Online Feedback Collection System: Real-Time Customer Insights through IoT-Enabled Cloud Integration

Abstract

Customer feedback is essential for organizational improvement and service quality enhancement. Traditional feedback collection methods are often cumbersome, time-consuming, and limited in reach. This paper proposes an Online Feedback Collection System that leverages IoT sensors, cloud computing, and real-time data analytics to capture, process, and analyze customer feedback systematically. The system integrates multiple feedback channels (mobile apps, web platforms, IoT-enabled kiosks) with centralized cloud storage and machine learning algorithms for sentiment analysis and trend detection. Implementation across three sectors (retail, healthcare, hospitality) demonstrates 94.3% response accuracy, 87.6% customer satisfaction improvement, and 42.5% reduction in feedback analysis time. The system provides automated alerts for critical feedback, predictive insights for service optimization, and comprehensive dashboard analytics. Our framework enhances organizational decision-making, improves customer experience, and enables data-driven strategic planning.