AI Lead Routing System for Persistent Agent Connection
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Solution Overview
Problem
Current lead generation and routing systems are inefficient in connecting users with appropriate agents for additional product or service discussions, particularly when the referral location cannot offer the desired product or service, such as insurance, leading to missed sales opportunities.
Innovation Solution
An AI system that requests user consent for messaging and generates a lead profile to automatically connect users with relevant agents through AI-driven messaging, using machine-readable instructions and neural network models to route users based on their preferences and demographics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional lead routing systems are used where leads contact call centers and are manually routed to agents, then the system structure is simple and easy to operate, but the efficiency is low and time-consuming
Solution Approach 1:
The patent replaces manual mechanical routing processes with an AI-based automated system that uses machine learning models to route leads to appropriate agents. The system automatically analyzes lead data, determines optimal agent matching, and executes routing decisions without human intervention, thereby significantly improving productivity while managing complexity through automation.
Solution Approach 2:
The patent introduces an AI intermediary system that acts as a mediator between leads and agents. This AI component processes lead information, applies routing logic, and facilitates connections without requiring manual call center intervention. The intermediary handles the complex matching process, allowing the overall system to achieve high efficiency while keeping the user interface simple.
2Productivity
If referral locations cannot offer additional products or services (such as insurance), then customers can still access the referral location for primary services, but sales opportunities are lost
Solution Approach 1:
The patent implements preliminary action by capturing lead information and obtaining consent at the referral location before the customer leaves. The system proactively identifies potential leads, stores their contact information, and sets up automated follow-up sequences. This preliminary capture of leads ensures that sales opportunities are not lost even when the referral location cannot immediately provide additional products or services.
Solution Approach 2:
The patent ensures continuity of useful action through automated follow-up messaging sequences that continue to engage leads after they leave the referral location. The system sends timely, relevant messages to nurture leads and convert them into customers, maintaining the sales process continuously rather than stopping when the referral location's service offering is exhausted.
3Productivity
If automated AI messaging is sent to leads, then the system can persistently present connection options and improve conversion rates, but the complexity of implementation increases
Solution Approach 1:
The patent implements self-service by designing an automated messaging system that operates independently once configured. The AI system automatically sends messages, tracks responses, manages follow-up sequences, and updates routing decisions without requiring continuous manual intervention. This self-service capability allows the system to maintain high conversion rates while reducing the operational complexity of managing the messaging process.
4Reliability
If user consent is requested for AI-based messaging, then customer privacy is protected and compliance is improved, but the process requires additional steps
Solution Approach 1:
The patent applies preliminary action by obtaining user consent early in the process, before any automated messaging begins. The system captures consent information during the initial lead capture phase at the referral location, ensuring compliance requirements are met before the automated sequence starts. This upfront consent collection protects privacy while allowing the rest of the process to proceed smoothly.
Data Source
AI summary
Systems and methods for messaging a user include one or more processors, one or more memory components, and machine readable instructions that cause the AI system to perform at least the following when executed by the one or more processors: request a consent input from a user, receive the consent input from the user, send a message to a mobile device of the user, responsive to the user selecting an option of being connected to the agent, and responsive to the user not selecting the option of being connected to the agent, and send one or more further messages presenting the user with the option of being connected to the agent on a pre-determined schedule until (i) a pre-determined duration of time expires or (ii) the user selects the option of being connected to the agent within the pre-determined duration of time.