Mobile Self-Service Client for Wireless Customer Assistance
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Solution Overview
Problem
Mobile communication device users often face difficulties with self-service systems for resolving issues related to their wireless communication services, leading to frustration and decreased customer satisfaction, as they struggle to navigate through complex processes without effective assistance.
Innovation Solution
A system and method that processes historical and current self-service events on a mobile communication device to provide targeted customer assistance by analyzing event information, determining relevant customer service categories, and automatically connecting users to appropriate support channels via embedded APIs or chat sessions, thereby streamlining the support process and improving user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users attempt to resolve issues using a self-service portal, then they can access customer service information, but they become confused and fail to resolve the issue
Solution Approach 1:
The system continuously monitors user interactions with the self-service portal and provides real-time feedback by analyzing event information (dwell time, error codes, page reloads) to determine when assistance is needed and routing users to appropriate customer service groups
Solution Approach 2:
The self-service client acts as an intermediary between the user and the complex self-service portal, automatically analyzing user behavior patterns and mediating the interaction by selecting appropriate assistance routes based on trigger signatures
2Loss of information
If users struggle to navigate complex self-service processes, then they can access detailed service information, but frustration increases and customer satisfaction decreases
Solution Approach 1:
The system monitors user frustration indicators (dwell time, error codes, page reloads) and provides feedback by automatically routing to appropriate customer service groups when trigger signatures are detected
Solution Approach 2:
The self-service client automatically analyzes user behavior and makes decisions about assistance routing without requiring user input, allowing the system to serve itself in identifying when help is needed
3Ease of operation
If the system provides targeted customer assistance based on event analysis, then customer satisfaction improves, but system complexity increases
Solution Approach 1:
The system segments customer service into distinct categories with dedicated phone numbers and routing logic, allowing complex assistance to be divided into manageable segments that can be automatically routed based on trigger signatures
Solution Approach 2:
The self-service client automatically performs analysis of event information and decision-making for assistance routing without requiring complex user interaction or manual configuration, reducing the operational complexity burden on users
4Productivity
If the system automatically analyzes and routes users based on trigger signatures, then assistance efficiency improves, but processing requirements increase
Solution Approach 1:
The system performs partial analysis by focusing only on specific event information (dwell time, error codes, page reloads) and trigger signatures rather than processing all possible user interactions, reducing processing requirements while maintaining effectiveness
Data Source
AI summary
A system for providing targeted customer assistance to a wireless communication service subscriber comprising a mobile communication device comprising a processor; a display, a non-transitory memory, a radio transceiver, and a self-service client application. The client application comprises trigger signatures and phone numbers related to categories of customer service. The client application initiates a self-service session generates a key associated with the service subscriber, locates a log using the key, records current self-service event information, analyzes the self-service event information, wherein analyzing comprises at least determining a category of customer service of the event information. In response to the event information matching at least one trigger signature, selects a phone number associated with the category of customer service, presents the phone number via an embedded API, and calls a group associated with the category by invoking an embedded API of a dialer, wherein the log is transmitted to the group.