Systems, methods, and apparatus are described herein for determining a location from anonymous data. For example, a computing device may receive anonymous data associated with a browser session initialized by a user via a browser on a user computing device. The computing device may determine that the user has not been assigned a unique identifier. The computing device may determine whether the user opted-in to location tracking. If the user opted-out of location tracking, the computing device may determine a latitude coordinate and a longitude coordinate of the user computing device during the browser session. The computing device may identify a physical address for the user based on the latitude coordinate and the longitude coordinate, for example, using a map application programming interface (API). The computing device may assign the unique identifier to the user. The computing device may associate the unique identifier to the physical address.

Systems and methods for determining an optimal delivery location based on delivery address and delivery time are provided. An example method includes receiving an online order from a user application installed on a user device; generating a map comprising a dynamic display of a local service area polygon associated with the online order and transmitting the map to the user application; transmitting to the user application a request for a delivery address; upon receipt of the delivery address, querying the delivery address to determine whether the local service area polygon includes the delivery address; transmitting to the user application a request for a delivery time; upon receipt of the delivery time, automatically recommending an optimal delivery location and time within the local service area polygon based on the delivery address and delivery time; and executing a delivery of the online order based on the optimal delivery location and time.

Embodiments of the present invention provide methods, systems, apparatuses, and computer program products for predicting system resource volumes for future network time intervals based upon predicted likelihoods of termination transactions for the future network time interval.

Apparatus and associated methods relate to automatically prioritizing predicted events in a dynamic predicted queueing profile (PQP) for a service provider (SP) for a finite future time period. In an illustrative example, a central orchestration engine (COE) may generate, in response to a request for service from a service seeking entity (SSE), a dynamic queueing event profile (DQEP) associating the SSE with the PQP for the SP at the future time period. The COE may, for example, generate a confidence level of execution (CLE) for each DQEP in the PQP based on a historical behavior profile (HBP) of the SP and of each corresponding SSE. The COE may, for example, apply the confidence level of execution to each corresponding DQEP to assign a priority in the PQP. Various embodiments may, for example, advantageously dynamically prioritize a queue based on historical behavior of an SP and SSEs in the queue.

Systems, method and computer program products for presenting to a user a visualization of a vehicle dealer performance assessment based on dealer location and vehicle sales transaction data, where the assessment is based on geographically normalized metrics. Dealer location data and historical vehicle sales transaction data is collected by a in a vehicle data system from external data sources. Distances from dealers to geographical regions of interest are determined, and differences between these distances are normalized to produce competition zone indices for the geographical regions. The competition zone indices are then used to aggregate the geographical regions into different competition zones in which dealers of interest have corresponding levels of competitive advantage or disadvantage, normalized according to typical distances associated with transactions in the respective geographical regions.

Quantitative evaluations of friction within a customer experience may be provided to reduce abandonment and improve conversion of transactions. One or more transactions may be identified. One or more personas corresponding to the one or more transactions may be identified. One or more customer friction factor (CFF) scores corresponding to the one or more transactions may be determined. A given CFF score may be a quantification of an aspect of a given transaction that has a negative impact on a customer experience associated with the given transaction. The one or more CFF scores may be compared with one or more valid comparisons relating to the same industry and the same transaction type. One or more friction points may be identified based on the comparison of the one or more CFF scores. Addressing a friction point may reduce abandonment and improves conversion associated with transactions.

Various embodiments of the present technology generally relate to data delivery. More specifically, some embodiments of the present technology relate to systems and methods for using spatial and temporal analysis to associate data sources with mobile devices. The delivery of data to support a wide variety of services for and about mobile devices that are based on data stored in corporate, commercial, and government databases which is not currently linked to individual mobile devices. Some embodiments allow advertisers to better target their ads to relevant target audiences with greater accuracy.

Provided herein are platforms for determining a non-navigational quality of at least one infrastructure by a plurality of autonomous or semi-autonomous land vehicles through infrastructure recognition and assessment.

The present disclosure describes transaction-enabling systems and methods. A system may include a smart contract wrapper configured to access a distributed ledger including a plurality of intellectual property (IP) licensing terms corresponding to a plurality of IP assets, wherein the plurality of IP assets include an aggregate stack of IP, interpret an IP description value and an IP addition request, and, in response to the IP addition request and the IP description value, to add an IP asset to the aggregate stack of IP.

A computing system computes a timing interval between high-capacity vehicles (HCVs) for each HCV corridor within a geographic region to control rates of HCVs entering and exiting each of the HCV corridors. For each of the HCV corridors, the computing system schedules a first HCV to provide a transport service along the corridor beginning at a first starting time, transmits first schedule data for the corridor to the first HCV, schedules a second HCV to provide the transport service along the corridor beginning at a second starting time after the first starting time according to the timing interval for the corridor, and transmits second schedule data for the corridor to the second HCV.