Big Data Is Running The $22 Trillion Retail Industry

Retailers are turning to data to improve their performance


A recent report by Frost and Sullivan discussed how big data and analytics are helping to power the retail industry. It is creating opportunities for growth and stability in this $22 trillion industry. Not only in the e-commerce space where complex data has been at the core of its success, but also in improving the fortunes of brick and mortar stores.

Data has played a key role in many brick and mortar stores, but today it is going beyond what has previously been considered. For instance, the interlinking of data sources has given retailers new opportunities to identify trends and more importantly, the root causes of them. This could be anything from the way that a display looks as customers walk past the window, through to how they walk through the store once they are inside.

It is no longer just tracking where people walk through a wifi network, there are now considerably more opportunities to tap into other data sources, often tracking actions before entering the shop or after leaving it. It means that the exact thinking of customers before they make a purchase is easier to find and moves can be made to take advantage of this.

An increase in how people are using the internet whilst in store (social media, researching competitors etc) and the retailers ability to track this is not a wholly positive thing though, as when this practice becomes more widely known, there are likely to be privacy concerns raised about it. Retailers therefore need to make sure they are totally transparent about what they are collecting and why, otherwise customers may be turned off the idea of entering one of their brick and mortar stores in future.

Although not perfect, data is playing a large part in how retailers are managing their stock levels. For instance, if there is a considerable discussion online about a particular product, the chances are that this will sell well and therefore stock could be increased. It is also possible to look at historical data in order to ascertain how well a product is likely to sell at a particular time of year. For instance, how much do the sales of electronics increase during the holiday season and can retailers therefore take advantage of this through accurate stock numbers?

Retailers who are not making the most of the potential data they can get from their clients are likely to be left behind as their competitors can develop more complex models to increase accuracy. This kind of work is becoming increasingly important in this space as brick and mortar stores find themselves under threat from e-commerce sites who are winning more market share every year. 


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