AI Articles and Analysis about E-commerce

Episode Summary: In this episode of the AI in Industry podcast, we interview Sumit Borar, Senior Director of Data Sciences and Engineering at Myntra, an eCommerce site for fashion, about the current and future state of eCommerce personalization and how the way customers in India purchase products online affects that personalization. Myntra talks about the challenges of bringing dialed-in personalized recommendations to the physical world and the challenges of bringing eCommerce into the developing world.

Reuters referenced an Orbis Research figure estimating the global cosmetics market to be worth around $$805.61 billion by 2023.

By implementing an immersive virtual-reality environment, some AI applications claim it is possible to test products or retail ideas that have not been brought to on the market, putting them on a virtual shelf to study consumer reactions and behavior to real-time merchandising.

Episode Summary: When we think of recommendation engines, we might think of Amazon or Netflix, but while consumer goods and entertainment might be the most prominent domains for recommendation engines, there are others. This week, we speak with Madhu Gopinathan of MakeMyTrip, one of the few Indian unicorn companies, about recommendation engines for travel companies.

In a study from Researchscape International, 74 percent of 300 marketers surveyed said personalization in this field has strongly helped their clients or companies in advancing customer relationships. It also found that 54 percent said their clients or companies experienced a 10 percent increase in sales, while 13 percent of marketers surveyed reported a more than 30 percent lift.

In 2013, a McKinsey report noted that over 85 percent of Amazon sales revenue was generated from personalized recommendations. Since then, the use of personalized recommendations has grown. On average, today’s personalized recommendations account for 27-percent of retail site revenue, according to a recent Salesforce report. 

The fashion industry has grown at 5.5 percent annually in the past decade, according to the McKinsey Global Fashion Index, and in 2016 was estimated to be worth $2.4 trillion.

In recent years, artificial intelligence has enabled pricing solutions to track buying trends and determine more competitive product prices. While static pricing keeps prices absolute, dynamic pricing adjusts prices to offer customers different prices based on external factors and their individual buying habits.