Social Media Message Processing System for Contact Centers
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Solution Overview
Problem
The increasing use of social networking platforms for user interactions poses a challenge for contact centers to efficiently monitor and respond to customer inquiries and concerns in a timely and automated manner, especially with the decline of voice-based interactions and the rise of text-based communication.
Innovation Solution
A method and apparatus that utilize natural language processing to detect, interpret, and respond to user messages posted on social networking sites, allowing for automated message monitoring and response generation, enabling text-based communication with customers through SMS, MMS, or IM, and integrating with existing contact center systems for improved customer service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated text-based monitoring and message creation services are implemented, then contact center productivity is improved, but system complexity increases
Solution Approach 1:
The patent introduces natural language processing technology as an intermediary component between social media platforms and contact center systems. This NLP intermediary automatically parses, interprets, and structures unstructured social media text into actionable customer service tickets and responses, thereby improving productivity while managing system complexity through modular architecture.
Solution Approach 2:
The system implements automated self-service capabilities where the contact center platform automatically monitors social media channels, detects customer inquiries, parses message content, generates appropriate responses, and sends acknowledgments without requiring manual agent intervention for each interaction, thus enhancing productivity through automation.
2Productivity
If natural language processing and word parsing technology are deployed, then message processing efficiency is improved, but computational resource consumption increases
Solution Approach 1:
The patent applies partial action by implementing selective monitoring and parsing only for messages that contain keywords or patterns indicating customer service relevance. Rather than processing all social media text uniformly, the system performs targeted NLP analysis on pertinent messages, improving efficiency while reducing unnecessary computational resource consumption.
3Loss of time
If automated response generation is implemented, then response time to customer inquiries is reduced, but accuracy of response may deteriorate
Solution Approach 1:
The patent incorporates feedback mechanisms where the automated system generates initial responses based on parsed message content, then routes these responses for review and validation. Customer responses and interaction outcomes feed back into the system to continuously improve response accuracy, balancing speed with precision through iterative learning and human-in-the-loop validation.
Data Source
AI summary
A method and apparatus of processing communications with end users are disclosed. One example method may include detecting a message or post on a website over the Internet that matches a monitoring company's keywords or rules and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's topic of interest. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the user acknowledging the user's topic of interest. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.