Will Big Data prove to be the saviour of the retail industry?

If knowledge is power then in today's increasingly digital world, Big Data could be the lifeblood that ensures the world's biggest retailers remain powerful. Gathering data on customers and suppliers is nothing new in the retail industry and Big Data as a term means pretty much what it says. Put simply, it gathers data in greater and larger amounts, before running it all through a computer programme to reveal many different and intrinsic aspects of human behaviour.

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According to a poll of 350 retail and consumer CEOs by JDA Software Group and PwC, reported here, more than two thirds are increasing spending on technology because they say this will make consumer experiences better. However, no company can do this effectively without first knowing what will make consumer experiences better and this can only be achieved by mining customer data and developing a more in-depth understanding.

What is also vital though is to constantly revaluate this data, reanalyse it and recast the net for it if a retailer is to gain and keep a competitive advantage. The plethora of data streams available means it could and perhaps should be refined on a daily basis. If it isn't then corporates might miss out on the many positives it brings such as shifts in online searches for certain goods, changes in shopping habits in-store or online and ultimately gravitations away from products due to price rises or rivals' offers.

Haven’t retailers always collected Big Data?

Loyalty cards in supermarkets were once the arbiter and oracle of consumer data. They tracked food, drink and household goods being bought, and then sent out offers and discounts to customers based on their buying habits. They knew when and where and how often people shopped and it was all thanks to someone swiping a card or scanning a keyfob at the checkout. And they were actively insentivised to do so through collecting points.

Technology had ensured loyalty cards became a more useful replacement for outdated postal questionnaires, previously sent out randomly to households to fill in, Many went into the bin rather than an envelope for sending back. Now consumers are actively encouraged to fill in surveys online in return for offers and gifts, doing so from the comfort of their own homes. Nielsen too runs a panel where people scan their household purchases once they get them home using a handheld device provided to them. In return, they will earn rewards and as they have actively chosen to take part, the results delivered are likely to be regular and robust.

Yes retailers have also always monitored footfall and stock churn in-store or buying habits online but whereas much of this would have been on a macro level, Big Data shines a far more micro lens on the numbers. Data can be collected from numerous sources in a consumer’s world and even when these numbers are hidden deep in massive data sets, individual correlations can be spotted that would previously have been impossible to uncover through traditional means. Applying immense computing power to this big data ensures scenarios are forecast to identify and predict trends both current and future. It’s no wonder behemoths such as Alibaba are now getting plugged into using Big Data.

So what changes in retail can Big Data now influence?

It is now increasingly important in the retail industry not to look at data in isolation. Big Data means you can collect, compare and contrast data sets for so many research uses. Whether it is data on your customers' shopping habits, numbers about your suppliers and raw goods or competitors' offers and ticket prices, separately each gives an answer. But together the bigger picture provided from the Big Data can drive organisational change on much higher and much deeper levels. Run them together and in seconds a company could identify a new cheaper product stream to sell online or a new placement for a product within a store that by switching to would increase conversion and profits.

Big Data does not only have to be collected online. New stores are being made more technologically advanced, for example sending Bluetooth alerts to mobile phones nearby to attract customers to enter or perhaps even fitting smart shelves using all sorts of sensors to know when they are running low or what products people are choosing. It could be extrapolated to give customers a discount at the till because they are identified as making their first purchase ever or they are known to be a loyal consumer who returns time and again. Using Big Data in this way could help bricks and mortar remain competitive and popular to hit back against their online rivals.

In this piece, the rise of Big Data within retail shows a wealth of opportunity. It finishes by talking about how such collections of data can also be vital for supply chains, making business more effective behind-the-scenes as well as on the shopfloor or front end of a website. Supply chain Big Data is also covered here talking of how the consumer experience can be improved if factories and suppliers become more deeply plugged into their clients and their own suppliers too.

But what does this mean for data security?

Successfully implementing a way to capture this data and then, crucially, to analyse it effectively is vital. Having a robust infrastructure where this data is stored safely and privately should go without saying. However, the rising proliferation of hacking attempts and hacking successes around the world, some against huge well-known brands and corporates, proves the danger we face. Such sensitive data must be as impenetrable as it can be. This danger is said to be the reason there was huge growth in the Cyber insurance sector in 2016. And as ZDNet reported back in 2015, the financial gain for hackers can be great, which means that comes at a big cost to the customers who may have provided the Big Data initially.

A data breach or hack can totally reverse the tide of success gained from collecting Big Data. Not only can it lead to fines or legal action, it impacts most negatively on the perception of a business and reduces the levels of trusts once loyal consumers had for it. It is true that a lot Big Data can be anonymised at source meaning personal details are never attached to it but this is not always the case.

Big Data is often most effective when it can be focused on an individual specifically. The easiest way to implement and ultimately monetize a Big Data retail strategy would still appear to still be harnessing the habits and interests of consumers and targeting them directly, whether via post, email or on social media. It is crucial then that with such masses of data to be protected, companies adhere to local, regional and national rules, laws and conventions to prevent Big Data becoming a big problem.

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