A few years ago, the e-commerce giant Myntra had decided to stack in piles of women boots studded with pink stones, but they could not sell even one pair! After this happened, the company had tried to sell those off to its in-house employees by offering huge discounts; but then also, not even one employee showed the least interest in buying them. Read here- Driving E-Commerce Business By Leveraging Predictive Analytics

What went wrong?

According to Mr. Shamik Sharma, CTPO of Myntra, someone in their sales team had inaccurately predicted that pink boots are much in trend and that is why they would be selling like hotcakes. However, the truth was far from that, and it simply led to massive waste. Being one of the trendsetters of the modern E-Commerce business in India, Myntra had to devise measures so that such incidents do not recur and also to understand demand forecasts accurately to reduce bad products from piling up in their inventory.

How did they tackle this problem?

Myntra employed the latest technologies to come out of this situation. To predict the demand of their customers, experts adopted predictive analytics principles to determine the buying pattern of customers which would help them in stocking the right products for every season.
To let predictive analytics do its magic, the analytics tool had to be fed with data from various external sources like fashion trends from across the world and then the data was used to make bets on what people would prefer to wear in the next few seasons.
In this regard, Mr. Sharma along with a team of 30 expert data scientists immediately started working on the issues that cropped up not only from demand forecast but other problems as well.
According to the Myntra team, setting up the predictive analytics environment also benefitted them immensely in optimizing the supply chain, and sending out deliveries faster to customers.

Another example – How Housing.com handled the sudden surge in house searches on their portal

The Mumbai-based real estate portal, Housing.com, found an unprecedented rise in the number of searches in a day to day basis, about a couple of years ago.
The employees were finding it impossible to extrapolate the huge piles of data related to the age of a group of people looking for houses, location and sale history of the properties. But hiring more employees for this was impractical. To tackle this, Mr. Vivek Jain, the company’s CTO decided to build a data analytics platform with a team of over 55 data scientists. Their predictive analytics model would help them in understanding the unstructured data so that the selling information of the right property reaches the right people.

Opportunities offered by predictive analytics and Big Data

If statistics are to be believed, business analytics services and applications increased from about $122 billion in the year 2015 to $187 billion in 2019. Now if you add this with the $120 billion Indian e-commerce industry, then both data scientists and data vendors can access a fantastic platform that would help them deliver a more personalized customer experience.