Digital and Social Media Management

  Cross-Cutting AI Applications Addressing Multiple SERVQUAL Gaps 1. Jio's Integrated AI Service Platform Reliance Jio demonstrates comprehensive SERVQUAL gap reduction: Listening Gap : AI analyzes customer behavior across 400+ million subscribers to understand actual expectations vs. company perceptions Service Design Gap : ML translates insights into specific service standards (network uptime targets, support response times) Service Performance Gap : Real-time AI monitoring ensures employees meet standards, with automated quality assurance Communication Gap : AI personalizes marketing messages to match actual service capabilities, preventing over-promising Impact : Industry-leading Net Promoter Score of 74, with 90% first-call resolution rate. 2. Tata Consultancy Services (TCS) - iON Platform TCS uses AI to deliver educational services: Standards Setting : ML analyzes student performance to set realistic learning o...

  Service Recovery Through AI 1. Amazon India's Proactive Service Recovery Amazon uses AI to implement the service recovery paradox effectively: Predictive Failure Detection : Delivery Risk Prediction : Machine learning predicts potential delivery failures (weather, traffic, address issues) and proactively informs customers with alternatives Product Quality Monitoring : AI analyzes review patterns to identify defective product batches before customers complain Fraud Detection : ML identifies suspicious orders that might lead to customer dissatisfaction Automated Recovery Actions : Instant Refunds : AI approves refunds for specific failure types without human intervention Proactive Compensation : When delivery delays are predicted, AI automatically applies credits to customer accounts Personalized Apologies : Natural Language Generation creates customized apology messages based on customer history and fa...

Designing   Customer-Defined Service Standards with AI 1. Zomato's Real-Time Service Standards Monitoring Zomato implements both hard and soft standards using AI: Hard Standards (Measurable Metrics) : Delivery Time Prediction : AI predicts delivery times within 2-minute accuracy, setting realistic customer expectations Restaurant Partner Response Time : Machine learning monitors how quickly restaurants accept orders (target: under 60 seconds) Order Accuracy Rate : Computer vision at partner restaurants verifies order completeness before dispatch Soft Standards (Perception-Based) : Sentiment Analysis : Natural Language Processing analyzes customer reviews to measure "friendliness of delivery partner" and "food presentation quality" Voice Analytics : AI evaluates customer care calls for empathy, politeness, and problem-solving effectiveness Chatbot Interactions : ML measures customer satisfactio...