Truecar, Inc.

Mikhail Semeniuk

Michael D Swinson

Xingchu Liu

Isaac Lemon Laughlin

Meghashyam Grama Ramanuja

Joel Martin Lander

Scott Painter

Jesse Toprak

To increase the efficiency of a used vehicle data processing process while still tailoring to an individual user's unique specifications on a used vehicle, at least some pre-calculations are performed by a backend process before a request for data for a specified vehicle is received through a web site or a web server on the Internet. A user can be presented with an interface where the user can make a variety of determinations. After the user requests data on a specific vehicle configuration, a frontend process handles user-provided data in conjunction with the data calculated in the backend process to ensure that the results are better tailored to the user's specific vehicle attributes. The results can include 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.

System and method for analysis and presentation of used vehicle pricing data

Systems, methods and computer program products that determine wholesale prices for durable goods such as used vehicles. In one embodiment, a system includes a computer processor, a network interface, a data storage device, and an output device. The system collects and stores, via the network interface, historical sales information from external data sources. A retail price for a target vehicle is determined based on the collected information. Condition information for the vehicle is collected and used to adjust the retail price to arrive at a wholesale price, which is output to a user. The system may also adjust the price based on repair costs associated with identified vehicle conditions. The system may collect cost information associated with a wholesale sale transaction and deduct these costs and a profit margin from the wholesale price to produce a trade-in price.

Wholesale/trade-in pricing system, method and computer program product therefor

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.

Systems, methods and computer program products for determining costs of vehicle repairs and times to major repairs. In one embodiment, a system includes a computer processor, a data storage device, and an output device. The processor receives information from a user identifying a vehicle of interest. The processor retrieves repair data items that have characteristics common to the vehicle of interest from a database stored in the data storage device. The processor determines repairs that are expected to be necessary for the vehicle of interest based on the retrieved repair data items, and determines the costs associated with the identified expected repairs. The processor provides output to the user indicating the repair costs and/or the times at which the repairs are likely to be necessary. The output may be in graphical and/or numerical form.

Systems and methods for determining costs of vehicle repairs and times to major repairs

Systems and methods for estimating the cost of vehicle ownership wherein, in one embodiment, a system includes a computer processor that is coupled to a network interface, a data storage device and an output device, the processor being configured to receive information identifying a user-specified vehicle of interest and interval of interest. The processor uses this information to identify and retrieve pre-calculated data items that are stored in the data storage device, and to request external data items from an external data source and receive the requested external data items via the network interface. The processor computes cost-of-vehicle-ownership (COVO) components for the vehicle of interest, sums the components to determine an overall COVO, and outputs the components and overall COVO to a user via the output device. The user may provide further input to modify the COVO calculation.

Systems and methods for determining cost of vehicle ownership

Natural language processing (NLP) approaches may be utilized to map two strings. The strings may come from sources utilizing different naming conventions. One example may be a data aggregator that collects used car transaction information. Another example may be a comprehensive database listing all possible manufacturer-defined vehicle options. A NLP system may operate to determine whether a source string is present in a target string and outputting a match containing the source string and the target string if the source string is present in the target string or computing a similarity factor if the source string is not present in the target string. The similarity factor representing a measure of similarity between two strings may be computed based on a plurality of parameters, including a Levenshtein edit distance parameter. The computed similarity can be used to find pricing information, including trade-in, sale, and list prices, across disparate naming conventions.

Natural language processing system, method and computer program product useful for automotive data mapping

Embodiments disclosed herein can provide consumers with an effective tool for evaluating the negotiability of prices for vehicles in the marketplace. The tool may include a Price Flexibility Score which measures the elasticity of transaction prices by vehicle model. Specifically, a method may dynamically incorporate factors that affect price variance, convert those factors into variables, generate order statistics for each of the variables, apply a weighting factor to the variables to generate a price flexibility score for each make-model, and determine a negotiability index utilizing the price flexibility score. In one embodiment, the process of determining the negotiability index may be fully driven by a price flexibility model that incorporates a plurality of factors.

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Golden Valley, MN, United States of America

Mikhail Semeniuk