A system computes a timing interval between high-capacity vehicles (HCVs) for each of a plurality of HCV corridors within a geographic region, each respective HCV corridor of the plurality of HCV corridors including a start area. For each respective HCV corridor, the system transmits, via a network communication interface, (i) first data to a first computing device associated with a first HCV, the first data indicating the start area of the respective HCV corridor, and a first start time for the first HCV, and (ii) second data to a second computing device associated with a second HCV, the second data indicating the start area of the respective HCV corridor and a second start time for the second HCV, wherein the first start time for the first HCV and the second start time for the second HCV are based on the computed timing interval for the respective HCV corridor.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

The disclosed embodiments generally relate to in-store customer traffic analysis systems and methods. The system includes at least one sensor positioned within a retail store, at least one display associated with the at least one sensor, one or more memory devices storing instructions and one or more hardware processors configured to execute the instructions to perform operations. The operations include receiving a sensor signal indicating that a user device is within a proximity to the at least one sensor in the retail store, extracting a user device identifier from the sensor signal, correlating the sensor signal to the at least one display, generating a foot traffic record associated with the user device identifier and the at least one display, based on the received sensor signal, and storing the generated foot traffic record.

Customer transaction data is processed to determine transaction locations for transactions, including transactions whose locations are not initially known. The transaction location data is then utilized to identify merchants that are mobile merchants, and the mobile merchant locations are periodically recalculated and tracked. Customer transaction data is further utilized to identify relationships between mobile merchants and customers of those mobile merchants. Merchant and customer data is also analyzed to identify potential customers of mobile merchants, and data related to the mobile merchants is provided to current and potential customers of those mobile merchants.

A device may detect a first entry of a first user device of a first user into a merchant area. The device may monitor a movement of the first user device within the merchant area. The movement may include a transition from a shopping area of the merchant area to a checkout area of the merchant area. The device may detect a transaction between the first user and the merchant. The device may determine a shopping duration for the first user and a checkout duration for the first user. The device may detect a second entry of a second user device of a second user into the merchant area. The device may perform one or more actions based on detecting the second entry. The one or more actions may be performed selectively based on the shopping duration or the checkout duration of the first user.

A computer-implemented method includes: obtaining, by a detection device, first device information of a first set of devices detected in a target area using a first communication mode; determining, based on the first device information, a first quantity of devices in the target area; determining, based on second device information of a second set of devices, a verification coefficient, the second set of devices being detected in the target area using a second communication mode; and calculating, based on the first quantity of devices and a verification coefficient, a measure of real-time human traffic in the target area.

A system to dynamically generate, monitor and optimize a procurement campaign includes a processor-based server to process requests received from the client devices. The processor-based server includes a server processor to generate the procurement campaign having one or more units selected based on a campaign budget of the client, target rating point goal, a geolocation, a price, a format, average audited impressions and an inventory quality coefficient of each unit in the inventory of available units for purchase. The server processor monitors availability of previously unavailable units and track real-time changes to the inventory quality coefficients for each unit in the updated inventory. The server processor dynamically updates and optimizes the procurement campaign based on the updated inventory quality coefficients for the updated inventory of available units for purchase.

Systems and methods for identifying dominant user locations so that optimum user experience improvement solutions can be deployed at the identified locations are disclosed. One of the purposes of the dominant customer location identification system is to plan for site capacity (for example, small cell planning, hot-spots planning, and dense area capacity planning) and to offer optimum/premium customer experience. The system does this by understanding the customer's dominant locations over a certain period of time (for example, monthly) so that the customer's overall experience can be enhanced. Once a customer's dominant locations are identified, then the telecommunications service provider can gain a better understanding of the primary sites providing service to the customer, and deploy/implement/execute one or more optimum customer experience improvement solutions at the identified sites.

A system, method, and computer program product that facilitates markets and transactions between consumers and merchants. The system includes an enrollment process for consumers and merchants, a consumer identification module, a hyper-personalized matching process, a consumer experience feed, a purchase matching module, and a reward settlement module. The invention may implement artificial intelligence and machine learning methods to identify consumers who are likely to purchase a product or respond to a promotion and to identify promotions that an individual consumer will likely respond to. The invention can then present the identified promotions to a consumer in a personalized, emotionally engaging manner. If a consumer makes a purchase associated with the promotion, the system will identify the purchase and apply the purchase to the consumer's account.

Systems and methods relate to predicting improved operating hours for a merchant. For example, a method may include determining operating hours of a target merchant; identifying one or more merchants other than the target merchant having one or more common characteristics with the target merchant; obtaining transactional data indicating customer transactions at the one or more merchants other than the target merchant; computing an estimate of potential customer transactions at the target merchant during a the period of time not within the operating hours by processing input data including the obtained transactional data using a trained machine learning model to produce the estimate, the estimate being a number or value of consumer transactions missed as a result of the target merchant being closed during the period of time; and transmitting, to the target merchant, information indicating the computed estimate.