Systems, non-transitory computer readable mediums, and methods for improved vehicle transaction platforms

A method, comprising:

• determining, at a first time, prior to receiving a vehicle search request from a first consumer, via a website associated with a vehicle transaction platform comprising an inventory of vehicles for acquisition, and using a machine learning model, a plurality of consumer search patterns based on one or more prior searches performed by a plurality of consumers through a user interface of the website, wherein the inventory of vehicles includes at least 5,000 vehicles with at least 1,000 down payment options, at least 350 net trade-in options, at least five payment term options, and at least 50,000 tax locations, and wherein an amount of time required to calculate, by the vehicle transaction platform, all possible transaction pricing data permutations for vehicles in the inventory of vehicles would render the website of the vehicle transaction platform unusable as the vehicle transaction platform would be unable to perform calculations to update a user interface website in real-time with the transaction pricing data for each of the vehicles in the inventory of vehicles;
• determining, via the machine learning model, a first subset of vehicles of the inventory of vehicles and one or more deal structures associated with a first consumer search pattern of the plurality of consumer search patterns;
• determine, based on the one or more deal structures, actual transaction pricing data for the first subset of vehicles, the actual transaction pricing data including total purchase prices and periodic payment amounts for the first subset of vehicles;
• storing the plurality of consumer search patterns in memory, wherein the actual transaction pricing data is stored in the memory in association with the first consumer search pattern;
• receiving, at a second time subsequent to storing the plurality of consumer search patterns in the memory, from a user device associated with the first consumer, and via the user interface of the website associated with the vehicle transaction platform, the vehicle search request, wherein the first consumer that is different than the plurality of consumers, wherein the vehicle search request is performed using a first user account associated with a user;
• determining, by the machine learning model and based on consumer information associated with the first consumer, that the consumer information matches the first consumer search pattern of the plurality of consumer search patterns;
• retrieve, at the second time and based on the determination that the consumer information matches the first consumer search pattern, the first subset of vehicles and the actual transaction pricing data from the memory without re-calculating the actual transaction pricing data at the second time;
• present, at the second time, using the transaction pricing data stored in the memory instead of re-calculating the transaction pricing data in real-time, and via the user interface of the website, the first subset of vehicles and the actual transaction pricing data, such that the first subset of the vehicles and the transaction pricing are presented to the user in real-time via the user interface of the website as the user browses the website without causing latency that would prevent the user interface of the website from being presented in real-time;
• receiving, at a third time and via the user interface of the website associated with the vehicle transaction platform, an input including a modification to the vehicle search request;
• dynamically updating, in at the third time and based on the input, the actual transaction pricing data to produce updated actual transaction pricing data;
• and
• presenting, in at the third time and via the user interface, the updated actual transaction pricing data.

A non-transitory computer readable medium including computer-executable instructions stored thereon, which when executed by one or more processors, cause the one or more processors to perform operations of:

• determining, at a first time, prior to receiving a vehicle search request from a first consumer, via a website associated with a vehicle transaction platform comprising an inventory of vehicles for acquisition, and using a machine learning model, a plurality of consumer search patterns based on one or more prior searches performed by a plurality of consumers through a user interface of the website, wherein the inventory of vehicles includes at least 5,000 vehicles with at least 1,000 down payment options, at least 350 net trade-in options, at least five payment term options, and at least 50,000 tax locations, and wherein an amount of time required to calculate, by the vehicle transaction platform, all possible transaction pricing data permutations for vehicles in the inventory of vehicles would render the website of the vehicle transaction platform unusable as the vehicle transaction platform would be unable to perform calculations to update a user interface website in real-time with the transaction pricing data for each of the vehicles in the inventory of vehicles;
• determining, via the machine learning model, a first subset of vehicles of the inventory of vehicles and one or more deal structures associated with a first consumer search pattern of the plurality of consumer search patterns;
• determining, based on the one or more deal structures, actual transaction pricing data for the first subset of vehicles, the actual transaction pricing data including total purchase prices and periodic payment amounts for the first subset of vehicles;
• storing the plurality of consumer search patterns in memory, wherein the actual transaction pricing data is stored in the memory in association with the first consumer search pattern;
• receiving, at a second time subsequent to storing the plurality of consumer search patterns in the memory, from a user device associated with the first consumer, and via the user interface of the website associated with the vehicle transaction platform, the vehicle search request, wherein the first consumer that is different than the plurality of consumers, wherein the vehicle search request is performed using a first user account associated with a user;
• determining, by the machine learning model and based on consumer information associated with the first, that the consumer information matches the first consumer search pattern of the plurality of consumer search patterns;
• retrieving, at the second time and based on the determination that the consumer information matches the first consumer search pattern, the first subset of vehicles and the actual transaction pricing data from the memory without re-calculating the actual transaction pricing data at the second time;
• present, at the second time, using the transaction pricing data stored in the memory instead of re-calculating the transaction pricing data in real-time, and via the user interface of the website, the first subset of vehicles and the actual transaction pricing data, such that the first subset of the vehicles and the transaction pricing are presented to the user in real-time via the user interface of the website as the user browses the website without causing latency that would prevent the user interface of the website from being presented in real-time;
• receive, at a third time and via the user interface of the website associated with the vehicle transaction platform, an input including a modification to the vehicle search request;
• dynamically update, at the third time and based on the input, the actual transaction pricing data to produce updated actual transaction pricing data;
• and
• present, in at the third time and via the user interface, the updated actual transaction pricing data.