Cross-linking Call Metadata for Service Consistency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In call centers, customers often interact with different customer service representatives (CSRs) for each call, leading to inconsistent service due to the lack of a customer history or baseline for understanding the caller's disposition or temperament, as calls are typically treated as isolated events.
Innovation Solution
A Customer Relationship Management (CRM) device aggregates and analyzes call metadata across various call agents, creating caller profiles that include behavioral patterns, personality, and temperament, enabling CSRs to recognize deviations and provide improved interactions by cross-linking events and interactions across different calls, call centers, and services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If calls are treated as isolated events with different CSRs assigned to each call, then call center operational flexibility is maintained, but service consistency and customer understanding deteriorate
Solution Approach 1:
The system performs preliminary actions by capturing and storing call metadata (voice prints, caller ID, call details) during each interaction. This pre-processing of information creates a foundational database that enables consistent customer identification and profiling across multiple calls, resolving the contradiction by preparing data in advance rather than requiring complex real-time analysis
Solution Approach 2:
The patent introduces an intermediary CRM device that acts as a mediator between the call center system and customer data. This intermediary captures metadata, creates caller profiles, and cross-links calls across different CSRs and call centers, enabling service consistency without requiring direct complex integration between all system components
2Loss of information
If a centralized system aggregates and analyzes call metadata across multiple call centers, then caller profiling and service quality improve, but information processing complexity and data management burden increase
Solution Approach 1:
The system extracts only the essential and relevant metadata from calls (voice prints, caller ID, basic call details) rather than processing entire call recordings or all possible data points. This extraction approach preserves critical caller identification information while minimizing data processing complexity and management burden
Solution Approach 2:
The CRM device is designed with multi-functionality, serving as a universal platform that can aggregate data from multiple call centers, create caller profiles, cross-link calls, and provide reporting all through a single system. This universal approach consolidates data management functions rather than requiring separate systems for each task
3Adaptability or versatility
If caller profiles are created by aggregating metadata from multiple calls and call centers, then customer understanding and service personalization improve, but data aggregation time and processing resources increase
Solution Approach 1:
The system implements continuous data aggregation where call metadata is captured and added to caller profiles in real-time or near-real-time as calls occur. This continuous process eliminates the need for periodic batch processing, allowing the system to maintain up-to-date caller profiles without significant data aggregation delays while enabling ongoing service adaptability
Data Source
AI summary
A device for determining a behavioral deviation for an individual. The device includes a memory and a processor. The memory may store instructions. The processor may be coupled to the memory. When the processor executes the instructions, the processor may: generate a profile for a first individual using data associated with an identifier for the first individual, wherein the profile comprises behavioral information that matches a characteristic of the data; receive, from a first electronic device, a first multimedia item representing a first communication by the first individual; determine that a characteristic of the first multimedia item does not match the characteristic of the data; and send a first notification to a second electronic device indicating that a behavior of the first individual deviated from the behavioral information of the profile.