IVR System Predicts Caller Data From Prior Calls
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Solution Overview
Problem
Conventional IVR systems often require callers to repeatedly provide information, leading to frustration and inefficiency, especially when callers need to access similar information multiple times, as they struggle to recall or accurately input long alphanumeric codes, resulting in misrecognition errors and prolonged interaction times.
Innovation Solution
An IVR system that predicts information needed to service a call by analyzing data from prior calls, allowing it to prefill or confirm information automatically, reducing the need for callers to re-enter data and streamline the call process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If IVR systems require callers to repeatedly provide information, then information accuracy can be verified, but caller frustration increases and interaction time prolongs
Solution Approach 1:
The system performs preliminary actions by analyzing caller behavior data from prior calls before the current interaction begins. It pre-identifies likely information needs and prepares predictive models, so that when the call occurs, the system can quickly present relevant information or questions without requiring the caller to repeatedly provide the same data, thus reducing interaction time while maintaining accuracy through pre-verified patterns
Solution Approach 2:
The system implements feedback mechanisms by continuously analyzing caller responses and behavior patterns during and across calls. This feedback loop allows the system to adjust its predictions in real-time, verifying information accuracy through pattern recognition while reducing the need for repetitive questioning, thereby shortening interaction time without sacrificing reliability
2Loss of information
If IVR systems require callers to input long alphanumeric codes, then specific information can be retrieved, but misrecognition errors increase
Solution Approach 1:
The system creates copies of caller behavior patterns and historical data from previous interactions. By analyzing these copied data sets, the system can predict what information the caller likely needs and what codes they may be referring to, reducing the need for callers to manually input long alphanumeric codes and thereby decreasing misrecognition errors while still enabling specific information retrieval
Solution Approach 2:
The system replaces the mechanical input process (caller manually entering codes) with an automated prediction system that uses behavioral analysis and pattern recognition. This substitution eliminates the errors associated with manual code entry while maintaining the ability to retrieve specific information, as the system automatically identifies and processes the relevant data based on predicted caller intent
3Loss of information
If IVR systems use traditional call flow navigation, then all information can be gathered, but caller burden increases
Solution Approach 1:
The system extracts and prioritizes only the most relevant information needs based on predictive analysis of caller behavior. Instead of forcing callers through complete traditional call flows, the system identifies and addresses only the essential information requirements, removing unnecessary steps and reducing caller burden while still gathering sufficient information to service the call effectively
Solution Approach 2:
The system applies partial action by gathering only the necessary subset of information needed to service the call, rather than requiring complete information collection through full call flow navigation. The predictive analysis determines the minimum viable information set required, reducing caller burden while maintaining information completeness for effective call servicing
Data Source
AI summary
A call from a caller to an interactive voice response (IVR) system may be serviced based on behavior by the caller in one or more prior calls to the IVR system. The call may be serviced by predicting information to be used in servicing the call. Predicting such information may include analyzing data reflecting behavior by the caller in one or more prior calls to the IVR system.


