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How is global datafication helping customer experience management?

11th Sep 2013
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‘Big Data’ is an unpopular term – frequently maligned as yet another business buzzword. Despite this, professionals begrudgingly accept that it is important. It’s like a smelly kid in the playground that also happens to have the coolest toys.

But perhaps those that are sniffy about Big Data should speak to Timo Elliott, an innovation evangelist and 20-year veteran of SAP BusinessObjects. He defines Big Data as “Making use of data that was previously ignored because of technology limitations” – a succinct description that certainly doesn’t have the whiff of business BS.

And just so we’re clear – the amount of data that has been “previously ignored” is substantial. SAP CEO Bill McDermott recently estimated that a whopping 98% of any company’s data would be classified as ‘dark data’, locked up somewhere that it can’t be accessed or in a format that is unusable. The implications of unlocking that data are obvious.

“A lot of it is unstructured information,” elaborates Elliott. “Organisations are really good at analysing structured information - numbers. But unstructured information – text – has been hard to analyse. You’d need specific architecture, specific skills and for whatever reason people have had the time to invest in it.”

But the need to unlock value from this vast amount of data is becoming increasingly pressing. Ian Cheshire, chairman of the British Retail Consortium, recently gave a keynote speech stressing that it has never been more crucial to gain an understanding of customer information that exists throughout the business.

“Between the seismic shift in consumers’ expectations for their retail experience, and the ongoing economic gloom, retailers are faced with an extremely challenging landscape today,” he suggested. “Unlocking the value of customer data has emerged as the retail game-changer in this environment. Many big names have already disappeared from the UK High Street this year, and there will be many more to come if retailers fail to address the Big Data challenge, understand their customers and adapt to their needs.”

Meanwhile, the volume of data that businesses can tap into is increasing exponentially. This is a result of what Elliott calls “the datafication of everything”.

He elaborates: “There has been a massive leap forward in what we can do in terms of technology, and we’re generating massive amounts of information. We’re datafying lots of activities that were previously invisible. It could be anything from driving a car with telemetry, and the way that McLaren uses data to realise optimum performance of drivers and cars, to the way that my Kindle is watching me – the instant I finished Ken Follett's latest book, the next morning I got an email asking if I’d like to buy his next book. Our friends are datafied through Facebook. Our professional contacts are datafied through LinkedIn. Our health is datafied through the likes of Fitbit.”

Unlocking dark data

Fortunately, technology solutions are evolving to unlock the ‘dark data’ and glean insights from otherwise overlooked data – all at incredible speeds. SAP’s HANA platform, replete with its in-memory analytics, is of course the tool that is top of mind for Elliott.

“HANA has text analytics built in, so you can bring in a whole bunch of tweets or customer surveys or any unstructured information and we’ll trawl through it, figure out the sentiment and then you can start doing more of the traditional analytics on top of that, not as a standalone solution but combined with your transactional information and marketing campaign information. So if you’re doing a marketing campaign, you can find out whether it changed the sentiment and figure out whether the sentiment actually affects your sales. To do that means bringing together information from all sorts of sources but it’s now easier to do that than ever before.”

But by harnessing Big Data with these new tools brands can also make a real impression where the rubber meets the road, transforming the customer experience in real-time. Fashion brand Burberry and its flagship store in London is just one example.

Elliott explains: “The sales assistants have iPads so that as soon as you identify yourself, they have all your purchase history details and preferences to hand instantly. They’re trying to recreate the luxury experience of 100 years ago in the digital era. 100 years ago you would have a tailor who would know your size and know what cut you were interested in and would be able to go and offer things to you rather than you having to go and do it. And this is exactly what Burberry is doing.”

Big Data opens up the possibility of creating true personalisation, he explains – not just recommendations, but the actual experience itself. And one brand truly delivering on this is Disney. Disney has long used analytics to optimise the experience of its parks, monitoring where everybody is in the park to identify if queues are getting too big on particular rides, whereupon they would, for instance, move Mickey and Minnie Mouse to another area to attract people away from the busiest rides.

Similarly, if queues at specific stores in the park become too long, managers can quickly ensure that somebody from a till in another quieter store can come in and help, reducing the lines, improving customer satisfaction and improving profitability.

But now Disney is rolling out a new generation of technology, My Magic+, a billion dollar system that it believes will revolutionise theme parks. The innovation utilises customer wristbands with built in RFID chips, acting as a ticket, room key, credit card and fastpass to rides for visitors, while feeding traffic information back to Disney’s team to help better manage crowd patterns.

“Disney are still a little secretive about what they’re exactly doing, but they will be allowing you to customise your visit as much as possible, booking rides with more precision – so you are going to go on this particular ride at 3PM and this ride at 5PM – and that means you don’t have to line up as much,” says Elliott. “That’s always the big problem – everybody has to line up. But if you can coordinate every individual on an individual schedule, it could be solved.

“Now, obviously you can’t have people doing rides all day, back-to-back. The logistics don’t work. So they’re building more areas in the park which are general play areas for kids, for example. So you could do a ride, then the kids spend an hour in the play area, but you know that you've got your next ride coming up in an hour’s time – so you got an hour playing rather than an hour waiting in line because it's customised to you as an individual. 

“Or it could be that Disney realises that a family have a ride booked at five, but they see that they're still in the restaurant – so they automatically rebook them to a later ride and send them an alert. It's really customising the experience in ways which were just impossible before to provide that customer experience. And everybody is trying to figure out ways of doing this.”

And Big Data, despite its unpalatable name, increasingly looks like the way to succeed. 

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