Anticipating User Interaction in Contact Center Systems
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Solution Overview
Problem
Existing customer contact center systems face inefficiencies due to generic user interfaces and time-consuming data retrieval processes, leading to increased overhead costs and latency during customer interactions.
Innovation Solution
The system anticipates user interactions by preloading relevant data and creating agent desktop sessions based on anticipated customer needs, reducing the need for real-time data retrieval and improving resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a generic user interface with wide variety of data and tools is provided to agents, then agents have access to comprehensive information, but the interface complexity increases and not all features are relevant to every interaction
Solution Approach 1:
The generic user interface is segmented into customized views based on interaction type and agent role. The system divides the comprehensive data and tools into relevant subsets, presenting only the necessary features to each agent during specific interactions, thereby reducing interface complexity while maintaining comprehensive information access when needed.
Solution Approach 2:
The user interface dynamically adapts its complexity and content based on the current interaction context, customer type, and agent credentials. The interface transitions from a static generic view to a dynamic customized view that adjusts in real-time, showing only relevant features and data for each specific situation.
2Loss of information
If data is retrieved from contact center resources during communication session, then agents can access customer information, but the process is time consuming and bandwidth intensive causing latency
Solution Approach 1:
The system performs preliminary actions by pre-fetching and caching customer data, interaction history, and relevant information before the actual communication session begins. This advance preparation ensures that when the agent needs the information, it is already available locally, eliminating retrieval delays and reducing bandwidth consumption during the interaction.
Solution Approach 2:
Instead of retrieving data in real-time during the communication session, the system creates local copies of customer information and interaction data in advance. These copies are stored in the agent's local environment or cached on the server, allowing instant access without repeated queries to the main contact center resources.
3Reliability
If contact center systems provide high quality service and comprehensive tools, then customer service quality improves, but overhead costs increase
Solution Approach 1:
The system implements local quality by providing different levels of service quality and tool access to different agents based on their specific needs, customer types, and interaction contexts. Instead of uniformly providing comprehensive tools to all agents, the system tailors the quality and quantity of resources locally to each agent-customer interaction, reducing overall overhead while maintaining high service quality where necessary.
Data Source
AI summary
A method for preloading a user interface, the method comprising: anticipating, by a processor, an interaction with a customer of a customer contact center; creating, by the processor, an agent desktop session based on this anticipation; storing, by the processor, the agent desktop session in association with information for the customer; detecting, by the processor, an interaction with the customer; identifying, by the processor, an agent of the customer contact center for routing the interaction to the agent; and launching, by the processor, the agent desktop session on an agent device of the identified agent.