Customer Service Analytics for Call Deflection and Chat Conversion
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Solution Overview
Problem
Current customer service technologies fail to effectively reduce phone contact volumes despite investments in self-service tools due to generic, knowledge-based approaches that are not customized, leading to inadequate online problem resolution and increased costs.
Innovation Solution
A computer-implemented technique that incorporates analytics into customer data to optimize call deflection strategies, convert telephone calls into online chats, and manage wait times, using IVR messages, intuitive Web page designs, and proactive chat invitations to increase chat acceptance rates and minimize costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If generic knowledge-based self-service tools are used, then implementation cost is reduced, but customer satisfaction and problem resolution effectiveness deteriorate
Solution Approach 1:
The patent applies local quality by customizing self-service content for specific customer segments based on their profiles, behaviors, and needs. Instead of generic knowledge bases, the system delivers tailored recommendations and solutions matched to individual customer characteristics, thereby improving problem resolution effectiveness without proportionally increasing implementation costs.
Solution Approach 2:
The system performs preliminary action by proactively reaching out to customers with customized self-service content before they encounter problems or contact support. Analytics predict customer needs and deliver relevant solutions in advance, preventing issues before they require human intervention and improving resolution effectiveness.
2Ease of manufacture
If more self-service tools are invested, then cost is reduced, but phone contact volumes remain high due to inadequate online resolution
Solution Approach 1:
The patent implements feedback loops where customer interactions with self-service tools are continuously monitored and analyzed. Analytics systems learn from customer behavior patterns and refine content delivery, ensuring that self-service investments effectively reduce phone contacts by addressing actual customer needs rather than deploying generic solutions.
Solution Approach 2:
The system dynamically changes parameters such as content delivery timing, channel selection, and personalization level based on real-time analytics. This adaptive approach optimizes the effectiveness of self-service investments, maximizing phone contact reduction by delivering the right content at the right time to the right customers.
3Productivity
If call deflection strategies are implemented, then phone contact volumes are reduced, but customer satisfaction may deteriorate if alternatives are inadequate
Solution Approach 1:
The patent uses personalized chatbots and virtual assistants as intermediaries to bridge customers and self-service content. These intelligent mediators guide customers through customized resolution paths, ensuring that call deflection strategies maintain high customer satisfaction by providing adequate, tailored support alternatives rather than generic self-service options.
4Reliability
If customized analytics-based strategies are used, then customer satisfaction is improved, but device complexity and implementation cost increase
Solution Approach 1:
The patent implements a unified analytics platform that performs multiple functions: customer profiling, behavior analysis, content recommendation, and channel optimization. This multi-functional system consolidates complexity into a single infrastructure that delivers customized strategies across multiple touchpoints, improving customer satisfaction without proportionally increasing overall system complexity.
Data Source
AI summary
A method and apparatus for a computer-implemented technique for maximizing customer satisfaction and first call resolution, including converting telephone calls into online chats, while minimizing cost is provided. Techniques for incorporating analytics as applied to customer data into particular strategies for call deflection, targeting particular individuals to increase chat acceptance rate, and computing a customer's wait time are also provided.


