Systems and methods for providing an enhanced analytical engine

A vehicle searching method comprising:

• receiving, via an interface of the vehicle searching system, a request from a user, the request comprising vehicle identification information comprising an indication of one or more vehicle features desired by the user;
• identifying information associated with one or more vehicles associated with one or more of a plurality of dealership systems;
• generating, based on the vehicle identification information, a filtered set of vehicles from among the one or more vehicles;
• providing, to the user, data representing information associated with the filtered set of vehicles;
• accessing historical vehicle purchase transaction data for the corresponding dealership system of each vehicle of the filtered set of vehicles, the historical vehicle purchase transaction data comprising vehicle information and overall negotiated price;
• generating, based on the user request and the historical vehicle purchase transaction data, a proposed offer package for each vehicle of the filtered set of vehicles, each proposed offer package comprising an associated overall price including one or more addons of one or more potential addons and a payment price within a threshold of a desired monthly payment or overall purchase price;
• determining, for each proposed offer package, a first respective likelihood of success metric representing the likelihood that the proposed offer package will be accepted by the corresponding dealership system by comparing the one or more of a warranty option, a maintenance option, or a service contract option for each vehicle of the filtered set of vehicles to similar historical warranty options, maintenance options, and service contract options from historical vehicle purchase transaction data;
• and
• providing, to the user, via the interface of the vehicle searching system, the generated proposed offer packages and the first respective likelihood of success metric.

A vehicle searching system comprising:

• one or more processors;
• and
• at least one memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, are configured to cause the system to:
• receive, via an interface of the vehicle searching system, a request from a user, the request comprising vehicle identification information comprising an indication of one or more vehicle features desired by the user;
• identify information associated with one or more vehicles associated with one or more of a plurality of dealership systems;
• generate, based on the vehicle identification information, a filtered set of vehicles from among the one or more vehicles;
• provide, to the user, data representing information associated with the filtered set of vehicles;
• access historical vehicle purchase transaction data for the corresponding dealership system of each vehicle of the filtered set of vehicles, the historical vehicle purchase transaction data comprising vehicle information and overall negotiated price;
• generate, based on the user request and the historical vehicle purchase transaction data, a proposed offer package for each vehicle of the filtered set of vehicles, each proposed offer package comprising an associated overall price including one or more addons of one or more potential addons and a price within a threshold of a desired monthly payment or overall purchase price;
• determine, for each proposed offer package, a first respective likelihood of success metric representing the likelihood that the proposed offer package will be accepted by the corresponding dealership system by comparing the one or more of a warranty option, a maintenance option, or a service contract option for each vehicle of the filtered set of vehicles to similar historical warranty options, maintenance options, and service contract options from historical vehicle purchase transaction data;
• and
• provide, to the user, via the interface of the vehicle searching system, the generated proposed offer packages and the first respective likelihood of success metric.