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December 02, 2019 | Information & Technology
The term ‘retail’ denotes a commercial transaction wherein businesses sell their goods to individuals for personal consumption. While being a buzzword in modern economic parlance, retail has an interesting history that dates back to the period when paper or metal money was not the currency. The earliest form of retail can be traced to the barter system where goods were exchanged for goods, followed by the glorious era of metal money which was started in Mesopotamia. The Chinese later developed a primitive system of accounting and in 1883, the cash register was invented in America. This was the watershed moment in the evolution of the retail industry as the cash register enabled efficient accounting and the daily sale of goods could be tracked with greater convenience. The other landmark development was the invention of the electronic cash register in the 1960s which further simplified the process. The retail industry has grown by leaps and bounds since then.
Retail Analytics in the 21st Century
The period after the end of the Second World War saw rapid developments in societies all over the world. Populations grew, businesses expanded, and globalization brought the world closer than ever before. The flip side was the increasing complications in the socio-economic fabric of countries. Various new practices were developed and adopted to simplify processes and reduce human effort and one of the biggest beneficiaries was the retail industry.
As with other industries and sectors in the 21st century, retail too faces the seemingly insurmountable task of collecting, consolidating, and analyzing data. Even though the human brain is capable of processing large quantities of data, computers are nevertheless required in today’s world where “time is money” and the sheer volume data that is generated every hour of every day, especially at departmental stores. Just visit a Walmart or Target on a Sunday and you will know the gravity of this statement. While computers cannot supplant human intelligence and judgement, they most certainly are needed to make processes time and cost-effective and businesses profitable.
Technology to the Rescue
However, simply having computers is not enough and new advancements need to be made to make even computers intelligent. Machine Learning ML) is one such technological advancement. Artificial Intelligence (AI) and Internet of Things (IoT) have made human life incredibly comfortable; Machine Learning, a subset of AI, is aimed at making businesses lucrative and sustainable. And the retail industry is making good of this technology to the best of its abilities.
Machine Learning models are founded on algorithms which need to be tweaked time and again to make them as intelligent and predictive as possible. This can empower a retail business to streamline many of its processes, eschewing the need for human intervention. For example, ML can enable a retail outlet to analyze customer preferences, buying habits, interact with them virtually, and guide them. Some of the biggest names in the retail industry are employing this technique. Take North Face for example. The company teamed up with IBM Watson in 2015 to integrate the Watson AI with North Face’s website. The idea is for Watson to act as a shopping guide, a virtual human conversation medium, for customers buying products online. ML can also help retailers to identify and predict buying patterns based on previous purchases and detect fraudulent activities. Amazon has made great strides in this respect. Having applied ML to its e-commerce business, Amazon has become a living and thinking organism that seems to have mastered the art of predictive analysis of consumer behavior and tailoring products and services to individual customer needs. The power behind Amazon’s Alexa and Web Service (AWS) cloud computing platform is nothing else but a highly sophisticated Machine Learning system.
Where Do We Go from Here?
Machine Learning has revolutionized the production function of businesses. Capitalism demands profit maximization and ML is delivering it on a platter. Amazon gets almost 35% of its sales from it ML model which personalizes recommendations for its customers. It’s no wonder that the company is making copious amount of money and is current valued at US$ 1 trillion, rich enough to buy a small African or East European country. As Machine Learning mechanisms become more accessible and affordable, it would not be too far afield to state that the technology will turn traditional business models and economic theories on their heads.
About the Author
Name: Shantanu Ayachit
Shantanu Ayachit is part of a talented team of content writers working in Fortune Business Insights, one of the most promising market research firms in the industry. He has experience in developing quality content and is currently involved in writing articles, press releases, and blogs for the company. He is highly motivated and enjoys putting ideas and thoughts into words to enable the reader to experience a seamless perusal.