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 geofencing is presently manual, i.e. a retailer has to specify the location and the radius of area around it to setup the geo-fences. In addition, this process does not take into account 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 creation of affnity based smart geo-fences. Affnity towards a product/service refers to the user’s interest in a product/service. Our unique formulation to estimate affnity, using historical app usage data, is sensitive to a user’s location as well and thus, the affnity is termed as location sensitive product affnity (LSPA). The geo-fence logic tries to capture contiguous groups of locations where the affnity high. Experiments on real world ecommerce dataset reveals that geo-fences designed by our approach performs signiffcantly 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 created in an automated manner and help enterprises target interested users with better accuracy as compared to the present industry practices.