Recommendation Systems and Collaborative Filtering in E-commerce
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Recommendation Systems and Collaborative Filtering at Big Basket, Netflix

Reading Time: 1 minute

Recommendation systems are extensively used by e-commerce stores to retarget customers and improve engagement and sales. In this video, Mani Subramanian, a renowned data analytics expert introduces the concept of recommendation systems and discusses the functionalities and applications in online retail and consumable’s industry. He also demonstrates the various approaches of building a recommendation system and illustrates his point by showing how Big Basket uses their recommendation system to improve sales. In addition, you can also learn how Netflix recommends movies that users are likely to watch based on their profiles and watching history. In addition to Recommendation Systems, Mani also introduces the concept of Collaborative Filtering.

By: Mani Subramanian

Mani Subramanian heads Analytics function at bigbasket.com, India’s largest online food and grocery store. He has over 18 years of experience in Consulting and Analytics. Prior to bigbasket.com, Mani was a Director of Analytics at Dell. His experiences include co-leading the Supply Chain Center of Competence (CoC) at McKinsey, Principal Consultant at Infosys Technologies and Senior Consultant at Ernst & Young and PricewaterhouseCoopers. In these roles, Mani  has successfully led supply chain transformation and technology engagements for clients across the US, Europe and the Middle East. He has advised clients across various industries with a key focus on industrial manufacturing and hi-tech industries.

Mani graduated with a Bachelor of Engineering degree in Computer Science from University of Madras, an MBA from IIM Ahmedabad and a Master of Engineering degree from MIT.

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