Real-time Widget Prioritization via Local Cache for Agent Query Response
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Solution Overview
Problem
Enterprise organizations face challenges in providing real-time, accurate, and efficient responses to customer queries across large knowledge domains, often struggling to optimize network resources and reduce latency while ensuring timely and targeted responses.
Innovation Solution
A computing platform that detects voice-based interactions, transforms audio data into textual data, identifies customer queries, and retrieves relevant widgets from a repository, prioritizing them based on historical data and real-time interactions to display them on a graphical user interface, with the ability to self-arrange and update widgets dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time retrieval of widgets from a central repository is performed, then response accuracy is improved, but network latency and response time increase
Solution Approach 1:
The patent pre-loads relevant widgets from the central repository into a local cache before they are actually needed during customer service interactions. This preliminary action stores frequently accessed or potentially needed widgets locally, so when a customer query arises, the system can immediately retrieve relevant information from the local cache without waiting for network requests to the central repository, thus reducing network latency while maintaining response accuracy.
2Reliability
If comprehensive widget information is displayed to agents, then customer service quality is improved, but information overload and processing complexity increase
Solution Approach 1:
The patent applies local quality by prioritizing and selectively displaying widgets based on their relevance to the specific customer query and interaction context. Instead of displaying all available widget information uniformly, the system assigns different priorities to different widgets and presents only the most relevant ones to the agent at the appropriate moment. This reduces information overload while maintaining comprehensive coverage of necessary information, thereby improving customer service quality without overwhelming the agent.
Solution Approach 2:
The patent implements dynamic widget prioritization and display based on real-time interaction context. The system continuously monitors the customer-agent interaction and dynamically adjusts which widgets are displayed and in what order, based on the evolving conversation context, customer queries, and interaction history. This dynamic adaptation ensures that agents receive the most relevant information at each moment without being overwhelmed by static, comprehensive lists of all possible widgets.
3Speed
If multiple widgets are pre-loaded into local cache, then response speed is improved, but network bandwidth utilization increases
Solution Approach 1:
The patent applies partial action by selectively pre-loading only the most relevant widgets into the local cache based on predicted customer queries and interaction patterns, rather than caching all possible widgets. The system uses widget prioritization algorithms to determine which widgets are most likely to be needed and pre-loads only those, achieving sufficient response speed improvement while minimizing unnecessary network bandwidth consumption.
4Measurement precision
If widget priority scoring is continuously updated in real-time, then widget relevancy is improved, but computational resources and processing time increase
Solution Approach 1:
The patent implements periodic updates of widget priority scores rather than continuous real-time updates. The system updates widget priorities at specific intervals or triggered by certain events (such as completing a customer interaction or detecting significant changes in interaction patterns), rather than continuously recalculating priorities during every moment of every interaction. This periodic approach maintains adequate widget relevancy while significantly reducing the computational resource burden compared to continuous updates.
Data Source
AI summary
Aspects of the disclosure relate to real-time knowledge-based widget prioritization and display. A computing platform may detect, via a computing device, a voice-based interaction between an enterprise agent and a customer. Then, the computing platform may cause, via the computing device, the voice-based interaction to be captured as audio data. The computing platform may then transform the audio data to textual data. Subsequently, the computing platform may identify, in the textual data, a customer query. Then, the computing platform may retrieve, in real-time and based on the voice-based interaction and from a repository of widgets, a first widget, where the first widget includes information at least partially responsive to the customer query. Then, the computing platform may display, to the enterprise agent and via a graphical user interface in use by the enterprise agent, the first widget.