Usage of Big Data at Flipkart
Flipkart uses big data in a variety of ways to improve its operations and provide a better shopping experience for its customers. To maintain its market-leading position, Flipkart intends to use a combination of big data analytics, social shopping, and a mobile-first strategy. With more than 45 million users who have registered, Flipkart has a wealth of transactional and customer data that may be mined for information.
Some specific examples of how Flipkart uses big data include:
- Personalization: Flipkart uses data analytics to personalize the shopping experience for each individual customer. This includes personalized recommendations, targeted ads, and customized content.
- Inventory management: Flipkart uses big data to track and analyze data on product demand, supply chain efficiency, and other factors to optimize its inventory management. This helps Flipkart ensure that it has the right products in stock at the right time, which can improve customer satisfaction and reduce costs.
- Fraud detection: Flipkart uses data analytics to identify and prevent fraudulent activity on its platform, such as fake reviews, fake orders, and other types of fraud. This helps protect both Flipkart and its customers from fraud and increases trust in the platform.
- Customer service: Flipkart uses data analytics to improve its customer service by analyzing customer inquiries and feedback to identify trends and areas for improvement. This can help Flipkart resolve customer issues more quickly and effectively, which can improve customer satisfaction.
- Marketing: Flipkart uses data analytics to identify trends and patterns in customer behavior, which can help the company tailor its marketing efforts to better target specific segments of its customer base.
Overall, Flipkart uses big data in a variety of ways to improve its operations and provide a better shopping experience for its customers.
Flipkart also intends to make use of computer vision, which refers to a machine’s capacity to learn how to recognise images just like a human. The business employed Krishnendu Chaudhury, an image scientist who had previously worked on the Google Brain project, which aimed to teach computers how to recognise objects like photographs and speech in the same way that humans do.