Context-Driven Support Recommendations From Device Log Analysis
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Solution Overview
Problem
Customers often encounter lengthy and inefficient technical support sessions due to TS entities' lack of awareness about the system configuration and state of their computing devices, leading to unsatisfactory experiences and reduced likelihood of future interactions.
Innovation Solution
A proactive, runtime, and computing device context-based approach that analyzes log files to extract relevant data, determines previously applied steps, and displays appropriate next steps on a graphical user interface for the TS entity, ensuring awareness of the system configuration and state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If technical support entities conduct detailed conversations to understand customer issues, then solution accuracy improves, but conversation length increases
Solution Approach 1:
The system performs preliminary analysis by automatically collecting and analyzing device logs, system configurations, and error messages before the technical support conversation begins. This preliminary action provides the TSS with pre-prepared diagnostic information and potential solutions, eliminating the need for lengthy information-gathering conversations while maintaining high solution accuracy.
Solution Approach 2:
An automated log analysis system acts as an intermediary between the customer's device and the technical support entity. This intermediary continuously monitors device state, collects relevant logs, and presents processed information to the TSS, reducing the need for direct questioning and enabling faster, more accurate support interactions.
2Adaptability or versatility
If technical support entities gather comprehensive device information, then solution relevance improves, but system complexity increases
Solution Approach 1:
The system implements self-service capabilities where the device automatically generates and transmits relevant logs and configuration data to the technical support platform without requiring manual intervention. This self-service approach enables comprehensive device information gathering while keeping the system architecture relatively simple through automated processes.
Solution Approach 2:
The log analysis system is segmented into modular components that independently handle different aspects of device information collection (system logs, application logs, configuration files, error messages). Each module operates autonomously and contributes specific data types, making the overall system manageable despite its comprehensive information-gathering capabilities.
3Productivity
If technical support conversations are kept short, then productivity improves, but customer experience deteriorates
Solution Approach 1:
The system implements continuous feedback loops where device logs are monitored in real-time, and the technical support platform receives automated updates on device state changes, solution effectiveness, and customer interactions. This feedback mechanism enables short, efficient conversations while maintaining customer experience through proactive issue detection and resolution tracking.
Solution Approach 2:
By performing preliminary diagnostic analysis and preparing potential solutions before customer contact, the system enables technical support representatives to provide accurate, targeted assistance in brief interactions. This preliminary preparation ensures that even short conversations deliver high-value, personalized support that maintains customer satisfaction.
Data Source
AI summary
A method for managing a technical support (TS) conversation includes: obtaining, in response to a TS request from a user of a client device, a log file associated with an application executing on the client device, in which the TS request specifies a hardware component failure on the client device; analyzing the log file to extract relevant data; obtaining, based on the relevant data, a fix from a solution service, in which the fix includes a plurality of steps; analyzing the log file to make a first determination that a first step of the plurality of steps has previously been applied to the client device; and initiating, based on the first determination, display of a second step of the plurality of steps on a graphical user interface (GUI) accessible to a TS entity, in which the second step has not been applied to the client device.