Geo-Conquesting Based on Graph Analysis for Crowdsourced Metatrails from Mobile Sensing

TL;DR

This paper presents a graph analysis approach for smart city marketing using crowdsourced mobile sensing data, introducing novel features like hotspot networks and crowd transitions to inform market planning.

Contribution

It introduces new crowdsourced features derived from mobile sensing data for market planning, focusing on enterprise perspectives in smart city environments.

Findings

Demonstrated the effectiveness of graph-based features in reflecting crowd preferences

Simulations validated the proposed approach for practical geo-conquesting applications

Discussed scenarios for deploying the method in real-world marketing strategies

Abstract

This article investigates graph analysis for intelligent marketing in smart cities, where metatrails are crowdsourced by mobile sensing for marketing strategies. Unlike most works that focused on client sides, this study is intended for market planning, from the perspective of enterprises. Several novel crowdsourced features based on metatrails, including hotspot networks, crowd transitions, affinity subnetworks, and sequential visiting patterns, are discussed in the article. These smart footprints can reflect crowd preferences and the topology of a site of interest. Marketers can utilize such information for commercial resource planning and deployment. Simulations were conducted to demonstrate the performance. At the end, this study also discusses different scenarios for practical geo-conquesting applications.