The Christmas countdown is in full swing and for many shoppers the bells are not so much ringing out, as tolling. Scouring the high streets for gifts during the annual festive crush is something of a nightmare for most people – especially when you don’t have a clue what you’re looking for.
With record numbers of Christmas shoppers taking their custom online last year, the omni-channel experience is flourishing and predictive analytics is helping retailers to tell their customers what they want, when they want it. The result is a much deeper relationship with the customer, who now expects a certain level of personalisation throughout the retail experience. The question is whether retailers are offering a truly personalised experience, which is indicative of genuine customer curiosity – or are they simply box ticking within the fast-paced technological evolution of retail?
It is now standard practice for retailers to cultivate an online presence, sculpting customer relations through the likes of Facebook, Instagram and Twitter – with larger retailers drawing customers to their online stores through mobile apps. Marks & Spencer teamed up with Cloudera to create a fully integrated approach to data analytics, providing a 360-degree customer view offering a better understanding of purchase patterns and shopping behaviours across channels.
Similarly, John Lewis partnered with Adobe Analytics to revamp its website in 2013 and continue to monitor customer behaviour in real-time, to kerb any drops in conversion. High street giants are embracing the insights driven by an increasing band of armchair Christmas shoppers – based on the previous year, there was a 12 per cent increase in digital shoppers, spending a total of 24.4 billion. As we increasingly live our lives through our devices, the variety of information available to retailers has grown exponentially. But are they being creative enough with the data available?
A stand out example of how predictive analytics is innovating the retail experience and stopping short of true personalisation, takes us to the second largest retailer in America, Target, which predicted the pregnancy of a high schooler in Mississippi. For Target, expectant parents are the golden eggs – once collected during pregnancy, customers are likely to be loyal for life. So, it’s no surprise that the retail giant has gone to great lengths to extract insights from this arena.
Utilising in-app and in-store customer data, alongside purchased data, Target grinds down its customers’ behavioural patterns and develops more personalised product marketing campaigns – a service that is more sophisticated and contextually aware than the “you bought this, so buy this” model. In an eye-opening New York Times article the depth of these insights were revealed – to Target’s displeasure. For example, women buy increasing amounts of body lotion around the beginning of the second trimester; around the 20 week mark they load up on vitamins and in the final stages start stocking up on hand sanitizers and wash cloths.
And so an unassuming pregnant high schooler, yet to make her father aware of her predicament, was sent a pamphlet detailing products for expectant mothers. Cue: an enraged father storms down to the local branch, demanding to know why his daughter is being targeted with such products while still in school. The store manager had no idea why this would happen. However, when he called a week later to apologise further, the father had his own, sheepish apology – his daughter was pregnant, after all.
Data mining into the womb is impressive. But is the analysis delving far enough to offer the kind of context necessary to reflect each customers’ unique needs? It is one thing to understand the requirements of a general pregnancy – but had Target taken into consideration the age of their customer, a better understanding of the sensitivities surrounding this particular pregnancy could have enhanced their marketing strategy.
This question is particularly pertinent with the onslaught of the Christmas shop. With increasing numbers of shoppers moving online, it is not enough to box customers off into general categories – to truly help customers out, retailers delve deeper into our family lives and synthesise data sets to create a fuller picture. Retailers need to go beyond the basic ‘getting to know you’ questions to reveal the individual needs of their customers. When shopping for an awkward aunt, you don’t want suggestions like a cross-word book, when really she’s an avid hiker who can’t sit still for five minutes. While that sounds pedantic, the difference in the customer experience made by customer curious dialogue as opposed to a hopeful fumble in the dark is powerful.
In a Penton Marketing report, 63 per cent of retailers stated that they believe the use of data is either ‘very important’ or ‘critical’ to the success of their business. As our journeys through various apps are tracked, our location check ins stored and our calendars synced, retailers are getting better at utilising the data deluge – but there’s much more of it to come - and it's companies like NetApp that are responsible for managing that data.
As retail data sits in the cloud, ready for real-time analytics, customers are waiting to be shown what it is that they really want, and the only way to do this is through sophisticated data management techniques. This is enabled by a platform such as NetApp's Data Fabric, which allows data to flow seamlessly across multiple storage environments, from which retailers can make decisions based on mutliple sets of information about their customer.