Digital transformation is permeating every field and industry we know today, beginning with mass media and progressing to education, healthcare, finance, and banking. Organizations go digital to improve their services and facilities in order to increase customer satisfaction. The concept of digital transformation in retail is based on customer needs and requirements.
Higher sales in the retail digital transformation market have been driven by increased Internet penetration in the retail sector and an increase in the number of Internet users. Customers are more likely to shop online because of improved logistical infrastructure, enhanced and secure payment methods, and optimised shipping services. Technological advancements and awareness have resulted in an increase in the number of Internet users, significantly increasing the traffic of online shoppers. Higher penetration of mobile devices for online shopping, an increase in the number of online shopping applications, and investment in the development of m-commerce have all contributed to the growth of the global retail digital transformation market.
Machine learning is critical to establishing a bond between a retailer and a customer by assisting the retailer in better understanding and predicting what the customer wants. Machine learning is a branch of data science that collects data from one (or more) sources and then feeds that data into machine learning models, which help predict future outcomes.
Retailers can use machine learning data to identify shopping patterns, understand purchasing behaviours, adjust promotions and special offers, personalise product recommendations, adjust pricing on the fly, and create forecasts based on historical trends and customer preferences.
