Bishal Mukherjee

 How Data Science is Revolutionizing eCommerce Data science as the name suggests is data driven by science. It is a method to extract relevant data or insight from the data in various forms which can either be structured or unstructured. It is kind of similar to data mining. If we talk about business terms, it helps businesses provide a richer understanding of the clienteles’ by capturing and integrating the information of the prospect’s online behavior. At this period of time, ecommerce is the essence of almost every business. The world at this time is immersed in data from innumerable sources. Data science and ‘data scientists’ have actually revolutionized modern business. In the field of eCommerce, customer and sales data are integrated into a database which further is linked with the email marketing and ad platform data. A thorough analysis of these gives a data scientist a 3D view of (i) Customer lifetime value, (ii) Personality analysis, (iii) Churn detection, (iv) Customer segmentation, (v) Cohort analysis, and (vi) Trend analysis. This helps the business to work and forecast new and beneficial acquisition and retention strategies and it exactly is the revolution it has brought to the modern business. Let me explain it this way – assume you’re on a shopping app/website browsing. You scroll downwards and see that the app/website has recommendations based on your browsing/shopping history. Did you ever ponder how does the app/website know your preferences and suggests products that you might end up buying? That, my friend, is data science. This method can be classified under Acquisition strategy. You might initially have logged in to the website to just browse but recommendations have a probable chance of triggering a sale. Per, Bhanu Ram Gopal (VP – Engineering & Analytics, Myntra), use of data science improved product recommendations to customers and boosted up-selling as well as cross sales. Once you select a product, most websites/apps recommend a bundle option of similar or related products. Statistics say that cross-selling is a major part of today’s eCommerce business. As a matter of fact, websites/apps these days also recommend items based on perceived customer journeys. This is also a part of the acquisition. The technique simply tells you what other customers have loved so far and thus intrigues a prospect increasing the chances of a successful sale. Retention strategy is when businesses use offers, promo codes, discounts etc to a prospect and/or flash sales to retain market. Big brands use data science and scientists to monitor stock and manage promotions accordingly. L’Oréal employs data scientists to find out the effects of cosmetics on various skin types. One of the most recent use of data science was by Fruition Sciences to determine how much and when to water grapes in order to produce better quality wine. The inclusion of data science in online business will help sellers offer personalized deals per customer based on individual browsing habits and patterns. Stats show that 43% of retail sales are inclined towards the web. It helps a business to anticipate customer behavior and understand connections of customer’s product reviews and shopping behavior with other customers further leading to successful Prediction model (surfing behavior vs % deal-making). Piyush Chowhan (VP & CIO – Arvind Lifestyle) recently spoke about the integrating the retail store data with online data to build a truly customer centric organization. A recent survey shows that nearly 50% of the retailers consider the fact that addition of BI tools helped improve their current market. A mere 16% are confident about the traditional approach they follow.Thus, data science helps to gain sales/conversion providing optimized information about customers. Numbers speak, isn’t it? Keywords: Data science Data mining Online sales eCommerce