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September 23, 2015

5 ways Big Data is changing retail

List: Drive down into your Big Data to find some retail value.

By James Nunns

Applying Big Data to your business can be tricky work, you need direction and strategy in order to apply the right data in the right ways.

If you get it right though, Big Data can provide a real competitive advantage and help you to save money and to make it.

Retail is a solid example of a market that is forging ahead with using data to get that advantage.

CBR has compiled a list of five ways Big Data is changing retail.

1. Focused marketing

Say goodbye to sifting through promotions and deals that don’t interest you at all. By analysing your buying habits, retailers can identify what you like to buy and tailor offers to fit you.

Last month you bought some new skinny jeans, but you were also looking at the shoe section. Perhaps you decided not to at the time but the site remembers and can suggest different types of shoes the next time you shop.

If you are signed up to receive newsletters from stores then they can also apply your data from your shopping habits, to provide a tailored newsletter.

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2. Shopper behaviour

Spotting shopper trends is vital for shops to stay on top of customer demand. Gone are the days of relying on a report once a month that will point you in the general direction of upcoming sales.

Now, stores can rely on minute by minute demand levels across their stores, highlight where stock demand for particular products are at their highest and make sure the store has, for example, enough cardigans in store.

This can be achieved by simply staying on top of your data, using a product like Oracle Retail can help a business to stay on top of their supply chain.

3. Pricing

Dynamic pricing is increasingly being used as retailers monitor what their competitors’ prices are. It is typically used in ecommerce, but as brick and mortar retailers modernise their stores, you should expect to see more digital displays.

This is linked into the Internet of Things, but it will be Big Data behind it. By being aware of shoppers habits, demand and competitors pricing, shops will be able to dynamically change their pricing.

4. Smarter stores

This was touched on with the previous point, but stores really are going to get smarter. Expect the layouts to change as technology like Swarm helps stores to track foot traffic, predict patterns and calculate the in-store conversion rate.

Some companies such as Nomi use data from tracking mobile phones to map your path around a store. This can then be fed back to the retailer to see how best to optimise the store.

This data isn’t used alone, as sales data can also be added to see what products do best and where to place them.

5. Logistics

Logistics is a broad subject area as it encapsulates areas such as delivery, stock levels, staff numbers and others.

It is in an area such as this that you can really put your data to work. Looking at a an area such as staff levels, you can make the decision whether or not you really need ten members of staff in on a Tuesday, if you know for a fact that foot traffic is at its lowest.

Also, should you only have enough stock for a slow Tuesday, if it is a Boxing day and you can see that it is likely to be your busiest day of the year.

If you can apply Big Data to your supply chain and reduce costs by maybe even one or two percent, that can really add up to make a difference to the big picture.

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