
Ravi Vijayaraghavan
Vice President and Head- Analytics and Decision Sciences
Bengaluru, India
Topic: Analytics and Decision Sciences for Ecommerce – An overview and use cases in customer experience
Dr Ravi Vijayaraghavan is an executive leader with a proven record of building world-class analytics and data sciences organizations. He has built and managed data science and analytics teams in Large Fortune 500 Companies and Silicon Valley startups. He has generated substantial Intellectual Property for the companies. He has worked with and have 25+ patents and patent filings. As a researcher, Dr Ravi has several peer reviewed publications. Currently he is responsible for the Analytics and Decision Sciences organization at Flipkart. Flipkart is the leading destination for online shopping in India and its biggest e-commerce player. At Flipkart Analytics organization we are embarking on an exciting journey to build cutting-edge capabilities that enable Flipkart to make better business and product decisions with data and science. He has been nominated to be among the 10 most influential analytics leaders in India in 2015, 2016, 2018 and 2019.
Few key patents are; Method and Apparatus for Analyzing Leakage from Chat to Voice. Method and Apparatus for Analyzing and applying Data Related to Customer Interactions with Social Media. Chat Categorization and Agent Performance Modeling. Predictive Customer Service Environment Method and Apparatus for Optimizing Web and Mobile Self-Serve Apps.
Abstract:
The Analytics and Decision Sciences organisation at Flipkart has the charter of leveraging
Analytics and Data science to enable robust data-driven decision-making. Key focus areas of this
organisation are business growth and continuously improving customer experience. My talk will
present the overall landscape of the organisation and the areas we cover.
Key expectations of any consumer from an ecommerce platform are, a wide assortment/selection
of products, a price that is value for money, Good product quality and a good delivery
experience. Following the overview, I will present use cases related to applications of statistics,
machine learning and optimisation in addressing some of these expectations of our consumers.