Big Data For Retail: Trends and Prospects
Big Data has revolutionized retail. By analyzing information about consumer behavior, sellers are able to pinpoint trends, identify preferences, predict demand, and optimize supply. Let’s talk about the current status and prospects of using Big Data in retail.
Big Data has revolutionized retail. By analyzing information about consumer behavior, sellers are able to pinpoint trends, identify preferences, forecast demand, and optimize supply. Let’s talk about the current status and prospects of using Big Data in retail. If you are looking for good training on Big Data, then check out this Big Data Training from a recognized training partner that will help you learn and master Big Data from scratch to help you pursue your dream.
Currently, the main goal of using Big Data in retail is to monetize data to increase store profits. To do this, salespeople use predictive modeling based on machine learning technologies by analyzing:
- consumer behavior in the online space;
- content of checks.
All this became possible relatively recently due to the removal of the restrictions imposed earlier by server capacities. Retail has gained access to huge streams of information and its parallel processing on different machines.
What does the future hold for us?
It is likely that in a few years’ time stores will be able to personalize the offer for each customer.
- The same product will have a different value for two different consumers.
- On the same advertising medium, each client will display its own advertisement, which is relevant and most effective for him.
- Thanks to biometric identification technologies, stores will stop using traditional loyalty cards.
What Technologies Will Shape the Future of Retail and Big Data?
Cloud technologies are gaining more and more popularity in recent years, allowing to reduce the cost of building and maintaining the infrastructure necessary for analyzing big data. Moving processing to the cloud also saves on human resources.
An important advantage that any cloud infrastructure possesses is its high scalability and flexibility. If necessary, the retailer can increase (during peak periods) or, conversely, reduce it (during periods of downtime) at no additional cost.
These capabilities greatly optimize the operation and maintenance of the infrastructure and increase its reliability.
Big Data literally translates into Russian as “Big Data”. This term defines the masses of information that cannot be processed or analyzed using traditional methods using human labor and desktop computers. The peculiarity of big data consulting is that the data array continues to grow exponentially over time, therefore, the computing power of supercomputers is required for the operational analysis of the collected materials. Accordingly, Big Data processing requires cost-effective, innovative methods of processing information and providing conclusions. Big Data characterizes the large volume of structured and unstructured data that is generated every minute in the digital environment. IBM claims that in the world, enterprises generate nearly 2.5 quintillion bytes of data every day! And 90% of the global data was received only in the last 2 years.
But it is not the amount of information that is important, but the possibilities that its analysis gives. One of the main advantages of Big Data is predictive analysis. Big Data analytics tools predict the results of strategic decisions, which optimizes operational efficiency and reduces company risks.