriers remain. Due to privacy concerns, legal issues, the immaturity of big analytics, and constraints presented by physical-level communications and geo-tracking enabling technology, LBS has remained underdeveloped and under-actualized. This reality is rapidly changing. This paper focuses on recent developments in big analytics, especially the integration of social networking dynamics, text mining, semantics, dynamic behavioral profiling, and real-time trigger-based geo-sensing capabilities that are enabling the next generation of high performance direct digital marketing services.