Digital and Social Media Management

"We utilize AI and advanced search analytics to anticipate user needs, sometimes even before users are consciously aware of them. This allows us to build immersive, shoppable experiences based on emerging trends, making product discovery feel intuitive and the path to purchase completely seamless." Flipkart's AI Playbook features a Q&A with Sandhya Kapoor, SVP and Head of Central Platform Organization, detailing how AI drives e-commerce innovation in India.    AI for Customers AI enables hyper-personalization through enhanced search, product discovery, generative AI for descriptions and review summaries, and sophisticated chatbots. It powers predictive forecasting, fraud detection, supply chain optimization, and marketing. For Gen Z and Tier 2/3 users, AI supports video commerce with data-backed, creator-led shoppable experiences that anticipate needs for seamless purchasing.    Data Strategy Flipkart uses meticulous data practices, translating business ...

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  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 f...

  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 satisfaction with a...