Alternative Vehicle Structure Generation for Inventory Matching
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Solution Overview
Problem
The existing vehicle purchasing process is inefficient when buyers seek specific vehicles with matching terms, as similar vehicles may not be available, leading to a time-consuming search process for both buyers and dealers.
Innovation Solution
A method is developed to dynamically generate structures for alternative vehicles, calculating a combined score based on similarity to the buyer's initial choice, using a network environment with a vehicle database server, application server, and bank database server to present vehicles with comparable terms, employing AI and machine learning algorithms for clustering and scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the buyer searches for alternative vehicles manually when the initial choice is unavailable, then the buyer can find alternative vehicles, but the purchasing process becomes time-consuming
Solution Approach 1:
The system pre-generates multiple alternative vehicle configurations and financing terms before the buyer needs them. When the initial vehicle choice is unavailable, these pre-computed alternatives are immediately presented to the buyer, eliminating the need for time-consuming manual searches and iterations.
Solution Approach 2:
The system creates copies of the buyer's desired vehicle configuration with slight variations (different colors, trim levels, optional packages) and pairs them with pre-calculated financing terms. These copied configurations are quickly presented as alternatives, maintaining similarity to the original choice while avoiding lengthy renegotiation processes.
2Adaptability or versatility
If the dealer presents multiple alternative vehicles with different terms, then the buyer has more options, but the complexity of the purchasing process increases
Solution Approach 1:
The system systematically varies key parameters (vehicle configuration, financing term, interest rate, down payment) to generate alternative offers. By controlling and organizing these parameter changes, the system presents diverse options in a structured manner that doesn't overwhelm the buyer, maintaining simplicity while providing versatility.
Solution Approach 2:
The system employs a universal platform that handles multiple functions: vehicle configuration generation, financing term calculation, alternative presentation, and selection management. This multi-functional approach consolidates what would otherwise be separate complex processes into a single streamlined system.
3Ease of operation
If the buyer negotiates financing terms for each alternative vehicle, then the buyer can find suitable terms, but the process becomes increasingly time-consuming
Solution Approach 1:
The system pre-calculates multiple financing scenarios (different loan terms, interest rates, down payments) for each alternative vehicle configuration before presenting them to the buyer. This preliminary computation of financing terms eliminates the need for time-consuming negotiations, as suitable options are already prepared and presented.
Solution Approach 2:
The system automatically generates and presents financing terms based on the vehicle configuration and buyer's preferences, without requiring manual negotiation. The buyer can directly select from pre-computed financing options, making the process self-service oriented and significantly reducing time expenditure.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for providing an overall assessment of a combined inventory item and structure similarity to an initial inventory item and structure. A plurality of inventory items, stored in a database, maybe retrieved to generate a score value corresponding to each of the plurality of inventory items based on a plurality of facets describing the inventory item. Based on the generated score value, a subset of the plurality of inventory items may be determined based on data points representing the subset of the plurality of inventory items that are within a preconfigured Euclidean distance from a centroid representing a data point corresponding to the initial inventory item. One or more structures corresponding to the subset of the plurality of inventory items may be dynamically generated, and their combinations are scored for finding an alternate inventory item and structure.