The concept of e-tailing i.e electronic retailing came into the market about a decade ago and today almost everyone has adopted the online mode of shopping. It has always been a challenge for the e-tailers to provide easy and seamless experience to the user like what they demand, what they browse amongst the collection, did they find the desired product, and get the delivery on time? But it’s a different ballgame for the e-tailers to get this job done.
Amazon & North Face have already stepped into new technologies from past 2-3 years and have had some successful results.
How are these E-tailers using AI and Machine Learning in their System?
The Recommendation Scenario
When a company holds an enormous collection, clustering becomes an issue. Out of that huge collection how will the customer reach to his/her desired product becomes a question. Then comes the role of prediction algorithms designed under the influence of machine learning that intelligently reverts you to a product you might be searching for. Taking a case into consideration, like you are looking for a black trouser – slim fit, the next time you search again, the platform will feature a similar looking trouser with a related pattern you’re looking for, which might induce you to purchase. Basically, these prediction algorithms filter the products according to your choice & preferences.
In such a way these algorithms deduce, what is driving you and would recommend the sorted products based on your interests. This reduces your time to search through the entire collection.
AI Developed products
Moda Rapido a renowned fashion brand is working on selling their products intelligently. With Myntra (A leading apparel brand in India) by its side, it started the production of AI-designed t-shirts and monitors the rate of selling of these t-shirts against the human-designed t-shirts. According to the implementation of these products, soon there will be a complete market of apparels which will be entirely computer-generated.
We are already seeing how Amazon is using deep e-commerce algorithms and pipes that are taking it ahead of its competitors Google and Apple, in making the AI-powered smart home popular.
Solving the Transaction Complexity
During the rush on these e-tailer platforms, there is a heavy load on the payment gateway of these portals. Cross gateway transactions will eventually lead to heavy loads resulting in abrupt results on the transaction systems. The intelligent systems have been deployed over these e-tailers which automatically senses an incoming abnormal situation and auto- routes these transactions away from the gateway.
Logistics and Delivery
The company logistics uses Machine Learning to convert the vaguely described addresses into recognizable addresses. Errors are very frequent in address descriptions section, which makes it difficult to locate, therefore Machine Learning is very critical in logistics. The system uses AI for an automated revert of the expected time of delivery which has no human intervention in it. The Machine learns over a period of time the pattern of working of the entire supply chain i.e. the working hours on weekends, what the product is, what the size is etc.
E-commerce platforms like Amazon, North Face, eBay are working through automation process, right from the point of using robots for warehousing to delivery through drones. AI and ML are extremely important because of the potential.
What Benefits are these e-tailers getting from the Adoption of AI and Machine Learning?
Since these e-tailers played their cards successfully when innovation came into play and made huge out of it. According to the estimates, the Gross Merchandise Value (GMV) depleted by e-commerce companies is conventional to grow to around $80 billion by 2020 up from around $4 billion in 2009.
These Industry Giants are using Machine Learning to understand the patterns based on the data gathered by their systems based on past purchases and returns. For example, based on the last review that the size of the shoe delivered was a bit small since the size may vary according to the brand, then the system will infer the best suitable size for its customer.
Inventory can be updated based on the current trend to deliver the product which is not outdated.
Image Source: yourstory.com
What is Yet to be Introduced?
AI specialists are working on Speech Recognition, Natural Language Understanding, question answering, dialogue systems. For Example, Flipkart’s AI Project ‘Mira’- Flipkart (leading e-commerce store in India) is working on its AI project Mira, which is developed with the aim of preventing 10-11% returns, which can be done just by asking two or three questions prior to their search. Considering a case where a user wants to buy a T.V., now the AI & ML algorithm start working and e-tailers will ask for the brand, the size, type of screen etc., helping the customers to find the exact product they want which was not easily navigable the other way.
Leading E-tailers are a taking a step forward to introduce a fashion assistant which talks to you in common language and recommends you about various products. The entire processing will be based on voice recognition, if a user says, “cancel order” the order will be canceled.
Since we have seen what wonders can be done with the data, it is a great opportunity for industry giants to improve the efficiency with the reduced cost inputs. AI and ML are extremely important due to high potential. A lot of innovative experiments are going on in e-commerce and a lot of innovative techs is expected from this domain.