At-Risk Customer Text Chat Proactive Engagement

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Solution Overview

Problem

Current text chat systems for customer service lack the ability to proactively identify and engage at-risk customers who are likely to terminate their relationship with an entity, relying on generic business rules that do not effectively target specific behaviors indicative of attrition.

Innovation Solution

Implementing an algorithmic 'at-risk' flag based on customer characteristics and behaviors, such as account activity and online interactions, to proactively offer text chat invitations to customers who exhibit traits common among those who close accounts, using an electronic information processing platform to monitor and flag at-risk customers for targeted engagement.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If generic business rules are used to determine chat invitations, then the system is simple to implement, but the ability to identify at-risk customers is insufficient

Engineering Contradiction:

Improveaccuracy of identifying at-risk customersVSAvoidcomplexity of monitoring and flagging system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary analysis of customer navigation patterns and establishes at-risk flags before the customer actually terminates their relationship. By monitoring online behaviors such as time spent on specific pages, number of pages visited, and navigation paths, the system proactively identifies at-risk customers and triggers chat invitations before attrition occurs, rather than reacting after the relationship has ended

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary classification layer between generic business rules and chat invitation decisions. The system uses online behavior monitoring as an intermediary mechanism that translates raw navigation data into meaningful at-risk indicators, which then inform chat invitation decisions. This intermediary layer enables more precise identification without requiring complete system redesign

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If online behavior monitoring is implemented to identify at-risk customers, then customer attrition can be reduced, but the system complexity increases

Engineering Contradiction:

Improveeffectiveness in retaining customer relationshipsVSAvoidcomplexity of behavior monitoring platform

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system implements partial monitoring by focusing only on specific, high-value online behaviors that are most indicative of attrition risk, rather than monitoring all possible customer actions. Key metrics include time spent on specific pages, number of pages visited within a timeframe, and particular navigation patterns. This selective approach provides sufficient reliability for identifying at-risk customers while keeping the monitoring system manageable and avoiding excessive complexity

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system enables self-service by automatically monitoring customer navigation patterns and autonomously determining at-risk status without requiring manual intervention. The electronic information processing platform continuously tracks online behaviors, applies classification rules, and automatically generates chat invitations for at-risk customers, reducing the need for manual system management and complex configuration

Inventive Principle:

Principle #25Self-service

3Loss of time

If proactive chat invitations are sent to at-risk customers, then attrition is reduced, but the timing and targeting precision must be improved

Engineering Contradiction:

Improvetime to intervene before customer leavesVSAvoidprecision in identifying at-risk behaviors

Core Design Contradiction:

Loss of timeVSMeasurement precision

Solution Approach 1:

The system implements continuous feedback loops where customer navigation behaviors are monitored in real-time, immediately triggering re-evaluation of at-risk status when specific patterns are detected. When a customer exhibits behaviors such as spending excessive time on particular pages or navigating through exit-oriented paths, the system provides immediate feedback by updating the at-risk classification and promptly sending chat invitations, minimizing the time loss before intervention

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary identification of at-risk customers by analyzing navigation patterns before the customer actually leaves. By establishing classification rules that detect early warning signs such as specific page visit sequences, time spent on critical pages, and navigation depth, the system proactively flags at-risk customers and initiates chat invitations in advance, allowing timely intervention before attrition occurs

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS8452841B2Text chat for at-risk customers

Publication Date: 2013.05.28 BANK OF AMERICA CORP

AI summary

Apparatus and methods for supporting text chat for at-risk customers are provided. A method for operating an electronic information processing platform may include receiving, via the electronic information processing platform, information indicating that a customer exhibits behavior indicative of a desire to terminate a relationship with an entity. The method may further include, transmitting to the customer a text chat invitation, via the electronic information processing platform, in response to the received information.