Systems and methods for intelligent ad-based routing

Abstract

Examples of the present disclosure describe systems and methods for intelligent ad-based routing. In example aspects, a destination input, desired time for arrival, and user profile data is received in a ride-sharing application. The input data is classified by applying one or more machine-learning models to the data. Based on the classified data results, candidate physical advertisement locations may be selected along a certain route. Different types of routes may be selected that range from the shortest possible route (i.e., a direct route) to a major detour (i.e., the most cost-effective route). A major detour takes the user on a route that exposes the user to as many advertisements as possible while still arriving at the final destination before the desired time of arrival. In exchange for a longer route and more exposure to physical advertisements, the cost of the ride may be offset. While the user is in proximity to the physical advertisement along the route, businesses associated with the physical advertisement locations may transmit real-time advertisements/messages to the user to be displayed on a user device, a vehicular device, and/or a combination of the two. During the ride, the real-time business information may be received that may alter the route to maximize the effectiveness of real-time advertisement delivery.