Abstract:
A vehicle identification number (VIN) decoder (VDC) implementing a unique VIN decoding method may, for a given VIN, shorten the VIN and form a stem and a leaf therefrom. Utilizing the stem, the VDC may operate to find matching leaf values, if any, from a set of look up tables. Depending upon a match outcome, one or more trim identification code (TIC) values can be assigned to the VIN and a candidate list can be constructed utilizing the assigned TIC value(s). The candidate list, which can be optimized, may contain one or more candidate trims for the VIN. For each candidate trim, a confidence score and match probability can be generated. The VDC may provide decoded information containing trim data associated with at least one of the one or more candidate trims for the VIN to a client device over a network connection.
Abstract:
Systems and methods for the aggregation, analysis, and display of data for used vehicles are disclosed. Historical transaction data for used vehicles may be obtained and processed to determine pricing data, where this determined pricing data may be associated with a particular configuration of a vehicle. The user can then be presented with an interface pertinent to the vehicle configuration utilizing the aggregated data set or the associated determined data where the user can make a variety of determinations. This interface may, for example, be configured to present the historical transaction data visually, with the pricing data such as a trade-in price, a list price, an expected sale price or range of sale prices, market low sale price, market average sale price, market high sale price, etc. presented relative to the historical transaction data.
Abstract:
Embodiments disclosed herein provide systems and methods for the filtering, selection and presentation of vendors accounting for both user characteristics and vendor characteristics, such that the systems and methods may be used by both customer and vendor alike to better match customer needs with the resource-constrained vendors with whom a successful sale has a higher probability of occurring. Embodiments may include filtering, selecting and/or presenting vendors to a user sorted by the probability that the particular vendor will possess the characteristics that appeal to a particular customer and therefore result in a large probability of sale and suppress presentation of those vendors that are unlikely to be selected by the customer since their characteristics are less consistent with those needed by the customer and, therefore, are unlikely to result in a sale.
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 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 and method herein provide for sophisticated and efficient matching between users of a vehicle data system and data on sales that occur, where that data was obtained from distributed sources across a computer network. In particular, embodiments may obtain data from a variety of data sources across a distributed network and enhance data records by correlating the data obtained from these distributed sources. Data on sales thus obtain can be correlated with data on online users of the vehicle data system using a scoring engine to provide confidence scores to potential user-sale matches.
Abstract:
Embodiments disclosed provide a system, method, and computer program product for identifying consumer items more likely to be bought by an individual user. In some embodiments, a collaborative filter may be used to rank items based on the degree to which they match user preferences. The collaborative filter may be hierarchical and may take various factors into consideration. Example factors may include the similarity among items based on observable features, a summary of aggregate online search behavior across multiple users, the item features determined to be most important to the individual user, and a baseline item against which a conditional probability of another item being selected is measured.
Abstract:
A vehicle sales matching system may include a vehicle sales lead data database, a vehicle sales information database, and a sales matching system embodied on a non-transitory computer-readable medium and communicatively connected to the vehicle sales lead data database and the vehicle sales information database. The vehicle sales lead data may include validated customer data and third-party customer data. The vehicle sales information may include sales data from vehicle dealers, data extract services, and sales data sources. The sales matching system may be configured for applying one or more matching rules for matching a vehicle sales lead from the vehicle sales lead database to a vehicle sale from the vehicle sales information database.
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. 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.
Abstract:
Systems and method herein provide for sophisticated and efficient matching between users of a vehicle data system and data on sales that occur, where that data was obtained from distributed sources across a computer network. In particular, embodiments may obtain data from a variety of data sources across a distributed network and enhance data records by correlating the data obtained from these distributed sources. Data on sales thus obtain can be correlated with data on online users of the vehicle data system using a scoring engine to provide confidence scores to potential user-sale matches.