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Turn Your Retail Data Into Dollars

Turn Your Retail Data Into Dollars

Turn Your Retail Data Into Dollars

There is a lot of potential in data mining and analytics, but the act of converting it into real revenue is what many businesses are currently having trouble with. It is now even more crucial to have a system that is capable of analyzing large data sets, due to the constantly increasing volume of information that companies receive every day.

A report by Wired states that an estimate of five quintillion bytes of data are created every two days. With this amount of data, several opportunities to improve business strategies are made available to those who want to turn current information into usable insight. While there is a lot of speculation and hype surrounding data analytics, the reality is that several real-world applications are proving the hype to be warranted.

Leading retail giant Walmart has reaped the benefits of the practice after achieving an increase of 10 to 15% in successfull online sales due to data analytics. This led to a whopping $1 billion in incremental revenue thanks to analytics. These results were found after careful examination of their e-commerce transactions both before and after they implemented a big data strategy that studies client buying behaviors.

For example, retail giant Walmart has been able to achieve a ten to 15 percent increase in completed online sales through careful analysis of information, leading to $1 billion in incremental revenue. These figures were obtained by examining e-commerce sales before and after the firm applied a data analytics strategy to study customer buying behavior and spot where changes could be made.

Similar results can be seen across many companies in the retail sector as predictive analytics helps businesses predict supplier and cusstomer demand, anticipate sales and compute the impact of several scenarios on their current activities, among other benefits.

The uses of data analytics aren’t limited to increasing sales, however. This practice is also often used to recognize fraud and cut down the time it takes to conduct audit activities. Finance departments are now realizing that analytics offers better efficiency with lower expenses and many businesses are adjusting their priorities accordingly.

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