Automated Lead Segmentation and Routing for Auction Matching
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Solution Overview
Problem
The leads market faces inefficiencies in matching vendors with consumers due to timing and legal/serviceability issues, and existing pricing mechanisms are haphazard, making it difficult for buyers to obtain fair value for leads, with unscrupulous sellers flooding the market with junk leads that devalue high-quality leads.
Innovation Solution
An automated system that collects segmentation data to categorize leads dynamically, ensuring they are routed through appropriate telecommunications pathways, allowing for real-time matching of consumers with vendors who can service their needs and providing a fair market value through an open auctioning system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated segmentation data collection and routing is implemented, then lead matching efficiency and accuracy are improved, but system complexity increases
Solution Approach 1:
The system segments lead data into structured categories (segmentation data) including demographic information, geographic location, product interest, and contact preferences. This segmentation enables automated processing and precise matching while maintaining manageable system complexity through standardized data fields
Solution Approach 2:
The patent introduces an automated lead processing system as an intermediary between lead generation sources and vendors. This intermediary collects, validates, segments, and routes lead information through predefined pathways, reducing the complexity burden on individual components while improving overall efficiency
2Loss of time
If real-time lead matching is implemented, then consumer service timeliness is improved, but data collection and processing requirements increase
Solution Approach 1:
The system performs preliminary data collection and segmentation before the actual lead matching occurs. By pre-processing and categorizing lead information in advance, the system enables rapid real-time matching without requiring extensive data collection during the critical matching moment, thus reducing information loss while maintaining timeliness
Solution Approach 2:
The patent transforms raw lead data into segmented parameters (categories) that can be quickly processed and matched. This parameter transformation enables real-time decision-making by converting complex data into actionable categories that the matching system can process instantaneously
3Reliability
If automated lead categorization is implemented, then vendor-serviceability matching is improved, but data processing complexity increases
Solution Approach 1:
The system divides lead data into discrete segmentation categories (demographic, geographic, product, contact preferences) that can be systematically processed and matched. This segmentation simplifies the matching algorithm while improving accuracy by considering multiple independent factors
Solution Approach 2:
The patent transforms raw lead information into standardized segmented parameters that facilitate reliable matching. By converting unstructured data into standardized categories, the system reduces processing complexity while maintaining high matching accuracy through consistent parameter comparison
Data Source
AI summary
In an automated leads-and-bids matching system, bid profiles are defined to describe desires of lead buyers. Received leads are matched to active ones of the bid profiles whose specifications the leads substantially match. Lead segmentation data is captured on-the-fly for example by inducing potential consumers to navigate their way through tree-organized web sites that categorize the consumers according to their geographic location, income/revenue range, class of products desired and/or other attributes. Live voice or other telecommunication connections to the pre-classified consumers are coupled to corresponding, pre-classified telecommunication nodes of a call processing system. The call processing system deduces the segmentation data of the consumers from the identities of the pre-classified nodes through which their connections pass. The deduced segmentation data is passed to an automated matching system or auctioning subsystem that finds the highest bids for each given lead.