Vehicle recommendations based on browser context

A method for providing context-aware recommendations, comprising:

• receiving, by a device and based on executing one or more client-side browser fingerprinting scripts on a client device, information related to a browser context associated with the client device,
• wherein the browser context includes metadata from one or more micro-frontend widgets running on one or more vehicle dealer websites and a historical pattern of browser interactions with content related to vehicles, and
• wherein the browser context indicates a location associated with the client device;
• generating, by the device, a vehicle feature vector that includes an array of elements to represent a plurality of vehicle attributes,
• wherein each element in the array of elements has a value to represent a user preference related to a corresponding vehicle attribute based on the historical pattern of browser interactions with the content related to vehicles;
• applying, by the device, a similarity model to the vehicle feature vector to determine a vehicle recommendation dataset that includes a plurality of vehicles that are each associated with a respective set of vehicle attributes;
• filtering, by the device, the vehicle recommendation dataset based on a subset of the information related to the browser context associated with the client device that indicates a profile of a user associated with the client device,
• wherein the vehicle recommendation dataset is filtered such that the vehicle recommendation dataset excludes any vehicles that are not within a threshold distance of the location associated with the client device;
• and
• providing, by the device, information related to the vehicle recommendation dataset to the client device for display in an interface associated with the client device.

A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a system, cause the system to:
• receive, based on executing one or more client-side browser fingerprinting scripts on a client device, information related to a browser context associated with the client device,
• wherein the browser context includes a historical pattern of browser interactions that includes one or more browser sessions in which the client device accessed a vehicle manufacturer or vehicle dealer website to view or configure a vehicle having a set of vehicle attributes, and
• wherein the browser context includes metadata from one or more micro-frontend widgets running on one or more vehicle dealer websites;
• generate a vehicle feature vector that includes an array of elements to represent a plurality of vehicle attributes,
• wherein each element in the array of elements has a value to represent a user preference related to a corresponding vehicle attribute based on the historical pattern of browser interactions;
• apply a similarity model to the vehicle feature vector to determine a vehicle recommendation dataset that includes a plurality of vehicles that are each associated with a respective set of vehicle attributes;
• filter the vehicle recommendation dataset based on creditworthiness information associated with a user of the client device;
• and
• provide information related to the vehicle recommendation dataset to the client device for display in an interface associated with the client device.