The Real Time Application of Big Data in Retail
Ever since we began using computers we have been accumulating large sets of data. For a long time, these archives of bulk data were accumulated in databases that were then laboriously analyzed, often days or weeks after it was collected, and often the reports that were generated were neither practical nor timely. However, the potential for these large sets of data to reveal useful information has begun to be realized in recent years. Large data sets, called Big Data, are databases that record things like individual credit card purchases and inventory records, and the difficulty of interpreting it has always been the amount of computing power that is required to handle such huge amounts of raw data.
In recent years there have been some great advances in both technology and our understanding of how to process Big Data to produce practical results for management. Among the first industries to jump on board with Big Data are retailers who can potentially use it to improve every aspect of their business operation. Computer services like Hadoop, which specialize in analyzing Big Data by distributing data processing of large data sets across a network of computers, have allowed retailers to analyze large amounts of unstructured data, such as the movements of customers through their websites or comparisons of online views of particular products against actual sales. This allows managers to see more accurately how people are behaving and even to pinpoint areas where their marketing plans need to be improved.
Potentially the uses of Big Data in large retail businesses can be used to better anticipate the needs of their customers based on their past purchasing behaviors. Some retailers are currently testing systems that will track shoppers via video while they are in store to examine how they interact with the retail space and to suggest ways to increase the sales opportunities that they can create with their customers. Tracking customer behavior is just the beginning of the practical applications of Big Data for retailers, and it has the potential to improve their distribution networks and even to anticipate what their customers will need before they even know that they need it. As the computers that handle Big Data become larger and faster, and as more data is streamed into databases in real time, it will continue to offer better solutions to the challenges of efficiently running large retail concerns in real time as well.
The improvements in efficiency that can result from the analysis of Big Data will come from the ability to more accurately predict what consumer demands will be based on a wide range of previous experiences. The larger the data sets, the greater their individual accuracy will be and businesses will be able to most accurately target the needs of the individual customers about whom they have assembled the largest databases of past purchases and preferences. As more large sets of data are examined, and we learn more about our behavior as consumers, Big data will introduce innovative new marketing strategies that will eventually trickle down to even the smallest businesses. One obstacle that does confront the future of this new statistical sector is the potential lack of people that will be able to do the deep statistical analysis, and possible lack of managers that will understand what the results are telling them well enough to use it profitably. Even so, the benefits that Big Data will deliver to all industries, not just retail, and even the potential that it has to streamline national economies, will see Big Data being one of the major growth areas in the IT industry for decades to come.