From the way e-tailers offer products to the way shoppers buy or transact online, Predictive Analytics has been reshaping and transforming the e-commerce industry.
E-commerce has taken the global market by a storm and is expected to grow exponentially in the upcoming years. A market research firm, eMarketer, projects e-commerce sales will eclipse $3.5 trillion within the next five years. Walmart (i.e. the world’s largest company by revenue) has planned to close hundreds of stores to now refocus its efforts on its e-commerce site.
So, a big reason for this boom is the rapid growth in the internet and mobile users globally. E-commerce provides convenience to the users by giving better payment and advanced shipping option too. It also provides a new level of customization and personalization by using some advanced analytics tools.
Did you know? E-tailers track and analyse your online behavior to gain insights that allows them to make billions of money?
Have you ever wondered how Amazon knows if you are a movie buff, a gadget freak or an avid reader? Or how Google knows that you were looking for a new laptop on some website? Or how do you get the recommendation for an ideal party wear, that you were looking for a long time, directly to your inbox?
In this infograph, we intend to answer these questions and know how the industry uses analytics.
E-Commerce uses Predictive Analytics to deliver a great shopping experience!
Summing it all up-
How Predictive Analytics helps Buyers?
- Provides products that are relevant to shoppers’ needs.
- Reduces the time taken to shop.
- Reduces the hassle to choose from a variety of products.
Hence resulting in a great buying experience!
How Predictive Analytics helps Sellers?
Offering targeted and personalized products not only increases customer loyalty and retention but also improves customer satisfaction. It also aids in cross-selling and up-selling. These hence result in increased revenues and profits for the firms.
How the giants use Predictive Analytics?
- Amazon has the most sophisticated recommendation algorithms allowing it to offer targeted products.
- Alibaba- Chooses the best vendors to sell products.
- eBay- The American marketplace uses past data to rate sellers, thus helping buyers to make better decisions.
- Flipkart- Optimizes logistics and stock.
These were just some of the examples of analytics in e-commerce. Hopefully, you’ve now got a brief idea of how analytics is reshaping and transforming the online shopping experience.
If new to analytics and data science? Read A Newbie to Data Science? Start Here.