Visitor Prioritization System for Live Chat Support
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Solution Overview
Problem
Website operators face challenges in providing effective live, human-assisted support to a large number of visitors due to insufficient agents, necessitating a system to prioritize and group visitors for optimal engagement.
Innovation Solution
A networked communication system that uses experiential data to prioritize visitors based on factors like time spent on pages, browser type, and interaction history, allowing agents to select high-priority visitors for live chat through intuitive interfaces and visual representations, and extends this prioritization to email users based on email activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If live-chat support is provided to all visitors, then visitor experience is improved, but agent resources are insufficient to handle the volume
Solution Approach 1:
The patent segments visitors into different priority groups based on their behavior, demographics, and engagement metrics. This segmentation allows agents to focus on high-priority visitors who are most likely to convert, rather than attempting to serve all visitors equally. The system divides the visitor population into tiers (e.g., high, medium, low priority) and routes them to appropriate support channels or agents.
Solution Approach 2:
The patent changes the parameter of visitor prioritization by introducing multiple scoring dimensions (behavioral metrics, demographic data, engagement level, conversion probability). These parameter changes enable the system to dynamically rank visitors and allocate agent resources to those with the highest potential value, resolving the contradiction between limited agent availability and the need for quality support.
2Reliability
If agents manually review all visitor interactions to prioritize support, then support quality is improved, but time consumption increases
Solution Approach 1:
The patent performs preliminary prioritization actions by automatically analyzing visitor behavior data, demographic information, and engagement metrics before agents need to review interactions. The system pre-calculates priority scores and pre-ranks visitors, so agents receive a pre-sorted list of high-priority visitors rather than having to manually evaluate all interactions. This preliminary automated analysis significantly reduces agent time consumption while maintaining support quality.
Solution Approach 2:
The patent introduces an intermediary automated prioritization system that acts as a mediator between visitor interactions and agent review. This intermediary layer processes and scores visitor data using algorithms that analyze multiple parameters (time on site, pages viewed, demographic matching, conversion history), presenting a filtered and ranked list to agents. This intermediary eliminates the need for agents to manually review all interactions while preserving support quality through intelligent automated filtering.
3Measurement precision
If prioritization criteria are made complex to accurately identify high-value visitors, then conversion accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the prioritization criteria into distinct modular components: behavioral metrics (time on site, pages viewed), demographic data (age, location, device), engagement level (interaction frequency, conversion history), and conversion probability scores. Each segment can be independently configured and weighted, allowing the system to achieve high measurement precision through multiple focused parameters rather than one complex monolithic criterion.
Solution Approach 2:
The patent creates a universal prioritization framework that can accommodate multiple types of criteria (behavioral, demographic, engagement, conversion) within a single unified scoring system. This multi-functional approach allows the same system structure to handle diverse data types and prioritization needs, achieving high accuracy without proportionally increasing system complexity. The unified framework can be configured for different business contexts while maintaining a consistent underlying architecture.
Data Source
AI summary
A networked communication system allows a vendor that maintains a web site to prioritize, select, and establish human-assisted interaction with visitors to the website. The vendor's human help agents are provided with intuitive interfaces that depict visitor priority based on agent-specific ranking rules. Agents can manage these rules to optimize their performance in responding to visitors, and thus improve the quality of visitors' experiences.