Outbound Call Scheduling Using Confidence Scores
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Solution Overview
Problem
Existing systems for managing outbound calls lack efficiency in identifying reliable phone numbers and determining optimal call schedules, leading to increased resource expenditure and reduced success rates in contacting users.
Innovation Solution
A system that determines confidence scores for phone numbers based on historical call data and attributes, ranks these numbers, and generates a daily call schedule to maximize successful contacts, thereby reducing manual efforts and resource wastage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to identify reliable phone numbers and determine call schedules, then system complexity is reduced, but productivity and success rate deteriorate
Solution Approach 1:
The system automatically performs phone number verification, confidence scoring, and call schedule generation without requiring manual intervention. The automated verification system independently evaluates phone numbers against multiple criteria and generates optimal call schedules, eliminating the need for manual phone number validation and scheduling while significantly improving productivity
Solution Approach 2:
The system performs preliminary verification and scoring of phone numbers before actual calling occurs. By pre-calculating confidence scores and determining optimal call schedules in advance, the system prepares all necessary information beforehand, allowing agents to execute calls efficiently without on-the-spot decision-making, thus improving productivity without requiring complex real-time systems
2Reliability
If more phone numbers are contacted without prioritization, then coverage increases, but resource expenditure increases
Solution Approach 1:
The system applies different treatment to different phone numbers based on their individual confidence scores and characteristics. Rather than uniformly contacting all numbers, the system prioritizes high-confidence numbers for immediate calling while deferring or eliminating low-confidence numbers, thereby optimizing resource allocation to where it is most effective and improving contact success rates
Solution Approach 2:
The system dynamically adjusts calling parameters such as call frequency, timing, and priority based on calculated confidence scores and account status. By changing these parameters adaptively rather than using fixed schedules, the system maximizes resource efficiency - concentrating efforts on high-probability contacts while reducing or eliminating low-value calls, thus improving success rates without proportionally increasing resource expenditure
3Productivity
If call schedules are determined without data analysis, then ease of operation increases, but productivity deteriorates
Solution Approach 1:
The system continuously analyzes historical call data, account status changes, and phone number performance to dynamically adjust call schedules. This feedback mechanism ensures that scheduling decisions are data-driven and adaptive, improving productivity by optimizing contact timing and frequency based on actual performance patterns rather than using static or manual schedules
Solution Approach 2:
The system replaces manual scheduling operations with automated algorithms that process account data and historical call information to generate optimal call schedules. By substituting mechanical manual scheduling with automated computational processes, the system achieves superior scheduling efficiency while maintaining ease of operation through automated decision-making rather than requiring complex manual coordination
Data Source
AI summary
In some implementations, a system may identify, based on an account status of an account, one or more phone numbers associated with the account. The system may determine a confidence score of each phone number, based on historical call data and one or more phone number attributes, a rank of the phone number(s) based on corresponding confidence scores, and a quality score for each phone number based on a relative comparison of confidence scores of phone numbers of at least a subset of a plurality of users. The system may determine a daily call schedule, which may include a total frequency to call the user, based on the account status, a phone number frequency to call each phone number, based on one or more conditions related to corresponding quality scores, and a call order in which to call each phone number, based on the rank of the phone number(s).