Balanced Service Process for Contact Center FCR and CSAT
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Solution Overview
Problem
Current customer relationship management (CRM) systems fail to accurately measure and maximize first call or contact resolution (FCR) and customer satisfaction (CSAT) due to insufficient tools and lack of a detailed process, leading to confusing processes, low staff morale, high attrition, and lost customers.
Innovation Solution
A balanced service process that generates real-time, intraday, and historical FCR and CSAT statistics, provides dynamic reporting of issues, analyzes unresolved contacts, and aligns customer and agent perceptions of disposition through a closed loop channel, using automated Response Codes and analytics to identify trends and implement targeted actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If customer surveys are used to measure customer experience, then customer satisfaction data can be collected, but only about 3 out of 100 survey solicitations are useful for coaching
Solution Approach 1:
The system performs preliminary actions by automatically analyzing call recordings and agent responses before customer surveys are sent. The system pre-processes call data to identify resolution status and satisfaction indicators, so when surveys are sent, they are targeted more effectively. This preliminary analysis ensures that only high-value survey responses are sought, improving the ratio of useful responses from 3 to potentially much higher.
Solution Approach 2:
The system implements continuous feedback loops where agent responses to survey questions are automatically reviewed and validated. The system provides real-time feedback to agents about their responses and the actual customer sentiment detected through call analysis. This feedback mechanism ensures higher accuracy in measurement and reduces the need for follow-up surveys, improving the effectiveness of each survey solicitation.
2Reliability
If comprehensive customer engagement centers are implemented, then customer interactions can be managed effectively, but system complexity and implementation cost increase
Solution Approach 1:
The system extracts and focuses on the most critical component of customer engagement: the survey response validation process. Rather than implementing a complete complex engagement center, the system isolates and optimizes the specific function of measuring customer satisfaction through validated survey responses. This extraction approach achieves reliability improvement without requiring the full complexity of comprehensive engagement centers.
Solution Approach 2:
The system enables self-service through automated analysis of call recordings and agent responses. The system automatically determines resolution status, validates survey responses, and provides coaching recommendations without requiring complex manual processes. This automation reduces the need for complex system infrastructure while maintaining high reliability in customer interaction management.
3Measurement precision
If agents manually respond to survey questions, then customer satisfaction can be measured, but measurement accuracy is compromised due to agent bias
Solution Approach 1:
The system introduces an intermediary analysis layer between the customer call and the survey response validation. This intermediary component automatically analyzes call recordings, agent responses, and customer interactions to objectively determine satisfaction status. This intermediary function eliminates agent bias in measurement by using automated, objective analysis criteria rather than subjective agent judgments, thereby improving both measurement precision and customer perception accuracy.
Solution Approach 2:
The system replaces the mechanical manual validation process with automated electronic analysis. Instead of relying on agents to subjectively evaluate survey responses, the system uses automated algorithms that analyze call data, agent responses, and customer interaction patterns. This substitution of mechanical manual processes with automated electronic systems eliminates human bias while maintaining comprehensive measurement capability, improving both precision and accuracy of customer satisfaction measurement.
Data Source
AI summary
A system, method, and computer program product for customer contact management via voice, chat, e-mail and social network contacts includes a balanced service process (BSP) that includes a plurality of cause or response codes for maximizing first contact resolution (FCR) and CSAT. The BSP is incorporated within a contact center (single center, multiple centers and/or work at home), which receives voice calls, SMS messages, email, chat, or social media communications from customers. The BSP in real-time determines dispositions of such contacts, monitors and manages the performance of individual resolvers.