Language Interpretation Call Routing for Unanswered Mobile Sessions
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Solution Overview
Problem
Current language interpretation platforms face inefficiencies due to a high rate of unanswered calls from limited English proficiency speakers (LEPs) resulting from unrecognized caller IDs and spam awareness, leading to wasted computing resources.
Innovation Solution
A computer-implemented process that sends a message to the LEP's mobile device offering connection options after an unanswered call, allowing the LEP to recognize the call origin and enabling a callback, and utilizes an outbound calling data structure to optimize future calls based on contact preferences and historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the language interpretation platform places calls to LEPs' mobile devices, then language interpretation service can be provided, but the call answer rate is low due to unrecognized caller IDs and spam awareness
Solution Approach 1:
The system performs preliminary actions by sending a text message notification to the LEP's mobile device before placing the interpretation call. This notification includes the caller ID and purpose of the call, allowing the LEP to recognize and trust the incoming call, thereby increasing the likelihood of answering.
Solution Approach 2:
The system uses a text message notification as an intermediary between the language interpretation platform and the LEP's mobile device. This intermediary provides additional context and identification information that bridges the trust gap caused by spam awareness and unrecognized caller IDs.
2Reliability
If the platform attempts multiple calls to unreachable LEPs, then connection probability increases, but computing resources are wasted on unanswered calls
Solution Approach 1:
The system sends a preparatory text message notification before placing the interpretation call. This preliminary action increases the likelihood of the LEP answering by providing context and identification, thereby reducing the need for multiple retry calls and optimizing resource utilization.
Solution Approach 2:
The system monitors call answer rates and uses this feedback to optimize resource allocation. By tracking which calls are answered and which are not, the system can adjust its calling strategies and resource distribution to maximize connection probability while minimizing waste on consistently unanswered calls.
3Device complexity
If the platform uses traditional calling methods, then implementation is simple, but processing time for successful connections is increased
Solution Approach 1:
The system sends a text message notification in advance of the interpretation call. This preliminary action prepares the LEP to answer by providing context and identification, thereby reducing the time needed to establish a successful connection without significantly increasing system complexity.
Data Source
AI summary
A computer-implemented process receives, at a language interpretation platform from a customer service agent computing device, a request to establish a language interpretation session with a user. In addition, the computer-implemented process places a call from the language interpretation platform to a user mobile computing device. The computer-implemented process, upon the user not answering the call, automatically transmits a message to the user mobile computing device indicating one or more language interpretation connection options. Additionally, the computer-implemented process establishes, via the language interpretation platform, a language interpretation session between the customer service agent computing device, a language interpreter computing device, and the user mobile computing device based on the one or more language interpretation options.