Support Call Routing via Historical Interaction Analysis
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Solution Overview
Problem
Existing customer support systems often fail to effectively manage unresolved interactions, leading to customer frustration due to dropped calls, delayed assistance, and recurring issues, which can strain the interaction between customers and service agents.
Innovation Solution
A method within a support call management system that identifies customer interactions, retrieves historical data, determines call relationships, and routes calls to appropriate agents, experts, or supervisors based on call characteristics to manage unresolved interactions efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If customer support systems use traditional call routing without historical data analysis, then call routing is simple and fast, but unresolved interactions are not effectively managed leading to customer frustration
Solution Approach 1:
The system performs preliminary actions by retrieving and analyzing historical interaction data before routing the current support call. This allows the system to proactively identify unresolved issues and prepare appropriate routing decisions, ensuring that customers are connected to agents who can effectively resolve their specific problems based on past interactions.
Solution Approach 2:
The system implements feedback mechanisms by continuously analyzing historical interaction outcomes and using this information to improve call routing decisions. The feedback loop encompasses retrieving past interaction data, evaluating resolution effectiveness, and adjusting routing strategies to connect customers with more suitable agents based on learned patterns from previous interactions.
2Measurement precision
If the system analyzes historical interaction data and determines call relationships, then call routing accuracy improves, but processing time increases
Solution Approach 1:
The system applies partial action by selectively analyzing only the most relevant historical interaction data rather than processing complete historical records. This approach retrieves and evaluates key interaction patterns and unresolved issues from past calls, achieving sufficient routing accuracy without the computational overhead of comprehensive historical analysis.
3Measurement precision
If multiple support call queues are maintained for different interaction types, then call routing precision improves, but queue management complexity increases
Solution Approach 1:
The system implements universality by creating support call queues that can handle multiple interaction types and unresolved issue categories. Rather than requiring separate queues for each specific interaction type, the queues are designed to be multi-functional, capable of managing diverse customer issues through flexible routing criteria that evaluate historical data patterns.
Data Source
AI summary
Technologies for managing unresolved customer interactions in a support call management system are disclosed, including receiving a support call from a customer; identifying a customer and a support call type; retrieving historical interaction data associated with the customer; determining subsequent to having determined that historical interaction data associated with the customer includes other support calls, whether the other support calls are related to the received support call based in part on the historical interaction data and the support call type; determining whether to transmit the support call to an agent, an expert, or a supervisor as a function of at least one characteristic of the other support calls; and placing the support call into a support call queue as a function of the determination of whether the support call is to be transmitted to one of the agent, the expert, or the supervisor.