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: 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: 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.

Abstract: 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.

Abstract: 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.

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: 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.

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: 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: 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.

Abstract: 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.

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: 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: 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.

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: 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: 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, third party data extract services, and third party 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: 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: 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.