Intel UK's strategic marketing director Elaine Cook says using data correctly can help boost sales

Intel: ‘Big data’ can revitalise retail

More and more retailers are finding that ‘big data’ can help boost sales, when used in the right way, says Intel UK’s Elaine Cook.

The strategic marketing director for retail technology was speaking at an Ecommerce Expo keynote about big data – a term used to describe complex data sets which can be difficult to process.

"Retail may have started to turn a corner with big data. More retailers are finding that big data can revitalise their industry which is challenged by the economy and mobile profiling [or ‘showrooming’].

"There’s increased investment in tech in the retail space. 1TB of data now costs about £50 a year. As costs come down, retailers are able to see the benefits.

"Retailers using big data to its full potential could increase operating margins by 60 per cent according to a report by Mckinsey."

Cook mentioned that 54 per cent of customers abandon a purchase in-store after checking info online using their smartphone.

She also stressed the importance of omnichannel, and said that customers who used both online and in-store channels spend 36 per cent more than single-channel shoppers.

Cook said that the "explosion of data presents new business opportunities" and that retailers, by analysing sales data and other data in the right way, can benefit. 

"You have to turn data into something useful in order to monetise it," Cook added. "Make it relevant to retail – for example being able to take data and start predicting what the hot products will be this Christmas. 

"Every two years, the amount of info available to retailers is doubling. 

"For smaller companies, you need to look at what business problems you are trying to solve. What data sources do I have available to me? Then work to produce something meaningful that helps drive your business forward.

"Can you get weekly sales reports daily or every few hours to increase efficiency and spot trends?

"To tackle a problem, look at the data, look at a solution, then implement that solution.

"Trying and seeing if something works – then refining it – is way to go with big data."

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