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Multi-Channel Customer Sentiment Tracker with Real-Time Analytics and Alerting

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Created by: Cheng Siong Chin || cschin

Cheng Siong Chin

Last update

Last update 10 hours ago

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How It Works

Scheduled processes retrieve customer feedback from multiple channels. The system performs sentiment analysis to classify tone, then uses OpenAI models to extract themes, topics, and urgency indicators. All processed results are stored in a centralized database for trend tracking. Automated rules identify high-risk or negative sentiment items and trigger alerts to the relevant teams. Dashboards and workflow automation then visualize insights and support follow-up actions.

Setup Instructions

  1. Data Sources: Connect social media APIs, survey tools, and customer support platforms.
  2. AI Analysis: Configure the OpenAI API with sentiment and theme-extraction prompts.
  3. Database: Set up a feedback storage schema in your utility database.
  4. Alerts: Configure email notifications and CRM triggers for priority issues.
  5. Dashboards: Link your analytics and reporting tools for real-time insights.

Prerequisites

Social media/survey API credentials; OpenAI API key; database access; CRM system credentials; email notification setup

Use Cases

Customer sentiment tracking; product feedback aggregation; support ticket prioritization; brand monitoring; trend identification

Customization

Adjust sentiment thresholds; add new feedback sources; modify categorization rules

Benefits

Reduces analysis time 85%; captures actionable insights; enables rapid response to issues