TrueCar has filed a patent for a method of geo-specific vehicle pricing. The method involves classifying historical transaction records based on vehicle attributes and geographic entities, determining a geo-specific pricing model, and providing estimated prices for user-specified vehicle configurations. The system aims to provide more accurate and localized pricing information to users. GlobalData’s report on TrueCar gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on TrueCar, Dynamic premium pricing was a key innovation area identified from patents. TrueCar's grant share as of September 2023 was 56%. Grant share is based on the ratio of number of grants to total number of patents.
Geo-specific vehicle pricing estimation based on historical transaction records
A recently filed patent (Publication Number: US20230281652A1) describes a method for geo-specific vehicle pricing. The method involves determining a hierarchy of geographic entities and classifying historical transaction records into bins based on vehicle attributes and the geographic hierarchy. Users can input their vehicle configuration and location through a website, and the system will determine a geo-specific pricing model for estimating the price of the specified vehicle configuration. This determination takes into account the user's vehicle attributes, location, and the hierarchy of geographic entities. The system also determines a geographic resolution at which a minimum threshold number of historical transaction records is met for each bin, and the pricing model corresponds to this resolution. Using the pricing model and a bin with sufficient historical transaction records, the system calculates an estimated geo-specific price for the user's vehicle configuration in the specified geographic entity. This estimated price is then provided to the website for display on the user's device.
The patent also mentions the use of rules, such as polygon merging or clustering rules, based on spatial adjacency or socioeconomic characteristics. The hierarchy of geographic entities includes Designated Market Areas (DMA) regions, DMA groups, DMAs, subDMAs, Zip Code to Zip Code Tabulation Areas (ZCTA), and Zip Codes. Additionally, the application of the geo-specific vehicle pricing model involves determining degradation factor values and maximum transaction ages, analyzing historical performance, and weighing each transaction based on age and degradation factor value. The model also takes into account geo-specific socioeconomic data, inventory data, vehicle-specific features, and a predicted margin ratio.
The method may further adjust the estimated geo-specific price to account for incentives applicable to the user's vehicle configuration in the specified geographic entity. Before classifying, data can be appended to the historical transaction records, including configurator data, offset data, census data, customer and dealer incentives data, or industry data. Each transaction in the historical records can also be assigned a temporal weight based on age.
The patent also describes a vehicle data system that includes a processor, a non-transitory computer-readable medium, and instructions for implementing the method described above. The system can receive user inputs, determine the pricing model, calculate the estimated price, and provide it to the website for display.
In summary, this patent presents a method and system for geo-specific vehicle pricing that takes into account historical transaction records, vehicle attributes, and geographic entities. The system uses a pricing model to estimate the price of a user-specified vehicle configuration in a specific geographic entity and can adjust the price for applicable incentives.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
