Contact Center Overflow Routing Using Dynamic Expert Matching

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Solution Overview

Problem

Existing electronic communication systems in call centers struggle to accurately identify and match experts with customer inquiries, as they rely on static databases that may not capture all areas of expertise and often require manual input, leading to inefficiencies and increased wait times for customers during busy periods.

Innovation Solution

An automated electronic communication system that uses expert and agent term extraction engines, coupled with a matching engine, to dynamically identify and match expertise from electronic communications, allowing for real-time identification and connection of suitable experts, even beyond traditional job functions, and optionally routes inquiries to back office staff during high demand.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If all customer inquiries are directed first to contact center personnel, then customers receive initial support, but wait times increase during busy periods

Engineering Contradiction:

Improvecustomer service availabilityVSAvoidcustomer wait time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system segments the expert pool into contact center personnel and back office personnel, creating separate queues and routing mechanisms. This allows inquiries to be distributed across multiple groups based on availability and expertise, preventing all customers from waiting for contact center agents alone.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The automated routing system acts as an intermediary that intelligently directs inquiries between contact center personnel and back office personnel. It monitors queue lengths, availability, and expertise matches to dynamically route customers to the most appropriate available resource, reducing overall wait times.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of manufacture

If static expert databases are used for matching, then implementation is simple, but expertise information becomes outdated and incomplete

Engineering Contradiction:

Improvesystem implementation simplicityVSAvoidexpertise information accuracy

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The system transitions from static expert databases to dynamic profiles that automatically update based on observed behavior. Expertise information is continuously refined by analyzing communication patterns, successful resolutions, and interaction data, ensuring the database remains current without manual intervention.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements feedback loops where outcomes of expert-customer interactions are automatically captured and used to update expertise profiles. Successful resolutions reinforce identified expertise areas, while missed opportunities trigger profile adjustments, continuously improving matching accuracy.

Inventive Principle:

Principle #23Feedback

3Ease of operation

If manual expert directory review is required, then agents can select experts, but the process is time-consuming and lacks guidance

Engineering Contradiction:

Improveagent control over expert selectionVSAvoidexpert identification time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system provides self-service matching where the automated engine performs the expert identification and presentation based on the customer inquiry. Agents receive pre-filtered, ranked lists of recommended experts with relevant expertise indicators, eliminating the need for manual directory searching while maintaining agent oversight.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces the manual mechanical process of directory review with an automated computational matching engine. The engine analyzes inquiry content, compares against expert profiles, and generates recommendations automatically, substituting human manual search efforts with algorithmic processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Adaptability or versatility

If expertise is limited to traditional job functions, then role definitions remain clear, but the system cannot identify suitable experts outside defined roles

Engineering Contradiction:

Improveexpertise matching flexibilityVSAvoidexpertise identification complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system moves from fixed role-based expertise definitions to dynamic behavior-based profiles. Expertise is determined by observed communication patterns, successful resolutions, and interaction outcomes rather than static job descriptions, allowing the system to identify capable experts regardless of their formal role definitions.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS11818296B2Method to supply contact center resources during overflow state using back office personnel

Publication Date: 2023.11.14 MITEL CORP

AI summary

A method and system matching contact center agents and back office staff with a customer inquiry. Exemplary systems include an expert term extraction engine, a customer term extraction engine, and a matching engine to compare customer request terms to the expert terms from the customer term extraction engine. The comparison determines whether there is a match or potential match between the customer request terms and the stored expert terms. An exemplary system may also include a timer that communicates with one or more communication servers. Back office staff may assist contact center agents when one or more conditions are met, such as when a customer wait time exceeds a predetermined period or when there is no match or potential match between the customer request terms and the stored expert terms for contact center agents.