Virtual Cognitive Agents for Personalized Social Media Response

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Solution Overview

Problem

Current social media platforms lack efficient automated systems for real-time, personalized query response services, leading to increased operational costs and reduced customer engagement for businesses.

Innovation Solution

Integration of virtual cognitive agents (VCAs) with machine learning capabilities that analyze user data on social media platforms, providing contextual and personalized responses, and integrating with CRM systems for enriched customer insights.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual customer service handling is used, then personalized service quality is maintained, but operational costs increase and response time is slow

Engineering Contradiction:

Improveresponse timeVSAvoidautomation level

Core Design Contradiction:

ProductivityVSExtent of automation

Solution Approach 1:

The virtual cognitive agent performs self-service by automatically analyzing customer queries, generating appropriate responses, and communicating through social media platforms without requiring manual intervention. The system autonomously handles customer service tasks, reducing the need for human agents while maintaining service quality.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical processing with automated cognitive processing. Instead of human agents manually reading and responding to queries, the system uses machine learning models, natural language processing, and cognitive algorithms to automatically understand, analyze, and respond to customer queries in real-time.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Extent of automation

If automated response systems are implemented, then operational costs are reduced, but response personalization and contextual understanding may be compromised

Engineering Contradiction:

Improveautomation levelVSAvoidpersonalization capability

Core Design Contradiction:

Extent of automationVSAdaptability or versatility

Solution Approach 1:

The system incorporates feedback mechanisms where customer responses and interactions are continuously analyzed to refine and improve the virtual agent's understanding and response generation. This feedback loop enables the automated system to learn from real-time interactions and improve its personalization capabilities over time.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent employs dynamic parameter adjustment where the system modifies its response strategies based on changing contextual parameters such as customer sentiment, query complexity, and historical interaction patterns. This allows the automated system to adapt its behavior to different situations while maintaining personalization.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If real-time query analysis is performed, then customer engagement is improved, but system complexity and processing requirements increase

Engineering Contradiction:

Improvecustomer engagementVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system segments the complex query analysis process into distinct functional modules including sentiment analysis, intent recognition, context extraction, and response generation. This segmentation allows each component to process specific aspects of the query independently, reducing overall system complexity while maintaining real-time processing capability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediary processing layers that simplify the interaction between different system components. These intermediaries act as buffers and translators, managing the complexity of real-time data processing and communication while presenting simplified interfaces to both the virtual agent and the customer.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Adaptability or versatility

If social media integration is expanded, then customer service accessibility is improved, but data processing volume and operational burden increase

Engineering Contradiction:

Improveservice accessibilityVSAvoiddata volume

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The system applies partial action by selectively processing only the most relevant and urgent queries rather than treating all incoming data uniformly. It prioritizes high-value interactions and applies full analysis only where necessary, reducing the operational burden while maintaining comprehensive coverage for critical customer service scenarios.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11062220B2Integrated virtual cognitive agents and message communication architecture

Publication Date: 2021.07.13 ACCENTURE GLOBAL SOLUTIONS LTD

AI summary

A virtual cognitive agent (VCA) system comprises social media communication channels integrated with machine cognition engines. The VCA system connects to an external message platform and accesses posted messages. An intent is determined and sentiment analysis is performed on text elements from the intercepted messages to determine handling of the message. The integrated machine cognition engines determine a response to the captured message. The VCA system may access a corpus or exchange data with the originator of the post or another entity to determine the response. The integrated social media communication channels may connect to an external query response platform and communicate the response to the query response platform.