Ivy Sep 28, 2016 No Comments
We have changed the way we shop! India’s e-commerce market is likely to touch $38 billion in 2016, a huge jump from $23 billion in the year 2015.
As an Analyst (or a budding Analyst!), Have you thought of the ways Data Science is used in the e-commerce industry?
Figure this –
Browsing through your facebook account, you come across an ad by an online apparel brand that has been liked by some of your friends. Click! Move to the e commerce website/app. You find various merchants offering a wide variety of products coupled with insights like user ratings and testimonials from other customers. Click on an item! The site also recommends what other users have purchased along with this. Click! Go on to purchase the item.
What are things that were special in your interactions with this e-apparel store?
1. Online Marketing Analytics – The customers for an e commerce company are ones who are relatively aware and are present in the virtual environment. Attracting the maximum customers through marketing campaigns like Google adwords, social media marketing etc is only effective if data from customer interactions is analyzed to deliver the optimum results.
2. Product specific Analytics – Customer data like satisfaction rate, rating, no of times a product added to the cart, no of clicks by users etc is used to determine the price of a product on a category page among other things. It is important to analyze all data regarding each individual product type to predict/forecast sales and hence procurement.
3. Virtual Recommendations – In early days simple basket analysis was used to make recommendation, today we have customer specific predictive algorithms being executed. Basis the products previously purchased or the products where the user spends greater time, machine learning algorithms predict your next purchase!
4. Merchant/Supply Chain Analytics – This includes managing data for products right from warehouse to the customer. E-Commerce industries use analytics extensively to manage Inventory. Also a significant portion of work is into optimising transportation and pricing of delivery.
5. User Experience Analytics – The website architecture plays a very important role in determining the user experience. The data on page wise traffic, product category wise and SKU wise number of clicks is used to define the order in which we place the product types on the website. Along with this, the product that is searched for the maximum times, the campaigns that are the most successful also paves the way for the best layout.
6. Customer Fraud Analytics – Predictive analytics allows these companies to analyse browsing patterns, payment and purchasing methods, geography etc to detect and reduce Fraud. Now machine learning is also being used to define patterns and proactively point out any anomaly.
Ivy offers Advanced Analytics training programs in Retail Analytics, Healthcare, Financial Risk Analytics Certification other than its flagship Big Data and Business Analytics Course. Call us at 9748441111 for details.
Reference:
https://www.analyticsvidhya.com/blog/2015/08/role-analytics-e-commerce-industry/
http://conversionxl.com/predictive-analytics-changing-world-retail/?hvid=352IDw
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