Rise in expenditure on big data analytics tools and growth of the e-commerce sector drive the growth of big data analytics in retail

The global big data analytics in retail market size was valued at US$4.9 billion in 2020 and is projected to reach US$2.6 billion by 2028, registering a CAGR of 23.1% from 2021 to 2028. The retail industry is witnessing a major transformation through the use of advanced analytics and big data technologies. With the growth of e-commerce, online shopping, and high competition for customer loyalty, retailers are utilizing big data analytics to stay competitive in the market.

In the retail sector, big data analytics is being used at every stage of the retail process to understand customer behavior, predict demand, and optimize pricing. Most of the big data applications in retail are for system-wide cost reduction, improving online and in-store customer experience, data-driven adaptive supply chains, and real-time analytics and targeting. In terms of application, big data analytics in the retail sector is being segregated as merchandising and supply chain analytics, social media analytics, customer analytics, and operational intelligence, which is being used in small and medium enterprises and large-scale organizations.

The rise in expenditure on big data analytics tools, surge in need to deliver personalized customer experience to increase sales, and growth of the e-commerce sector drive the growth of the global big data analytics in the retail market. However, collecting and collating the data from disparate systems hamper the market growth. Moreover, the integration of new technologies such as IoT, AI, and machine learning in big data analytics in retail and the growing demand for predictive analytics in retail is expected to usher in a plethora of opportunities in the future.

Raise in the growth of the e-commerce sector is expected to increase the growth of the big data analytics market size. Much of the growth of the e-commerce industry has been triggered by an increase in internet and smartphone penetration. Retailers can improve the performance of their online stores and generate more revenue using big data analytics in retail software. Retailers can improve product landing pages by using website analytics, clickstream data, and heatmap studies to ensure higher engagement and conversion rates.