IBM has worked with Revive Vending to create systems for unmanned coffee shops that tap into the cognitive computing technology of Watson Analytics for data analysis.
Three unmanned Honest Café coffee shops are in operation in London, and another four are in the pipeline. The outlets offer a range of healthy and organic foods and juices alongside fair trade coffee, all through vending machines.
The lack of staff is a move by Revive Vending to reduce overheads and drive efficiency in café environments.
However, Mark Summerill, head of product development at Honest Café, said the automated approach means there is no interaction with customers. This can make it hard to build relationships and know the preferences of regular visitors.
"It's tough observing what our customers are saying and doing in our cafés," he said. "We don't know what our customers are into or what they look like. And as a startup it's crucial we know what sells and what areas we should push into."
While Honest Café does not have the staff to act on information on product purchases, it did have plenty of data, which is captured by the vending machines. However, the firm was not using this data to benefit its business.
"We lacked an effective way of analysing the data," Summerill said. "We don't have dedicated people on this and the data is sometimes hard pull to together to form a picture."
This is where Watson Analytics comes in. IBM's cloud-powered analytics service is used to crunch the vending machine data and form a picture of customers.
Summerill explained that Watson Analytics allows Honest Café to understand which customers sit and have a drink with friends, and which ones dash in to grab a quick coffee while on the move.
Transactional data is analysed to see how people pay for their food and drinks at certain times of the day so that Honest Café can automatically offer relevant promotions and products to individual customers.
Summerill is looking to build on the current analytics set-up in the Honest Café shops by using the Watson Analytics Personal edition to gain access to 25,000 tweets relevant to the café's datasets.
This will allow the company to use Twitter data to get better insights into what customers plan to buy, rather than reacting to historical purchases.
"Having direct access to Twitter data for insights into what our buyers are talking about is going to help augment our view and understanding of our customers even further," he said.
Modern retailers are digging into data and running it through analytics engines that take care of the technical and scientific complexities of data analysis, given the opportunities to increase sales and build brand loyalty from better insights into customer behaviour.
Miya Knights, senior research analyst at IDC, said that the mass of data generated by retailers through networked systems that cover retail activity can be used to support increasingly complex and sophisticated customer interactions.
"To retailers, big data presents a challenge and an opportunity to derive value from this analysis to inform business insight on four fronts, identified by IDC as customer loyalty, revenue growth, cost reduction and new business models," she said.
"The use of sales, customer and social data, as well as internal and external market and supply chain data, can help retailers optimise planning and forecasting capabilities in these areas."
Big data analysis is not the only technology trend retailers are tapping into, as cloud and mobile technologies are being harnessed by well-known high street brands.
Food retailer Pret A Manger has pushed large parts of its IT infrastructure into the cloud to bypass the need for highly skilled IT staff, which have become increasingly difficult to hire owing to the UK's digital skills gap.
Clothing brand Fat Face has adopted NetSuite's responsive web design software to make its e-commerce activities more suitable for smartphones and tablets.
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