Over the past 20 years, the capability for one person to turn their daily lives into a series of digital breadcrumbs has exploded. Every month, we see statistics suggesting that “every x days we create as much information as we did since the dawn of time / since the first computer / since the Second World War”.
All of this interaction, engagement and communication that we are creating, and indeed pretty much any recordable action that we take during our waking lives, is contributing to ‘Big Data’. From a humble tweet through to the purchase of a car, anything you do that can be stored in voluminous data warehouses worldwide is part of the Big Data picture.
But why has the term ‘Big Data’ become so pervasive recently? Probably for two broad reasons; the increasing speed and skill with which businesses and brands can capture all our disparate activities and the technological advances with which the same business and brands can aggregate this information together and begin to extract profit-shattering insights.
This mountain of information can, with the right structure and processes, be pinned back to the individual. But it isn’t a new concept. At a less complex level (principally because there were fewer customer ‘touchpoints’ in 1993) the DunnHumby approach to the launch of the Tesco Clubcard demonstrated the commercial value of integrated customer data and predictive analytics. At its heart was the facility to recommend products that would lead to a gradual increase in a customer’s spend with Tesco (thus removing that spend from their competitors).
This principle remains a key focus of ‘Big Data’ in the 21st Century, although the increase in complexity is considerable due to additional channels through which we can now communicate with brands. Unfortunately for brands and businesses, but fortunately for us as individuals, the arrival of these new channels has ushered in a new level of ownership of this communication.
Twitter’s latest figures put the UK userbase at 15m users (roughly 18% of the population), and it isn’t a captive audience that would have once responded, herd-like, to the soap opera adverts of the 1920’s, 30’s and 40’s. More often than not, a direct sales pitch via a social channel results in howls of derision and vitriol aimed at the brand (look at the responses to the majority of Twitter’s “Sponsored Tweets” as a guide).
Those brands that generate a considerable following are generally doing so by engaging and interacting with their followers (rather than talking at them) and by embracing the channel as a route through which honesty, guile and conversation tends to be rewarded.
So how does ‘Big Data’ fit into the social space? Well, it does and it doesn’t. The sentiment of the crowd online is a good steer for how a business is doing in the social arena, such as how well it deals with complaints, how often its content is shared and how quickly, if at all, it trends. So, at a corporate level, this crowd data can be integrated with more specific customer transactional data, site browsing behaviour and qualitative research, to help define an on-going business strategy.
So at the moment, whereas ‘Big Data’ may support an individual approach to the customer (via loyalty card tiering, vouchers, personalised email incentives etc.), we aren’t really there yet in pushing that information and knowledge back into the social media space with messages that meet the criteria of engaging without selling.
The ability to do this may change now that the Twitter IPO has been completed and there is pressure from shareholders to put their shoulders to the wheel. Pinterest recently announced it is looking to investigate “promoting pins”, for which the initial online response appears to have been bubbling unease but not immediate rejection. And Facebook has seen considerable drops in active users over the past 18 months in the UK, which may or may not be tied to more advertising and promotion on user newsfeeds.
