Abstract: Systems, methods and computer program products for selecting dealers based on characteristics of the dealers and the user. A vehicle data system collects dealer location and historical transaction data from external data sources and generates and stores an eligibility table that identifies a set of eligible dealers for each combination of user location and vehicle make. Eligible dealers are determined from the eligibility table using a location and vehicle make identified from a user request. Scores are determined for each eligible dealer based on a dealer scoring model using a binary choice model in the form of a logistic regression of market share, inventory, close rate, price and distance, and dealers are ranked by these scores. A presentation of dealers selected by rank and by closest location to the user is generated and provided to the user via an interface running on a computing device.

Abstract: 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.

Abstract: Systems, methods and computer program products for selecting dealers based on characteristics of the dealers and the user. A vehicle data system collects dealer location and historical transaction data from external data sources and generates and stores an eligibility table that identifies a set of eligible dealers for each combination of user location and vehicle make. Eligible dealers are determined from the eligibility table using a location and vehicle make identified from a user request. Scores are determined for each eligible dealer based on a dealer scoring model using a binary choice model in the form of a logistic regression of market share, inventory, close rate, price and distance, and dealers are ranked by these scores. A presentation of dealers selected by rank and by closest location to the user is generated and provided to the user via an interface running on a computing device.

Abstract: 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.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to assign zone labels to geographic areas and present representations of the geographic areas based on the normalization metrics across the distributed computer network.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to assign zone labels to geographic areas and present representations of the geographic areas based on the normalization metrics across the distributed computer network.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to determine or predict one or more metrics about participants in a network.

Abstract: Systems, methods and computer program products for selecting dealers based on characteristics of the dealers and the user. A vehicle data system collects dealer location and historical transaction data from external data sources and generates and stores an eligibility table that identifies a set of eligible dealers for each combination of user location and vehicle make. Eligible dealers are determined from the eligibility table using a location and vehicle make identified from a user request. Scores are determined for each eligible dealer based on a dealer scoring model using a binary choice model in the form of a logistic regression of market share, inventory, close rate, price and distance, and dealers are ranked by these scores. A presentation of dealers selected by rank and by closest location to the user is generated and provided to the user via an interface running on a computing device.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to determine or predict one or more metrics about participants in a network.

Abstract: Systems, methods and computer program products for selecting dealers based on characteristics of the dealers and the user. A vehicle data system collects dealer location and historical transaction data from external data sources and generates and stores an eligibility table that identifies a set of eligible dealers for each combination of user location and vehicle make. Eligible dealers are determined from the eligibility table using a location and vehicle make identified from a user request. Scores are determined for each eligible dealer based on a dealer scoring model using a binary choice model in the form of a logistic regression of market share, inventory, close rate, price and distance, and dealers are ranked by these scores. A presentation of dealers selected by rank and by closest location to the user is generated and provided to the user via an interface running on a computing device.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to assign zone labels to geographic areas and present representations of the geographic areas based on the normalization metrics across the distributed computer network.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to assign zone labels to geographic areas and present representations of the geographic areas based on the normalization metrics across the distributed computer network.

Abstract: Systems, methods and computer program products for selecting dealers based on characteristics of the dealers and the user. A vehicle data system collects dealer location and historical transaction data from external data sources and generates and stores an eligibility table that identifies a set of eligible dealers for each combination of user location and vehicle make. Eligible dealers are determined from the eligibility table using a location and vehicle make identified from a user request. Scores are determined for each eligible dealer based on a dealer scoring model using a binary choice model in the form of a logistic regression of market share, inventory, close rate, price and distance, and dealers are ranked by these scores. A presentation of dealers selected by rank and by closest location to the user is generated and provided to the user via an interface running on a computing device.

Abstract: 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.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to determine or predict one or more metrics about participants in a network.

Abstract: Embodiments of vehicle data systems for use in distributed computer network are disclosed. Particular embodiments may determine and enhance vehicle data from various data sources distributed across the computer network, and utilize the enhanced vehicle data in the determination of normalization metrics that account for geography and population density or spatial behavioral patterns. Embodiments may utilize these normalization metrics to assign zone labels to geographic areas and present representations of the geographic areas based on the normalization metrics across the distributed computer network.

Abstract: A vehicle data system may receive, via a website, a user query about a vehicle or features of a vehicle that may not actually exist. The vehicle data system can transform vehicle features representing a user-configured vehicle, compare the user-configured vehicle with inventory vehicles, determine how similar the user-configured vehicle is to each inventory vehicle, how likely each inventory vehicle may be purchased given the user-configured vehicle and consumer behavior modeled based on actual historical transaction data collected via the website. The vehicle features may be weighted. Feature weights can be automatically determined and continuously fine-tuned utilizing machine learning. Each inventory vehicle is scored utilizing a similarity vector that compares it with the user-configured vehicle. Top-ranked inventory vehicle(s) can then be recommended to the user via the website in real time.