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Geo-fencing is a location based service that allows sending of messages to users who enter/exit a specified geographical area, known as a geo-fence. Today, it has become one of the popular location based mobile marketing strategies. However, the process of designing geo-fences is presently manual, i.e. a retailer must specify the location and the radius of area around it to setup the geo-fences. Moreover, this process does not consider the user's preference towards the targeted product/service and thus, can compromise his/her experience of the app that sends these communications. We attempt to solve this problem by presenting a novel end-to-end system for automated design of affinity based smart geo-fences. Affinity towards a product/service refers to the user's interest in a product/service. Our unique formulation to estimate affinity, using historical app usage data, is sensitive to a user's location and thus, the affinity is termed as location sensitive product affinity (LSPA). The geo-fence logic tries to capture contiguous groups of locations where the affinity high. Experiments on real world e-commerce dataset reveals that geo-fences designed by our approach performs significantly better at accurately targeting the users who are interested in a product. We thus show that, using historical app usage data, geo-fences can be designed in an automated manner and can help enterprises target interested users with better accuracy as compared to the present industry practices.
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