Abstract: An attribution system aggregates and merges online data and offline chronologically. The attribution system examines merged data for unique visitor (UV) sessions initiated at an online medium (e.g., a website) within an attribution window for a spot that aired on an offline medium (e.g., a television network) and, for each conversion event that occurred in a UV session, assigns a session timestamp to it so that the conversion event is correlated to the spot. The attribution system then determines an overall conversion rate of UVs to the online medium in the attribution window and the attribution by the spot that aired on the offline medium to the overall conversion rate of UVs to the online medium in the attribution window. Results of the offline attribution to the online conversions can be visualized and presented on a client device communicatively connected to the attribution system.

Abstract: Embodiments of the present disclosure relate to data correlation of data pertaining to content distributed through distinct content delivery networks including offline networks and data related to user interaction with an online presence on the distributed computer network and uses for such correlated data, including to measure and quantify latent effects of the content distributed through a distinct content delivery network, such as an offline network, on user's interactions with the online presence on the distributed computer network.

Abstract: An attribution system aggregates and merges online data and offline chronologically. The attribution system examines merged data for unique visitor (UV) sessions initiated at an online medium (e.g., a website) within an attribution window for a spot that aired on an offline medium (e.g., a television network) and, for each conversion event that occurred in a UV session, assigns a session timestamp to it so that the conversion event is correlated to the spot. The attribution system then determines an overall conversion rate of UVs to the online medium in the attribution window and the attribution by the spot that aired on the offline medium to the overall conversion rate of UVs to the online medium in the attribution window. Results of the offline attribution to the online conversions can be visualized and presented on a client device communicatively connected to the attribution system.

Abstract: 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. In certain embodiments, one or more models may be applied over a set of historical transaction data associated with a vehicle configuration to determine pricing data. Some models may leverage incremental data in various conditions, including cases where fewer than a desired number of historical transactions are present in the bin of a specified vehicle, where fewer than, equal to, or more than a certain number of list prices for the specified vehicle available, and where no historical transaction data for new models is available.

Abstract: An attribution system aggregates and merges online data and offline chronologically. The attribution system examines merged data for unique visitor (UV) sessions initiated at an online medium (e.g., a website) within an attribution window for a spot that aired on an offline medium (e.g., a television network) and, for each conversion event that occurred in a UV session, assigns a session timestamp to it so that the conversion event is correlated to the spot. The attribution system then determines an overall conversion rate of UVs to the online medium in the attribution window and the attribution by the spot that aired on the offline medium to the overall conversion rate of UVs to the online medium in the attribution window. Results of the offline attribution to the online conversions can be visualized and presented on a client device communicatively connected to the attribution system.

Abstract: Embodiments of systems and methods disclosed herein provide solutions for predicting vehicle invoice pricing, trim, and options by starting from scratch (raw data), transforming the raw data into actionable data, and comprehensively exploring all possible option combinations that can match a vehicle's Manufacturer Suggested Retail Price (MSRP). Embodiments implement algorithms that determine the trim of a vehicle and intelligently analyze all possible option combinations that would result in a target MSRP while avoid searching unnecessary vehicle configurations. The algorithms can be used to predict the trim, invoice, and options of a vehicle based on the vehicle's VIN and MSRP.

Abstract: Embodiments of systems and methods disclosed herein provide solutions for predicting vehicle invoice pricing, trim, and options by starting from scratch (raw data), transforming the raw data into actionable data, and comprehensively exploring all possible option combinations that can match a vehicle's Manufacturer Suggested Retail Price (MSRP). Embodiments implement algorithms that determine the trim of a vehicle and intelligently analyze all possible option combinations that would result in a target MSRP while avoid searching unnecessary vehicle configurations. The algorithms can be used to predict the trim, invoice, and options of a vehicle based on the vehicle's VIN and MSRP.

Abstract: Embodiments of the present disclosure relate to data correlation of data pertaining to content distributed through distinct content delivery networks including offline networks and data related to user interaction with an online presence on the distributed computer network and uses for such correlated data, including to measure and quantify latent effects of the content distributed through a distinct content delivery network, such as an offline network, on user's interactions with the online presence on the distributed computer network.

Abstract: An attribution system aggregates and merges online data and offline chronologically. The attribution system examines merged data for unique visitor (UV) sessions initiated at an online medium (e.g., a website) within an attribution window for a spot that aired on an offline medium (e.g., a television network) and, for each conversion event that occurred in a UV session, assigns a session timestamp to it so that the conversion event is correlated to the spot. The attribution system then determines an overall conversion rate of UVs to the online medium in the attribution window and the attribution by the spot that aired on the offline medium to the overall conversion rate of UVs to the online medium in the attribution window. Results of the offline attribution to the online conversions can be visualized and presented on a client device communicatively connected to the attribution system.

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: An attribution system aggregates and merges online data and offline chronologically. The attribution system examines merged data for unique visitor (UV) sessions initiated at an online medium (e.g., a website) within an attribution window for a spot that aired on an offline medium (e.g., a television network) and, for each conversion event that occurred in a UV session, assigns a session timestamp to it so that the conversion event is correlated to the spot. The attribution system then determines an overall conversion rate of UVs to the online medium in the attribution window and the attribution by the spot that aired on the offline medium to the overall conversion rate of UVs to the online medium in the attribution window. Results of the offline attribution to the online conversions can be visualized and presented on a client device communicatively connected to the attribution system.

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 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. In certain embodiments, one or more models may be applied over a set of historical transaction data associated with a vehicle configuration to determine pricing data. Some models may leverage incremental data in various conditions, including cases where fewer than a desired number of historical transactions are present in the bin of a specified vehicle, where fewer than, equal to, or more than a certain number of list prices for the specified vehicle available, and where no historical transaction data for new models is available.

Abstract: Embodiments of the present disclosure relate to data correlation of data pertaining to content distributed through distinct content delivery networks including offline networks and data related to user interaction with an online presence on the distributed computer network and uses for such correlated data, including to measure and quantify latent effects of the content distributed through a distinct content delivery network, such as an offline network, on user's interactions with the online presence on the distributed computer network.

Abstract: 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. In certain embodiments, one or more models may be applied over a set of historical transaction data associated with a vehicle configuration to determine pricing data. Some models may leverage incremental data in various conditions, including cases where fewer than a desired number of historical transactions are present in the bin of a specified vehicle, where fewer than, equal to, or more than a certain number of list prices for the specified vehicle available, and where no historical transaction data for new models is available.

Abstract: 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. In certain embodiments, one or more models may be applied over a set of historical transaction data associated with a vehicle configuration to determine pricing data. Some models may leverage incremental data in various conditions, including cases where fewer than a desired number of historical transactions are present in the bin of a specified vehicle, where fewer than, equal to, or more than a certain number of list prices for the specified vehicle available, and where no historical transaction data for new models is available.

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 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. In certain embodiments, one or more models may be applied over a set of historical transaction data associated with a vehicle configuration to determine pricing data. Some models may leverage incremental data in various conditions, including cases where fewer than a desired number of historical transactions are present in the bin of a specified vehicle, where fewer than, equal to, or more than a certain number of list prices for the specified vehicle available, and where no historical transaction data for new models is available.

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 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. In certain embodiments, one or more models may be applied over a set of historical transaction data associated with a vehicle configuration to determine pricing data. Some models may leverage incremental data in various conditions, including cases where fewer than a desired number of historical transactions are present in the bin of a specified vehicle, where fewer than, equal to, or more than a certain number of list prices for the specified vehicle available, and where no historical transaction data for new models is available.