mjunction services will implement machine learning in their eAuction platform for forward auction services of steel products and steel scrap such as defectives and seconds. There will be two distinct components to this – to identify the right buyer and to estimate the likely selling price of the materials.
With around 150 auctions per day, the need of the hour was to have an intelligent system, an algorithm that would identify the right buyer for a particular product at a particular point of time based on the client’s area of operations. Estimating the likely selling price of the materials is also crucial for the success of an auction, as the auction opens on that price.
As of now, the application will applicable for forward auction of seconds and defectives only and will be extended to other segments only at a later stage.
mjunction CEO Mr Vinaya Varma said, “We have taken a leap towards adopting emerging technologies which will benefit both the buyers and the sellers. Accurate identification of the right bidders for the right products will increase the efficiency and effectiveness of the auction process.”
The automated system will not only select the right bidders for a particular auction, but also the relevant auctions for one particular bidder. This will be arrived at from the data it gathers through previous bidding history, location of the bidder, relationship between categories and other related factors. The price estimation will also be done by collecting data from previous prices, past auction participations, prime and seconds price fluctuations and other external factors such as growth of GDP.
The algorithm will introduce an automated bidder recommendation mechanism based on their buying behaviour and their likelihood to bid. The algorithm will also send in communications to the bidders identified for the auction.
Artificial intelligence (AI), data analytics, machine learning and deep learning are the next big technology applications that will be used for process automation of several businesses. mjunction, which has always kept itself abreast with the latest technologies, is jumping into the bandwagon, beginning with the eAuction process, which has been its strength for several years now.
While machine learning and deep learning instruct the machine and the software to interpret data, AI is the software which formulates the decisions. On the other hand, data analytics analyses data to chalk out consumer behavior, usage pattern and a host of other activities.
Some of the most common examples of machine learning applications are traffic predictions through GPS services, target advertisements and personalised news feed on social media platforms, product recommendation on shopping websites etc.