Variance Analysis for Customer-Merchant Offer Comparison
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack efficient mechanisms for customers to communicate and compare offers from multiple merchants, particularly in high-value product transactions, leading to difficulties in evaluating financing options and product preferences.
Innovation Solution
A computer-implemented method and system that enables customers to submit criteria, receive merchant replies, and determine variances between customer and merchant criteria, facilitating secure sharing and display of information to facilitate informed decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If customers manually communicate preferences to multiple merchants, then communication is possible, but time consumption increases and efficiency decreases
Solution Approach 1:
The system creates a digital copy of customer preferences and submits them electronically to multiple merchants simultaneously. This eliminates the need for customers to manually repeat their preferences to each merchant, significantly reducing time consumption and improving communication efficiency.
Solution Approach 2:
The customer preference submission system serves multiple functions: it communicates preferences to merchants, enables automated variance analysis, facilitates offer comparison, and provides decision-making support. This multi-functional approach replaces multiple separate communication actions with a single unified system.
2Loss of information
If merchants provide detailed offers with multiple criteria, then offer information is comprehensive, but customer ability to directly compare offers deteriorates
Solution Approach 1:
The system introduces an intermediary variance analysis component that automatically processes and compares multiple merchant offers against customer preferences. This intermediary translates complex multi-criteria offers into standardized variance metrics, making comparison straightforward while preserving all original offer information.
Solution Approach 2:
The system transforms diverse offer criteria into standardized variance parameters that represent deviations from customer preferences. By changing the representation format from raw offer data to normalized variance metrics, the system enables easy numerical comparison while maintaining complete information about original offers.
3Reliability
If pre-qualification financing approval is provided through a letter, then financing capability is confirmed, but useful information for vehicle matching is lost
Solution Approach 1:
Instead of providing a simple approval letter, the system creates a comprehensive digital profile that copies and structures all relevant financing and preference information in a machine-readable format. This enriched data copy can be directly utilized by merchants for vehicle matching while maintaining the reliability of financing approval.
Data Source
AI summary
A computer-implemented method may include causing a customer device to display a user portal; receiving the input customer criteria; determining that a merchant possesses a corresponding item; updating the user portal with a selectable indication of the merchant; facilitating secure information sharing by: generating an access communication unique to the customer and without any customer information; transmitting the communication to a merchant device; and providing a merchant portal with further interactive objects; receiving, a transmission based on the access communication; securely providing the customer information to the merchant device via the merchant portal; receiving merchant criteria entered by the merchant; and automatically: determining a variance between the customer criteria and the merchant criteria; and updating at least one of the merchant or user portal to include at least one of the variance or the merchant criteria.