{"id":57280,"date":"2019-05-31T15:21:19","date_gmt":"2019-05-31T09:51:19","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=57280"},"modified":"2025-08-01T18:03:32","modified_gmt":"2025-08-01T12:33:32","slug":"data-science-at-flipkart","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/data-science-at-flipkart\/","title":{"rendered":"How Data Science became the Trump Card for Flipkart?"},"content":{"rendered":"

From handling bookmarks to handling multi-billion dollar company Flipkart has come a long way.<\/strong><\/p>\n

After Walmart\u2019s acquisition for $16 billion(world\u2019s largest e-commerce deal) as an Indian, I feel sad and disheartened and you should too. I guess a lot of writers will quit their day jobs to pursue their passion for engineering(#PunIntended :p).<\/p>\n

Before exploring the case study – Data Science at Flipkart, let’s talk a little about Flipkart.<\/p>\n

Flipkart is India\u2019s largest e-commerce marketplace<\/strong>. It has a registered customer base of over 100 million. It was started 12 years ago and it offers over 80 million products across 80+ categories.<\/p>\n

Starting from Smartphones, Books, Media, Consumer Electronics, Furniture to fashion and Lifestyle it offers everything in one (Two-Three) clicks. It was launched in October 2007. Flipkart is known for its path-breaking services<\/strong> like Cash on Delivery, No cost EMI and 10-day Replacement Policy.<\/p>\n

It was the pioneer in offering services like In-a-Day Guarantee (65 cities) and Same-Day-Guarantee (13 cities) at scale. With over 1,00,000 registered sellers, it has redefined the way brands and MSME\u2019s do business online.<\/p>\n

Data Science at Flipkart<\/h3>\n

The company has a very flat structure within the Data Science team, which enables it to focus on excellence and create a deep sense of ownership. Also being a young team they are able to democratize the process of problem selection.<\/p>\n

\"data<\/a><\/p>\n

Here are some of the signals which they incorporate in their ranking function to help achieve their goals –<\/p>\n

Recommendation System<\/h4>\n

Flipkart is nothing without Data Science, the recommendation system helps in providing the highest conversion rates. It is also a significant contributor to the company\u2019s units and revenue.<\/p>\n

You can check the Data Science and Netflix<\/a><\/strong> case study to know more about the recommendation system.<\/em><\/p>\n

But, this doesn\u2019t end here because a person will not just purchase a product based on similar products or recommended products. There is much more to it.<\/p>\n

Product Quality<\/h4>\n

They ensure a check on quality by having a check on the material quality- It should be good and durable. Is the seller good? What is the feedback from the existing customers?<\/p>\n

To keep the users trust in them, they ensure that they are not compromising with the quality and for that, they show products that are of higher quality on top of the recommended list. By doing this, the trust factor remains intact and the users get quality products.<\/p>\n

Performance<\/h4>\n

To ensure that the users buy good performance and popular product, they have added it in their ranking system. This provides mutual benefit to them. The user makes the buying decision and the company gets more loyal customers who trust on the performance of the products.<\/p>\n

\"Data<\/a><\/p>\n

Source: Flipkart<\/a><\/p>\n

The page of Flipkart has a set of Filters on the left pane displaying Categories, Price, Brand, Customer ratings, Offers, Discount, Color, and Availability. The user can select the criteria in the filters and view only those products that fit into their requirement.<\/p>\n

The Problems that Flipkart faces are:<\/p>\n