In today's digital age, where our lives are very rarely disconnected from some form of a data capturing device, be it our smartphone or TV, ubiquitous CCTV tracking, or credit card spending, the cataloguing of data touchpoints has become a mainstream fascination. Apple’s legal battles with the FBI over hacking the San Bernadino shooter’s phone, WhatsApp’s incredibly high-level encryption update, and Somerset House’s recent sellout ‘Big Bang Data’ exhibition in London—all symbols of growing interest in ‘big data’. But what is this data? Why is it big? And what does it all mean for brand guardians and marketers?
What seems certain is that ‘big data’ is a buzzword that is not going away. It might even come to define the narrative of our generation. It has become the essential method brands use to track growth, keep spot behavioural patterns and predict opportunities. Empirical data analytics, algorithms, deep learning and black boxes promise to provide magical coded systems that will unpick our lives and deliver mountains of future insight in the process.
But if these systems can deliver incredible speed and accuracy, they fundamentally struggle to provide any level of cultural or contextual understanding or meaning. They can tell us lots of ‘what’, but very little underlying ‘why’. If big data is truly going to provide game-changing insight, marketers need to expect deeper analysis of data. They need to refuse to settle for simple correlations and instead pursue understanding of causation and cultural context.
Many commentators are fetishising the scale of data ‘out there.’ But the big ideas of the future will come when deeper understandings yielded by both big and small data are applied. In a world where everything in our lives is tracked, finding a path through the volume of noise to get to sharp insight has become the biggest challenge.
Todd Yellin, Netflix's vice president of product innovation, recently said, “'Big data' is a cliché because people think it’s this magic mountain of gold. It’s not a magic mountain of gold. Most of it is trash which you have to separate and sort.”
Big data is only the fragmented breadcrumb trail—the tip of the iceberg. If we are to truly understand, and not simply track correlations in people’s behaviours, we need to go beyond the trail into the forest, and analyse the breadcrumbs themselves. “He who would search for pearls must dive below” wrote John Dryden.
The parallels to Albert Einstein’s famous quote: “Not everything that can be counted counts, and not everything that counts can be counted” also highlights the value of picking the needle out of the haystack, and showcases the need to discern the value behind the quantifiable.
For instance, the number of times the hashtag #foodporn was used in 2014 only becomes valuable when you understand its emotional and cultural drivers. For real insight, we must go into Yellin’s forest. We must go beyond automated algorithms into deep forensic exploration. We need to follow emotional online supply chains, from hashtags to YouTube comments, analysing the meaning of language, images, and videos to find the cultural nuances that occur across borders and that account for market differences.
A simple choice of emoji shared with friends or a single review is small data, but can lead to big ideas. These choice, small data points are traces of who our consumers really are and can say so much about the causes driving behaviour, particularly what’s emerging, which may not yet be peaking in big-data manifestations. In this world, data becomes the opening question, the start point and the catalyst, rather than a final answer.
It is evident that data can give us a wealth of information, but we also need other research tools to get to the heart of human experience. The analytical and curious human brain is still the best at discerning social and emotional drivers, understanding collective needs, and getting to grips with the often illogical rationales behind actions that defy probability. The magic of data understanding and future big ideas will come from the intersection of big data and expert human interpretation. To understand people’s data we need people just as much as we need data.
The real question that marketers need to ask themselves is: How far will data help us? We need to understand how data’s value is rooted in human interpretation; its value comes from the person reading it. The Big Bang Data exhibition ended on this note from Jonathan Harris’ manifesto ‘Data will help us’:
It will help advertisers see people as statistics, but will it help us remember those statistics are people? It will help us feel connected, but will it help us feel loved? It will help us uncover the facts, but will it help us be wise? It will help us keep count of everything in our lives, but will it help us understand that not everything that counts in our lives can be counted? It will help us see the world as it is, but will it help us see the world as it could be?
Marguerite Vernes is research executive, digital forensics, and Lee Fordham is associate director, digital strategy, at Flamingo London