How can the analytics on Big Data affect the buying trends of customers in the retail industry?
Big Data has emerged as of one of the biggest business and technological buzzwords of recent years. “The term Big Data applies to information that cannot be processed or analysed using traditional tools or processes” (Eaton et al. 2012). A number of IT companies including International Business Machines (IBM), Hewlett Packard (HP) and Oracle are leading the development of Big Data analytics programs and are creating unique packages for retailers, which suggests that it is going to have a big impact on the retail industry.
The primary research has been carried out in the form of interviews, which has been conducted anonymously with representatives from COMPANY A and COMPANY B, to help meet the aims and objectives. Extensive secondary research has also been undertaken to provide more information to help answer the overall question: How can the analytics on Big Data affect the buying trends of customers in the retail industry?
There is a high probability that the main benefit of Big Data for retailers and their customers is being able to better understand customers, allowing for more personalised offers leading to higher sales and customer loyalty. One of the prominent factors that may affect the buying trends of retail customers is the channel by which purchases are made. The analytics of Big Data will undoubtedly have an impact on the buying trends of retail customers but ultimately when, where and how customers make purchases will be down to personal preference.
There is a distinct possibility that a collective view from a minimum of five retailers could prove more reliable, allowing for more representative conclusions to be made. As more and more data becomes available every second, and with the use of analytics tools becoming more commonplace in the retail industry, there could a huge impact for many years to come.
Peter Smith is currently completing the final year of a Business and ICT BSc (Hons) degree as well as being a course representative. His interests in Big Data and Analytics were discovered leading up to and during his year in industry.
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