Call Management Server Data Analysis for Context Preservation
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Solution Overview
Problem
Current call management systems fail to efficiently analyze, filter, and present prior conversation data to customer service representatives, leading to repetitive information exchange and lack of context in ongoing issues, as they do not perform computational analysis before the representative speaks with the customer.
Innovation Solution
Implementing a data analysis module within the call management server that gathers and analyzes account identifier and conversation topic information, retrieves relevant prior conversation data within a predetermined time frame, filters and summarizes it, and presents this information to the CSR before the call, enabling seamless integration across channels like voice calls and chats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the call routing system uses random routing to the next available customer service representative, then the system is simple to operate and representatives are easily utilized, but the customer loses context from prior conversations and must repeat information
Solution Approach 1:
The system performs preliminary actions by analyzing and retrieving prior conversation data before routing the customer to a representative. The server identifies customers with ongoing issues and proactively prepares their conversation history, making the information available to the assigned representative before the call begins, thus preventing information loss without complicating the routing process
Solution Approach 2:
The server acts as an intermediary between the customer and the representative. It retrieves and analyzes prior conversation data, then provides this information to the representative through the customer service interface. This intermediary function preserves conversation context without requiring changes to the simple routing mechanism
2Loss of information
If the system retrieves and presents all prior conversation data to the customer service representative, then the representative gains complete context, but the system complexity and data processing requirements increase
Solution Approach 1:
The system extracts only the relevant portions of prior conversation data needed to understand ongoing issues, rather than presenting all historical data. The server identifies and retrieves specific conversation segments related to unresolved problems, reducing data processing complexity while maintaining complete context for the representative
Solution Approach 2:
The system applies different processing qualities to different data elements. It performs detailed analysis on conversation segments related to ongoing issues while using simpler retrieval methods for routine information. This localized quality approach ensures complete context is provided where needed without uniformly increasing system complexity across all data processing
3Loss of time
If the system analyzes and filters prior conversation data before the call, then the representative receives relevant information promptly, but the data processing time and computational resources increase
Solution Approach 1:
The system performs data analysis and filtering in advance, before the customer call begins. The server identifies ongoing issues and prepares relevant conversation excerpts during the routing process, so the representative receives pre-processed, ready-to-use information without requiring additional processing time during the actual call
Solution Approach 2:
The system performs partial analysis by focusing computational resources only on identifying and extracting information related to ongoing issues, rather than analyzing all conversation data in detail. This selective approach reduces computational energy consumption while still providing the representative with the specific context needed to resolve current problems
Data Source
AI summary
Data analysis, filter, and presentation techniques are described for an example call management system. An example method for a data management system includes receiving, from a user device, an account identifier of a first person, receiving, from the user device, a first message related to a topic of conversation to be discussed during a telephone call with the first person, determining, based on the account identifier and within a pre-determined time period, a presence of a set of data that describes conversation(s) from prior telephone call(s)/chat(s) with the first person, and sending, to a computer, at least some data from the set of data and a second message that indicates that the telephone call is mapped to a second person, where the computer is configured to display on a screen the second message and a presentation option that presents the at least some data via the computer.