Motor Vehicle Lead Evaluation System with Predictive Scoring
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Solution Overview
Problem
The increase in Internet-based vehicle quote requests has diluted the quality of leads, making it difficult for motor vehicle dealers to evaluate their value effectively, leading to high costs and inconsistent quality in lead purchasing decisions.
Innovation Solution
A process and system for evaluating motor vehicle leads by determining a predictive score, valuing leads based on historical data, optimizing sales capacity and lead need, and routing leads according to business rules to ensure real-time optimization and quality assurance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If Internet-based lead generation is used to increase quote request volume, then lead quantity increases, but lead quality deteriorates
Solution Approach 1:
The patent segments leads into different quality tiers based on predictive scoring (e.g., hot, warm, cold leads). This segmentation allows dealers to focus resources on high-quality leads while still processing large volumes, resolving the contradiction between quantity and quality by treating different lead segments differently in the distribution process.
Solution Approach 2:
The system changes the parameter of lead evaluation by introducing predictive scoring based on multiple data points (consumer behavior, demographic information, purchase intent signals). This transforms lead quality from a subjective assessment to an objective, quantifiable metric, enabling effective quality control at scale.
2Productivity
If more leads are purchased to maintain sales volume, then sales capacity is maintained, but costs increase
Solution Approach 1:
The system performs preliminary valuation and scoring of leads before they are distributed to dealers. By pre-identifying high-quality leads through predictive analytics, the system ensures that dealers receive only the most promising leads, reducing waste and lowering the cost per acquisition while maintaining sales capacity.
Solution Approach 2:
The system incorporates feedback loops where outcome data from closed leads is fed back into the predictive scoring model. This continuous learning process improves the accuracy of lead valuation over time, enabling more efficient lead allocation and reducing acquisition costs while maintaining or improving sales productivity.
3Device complexity
If traditional lead evaluation methods are used, then process simplicity is maintained, but evaluation accuracy deteriorates
Solution Approach 1:
The patent introduces an intermediary predictive scoring system that automatically evaluates leads based on multiple data points. This intermediary layer handles the complexity of multi-factor analysis, presenting simplified, pre-evaluated lead scores to dealers. The intermediary absorbs the computational complexity while delivering simple, actionable quality indicators to end users.
Data Source
AI summary
System, process, and computer program product for evaluating a lead are provided. A process for evaluating a lead may include determining whether each incoming lead is duplicative, determining a score for each lead, valuing each lead based on the lead score and outcome data, and determining sales capacity and the motor vehicle dealer's existing need for leads. The process may also include applying business rules to each lead using a processor, where the business rules may include the real-time optimization of sales capacity and lead need of a motor vehicle dealer. The process may further include routing each lead based upon the satisfaction of the business rules.