(Image courtesy of R-Bloggers – shows McLaren Telemmetry data from Australian Grand Prix, 2010 – Jenson Button driving)
This piece comes courtesy of Warc giving me the keys to the kingdom for a look at what they’ve got. And I thought I’d stress-test it on a relatively new topic, like “Big Data”. The company I co-founded nearly 3 years ago, called Fabric, is focused on this world of Big Data, so it’s a topic close to our hearts. I got involved because I believe Big Data is the future of planning – at least, planning done well. Now, that may sound a bit over-enthusiastic, but here’s why…
Planning focuses on uncovering consumer behaviours that prompt change or growth: a change of perspective or understanding, growth in a certain behaviour, a change in awareness of what’s possible, growth in sales, and so on. In other words, we look for things that people are interested in, that they’ll react to – thoughts and ideas that are motivating – and we give those ideas to creatives who are tasked with making them potent, compelling and engaging.
This is exactly what Big Data can help us do. Not just any old “Big” bit of “Data”, but the paths people take and the engagements they undertake around digital content. The behaviours of people, when they’re acting naturally, not what they claim to do when they’re sitting in focus groups (something we’ve all had to learn to filter to find the truth). Now, Big Data is often misunderstood or misattributed. It’s seen as online Buzz – a great big pipe full of Twitter commentary, blog updates, forum conversation and sales messages. It’s often viewed as being great for reporting, more than upfront workl. Or it’s seen as a substitute for research, but within the same old mold (when, in fact, Big Data may well become the inspiration that prompts the qualitative research to dig deeper and explore more).
For me, the interesting pipe of data is real behaviour, writ large across all people’s digital connections. And, much as it’s fantastic to see social commentary around a brand, I believe the more valuable insight comes from behaviour, rather than buzz. Behaviour online will soon include more of the advertising world through TV over IP, but right now, today, it includes a huge amount of data: location information, app interactions, browsing behaviour, price-searching, sales behaviour.
Now, I don’t want (nor is it acceptable) to see what an individual, we’ll call “James Q”, is doing on Tuesday, but I do want to see what a hundred thousand people who are very similar to James are doing that makes Tuesday different from any other day of the week; how important that YouTube video can be along a path to purchase; what FaceBook really means in terms of brand preference, predisposition or loyalty; how repetition may genuinely work or how much more important distinctiveness is vs differentiation (see Mythbuster in Oct 2012 Admap for more on that topic).
Face it; the trails of behaviour online are fast becoming a facsimile for everyday behaviours. Take car purchase, for example: the process of browsing, deciding, spec’ing up, spec’ing back down and finding the right model at the right price is all achievable online, so large volumes of people do just that. Even if they do not make the final purchase online, the important behaviours are being displayed and can be reviewed.
And this is what Big Data delivers on a plate, so long as you’ve got the technology in place to sift through it (which is what we’re delivering and developing at Fabric, incidentally). You can now get a connected view of your customer – within groups or segments – and see what levers are most important in terms of conversion, social engagement or simply viewing activity. You can map out common journeys and you can see changes in activity within days or weeks… the main constraint now is the depth of content you’re analysing – and, therefore, what you can derive from it. It’s a planners’ dream: Real behaviour, not claimed. Able to take a myriad of queries so you can dig for insights.
Wouldn’t that be a seismic shift for planning? Briefs built on concrete behaviour; rather than a hopeful whim, backed by some Googled evidence. It’s still going to require planners to build hypotheses, make lateral jumps and create meaning within the data. But imagine doing that with a new source – one that is fundamentally more concrete and doesn’t rely on people ‘reporting’ their own (wishful) behaviour.
It’s how Amazon knows what to recommend at an individual level when you’re shopping (and why you buy things you didn’t go looking for!). It’s how American Express could predict your divorce, with an 80% success rate, TWO years before it happens (based on the divergent behaviour between a couple). It’s how a couple of HP engineers were able to predict opening movie takings with more accuracy than the leading Hollywood firm. And how Google Flu trends became a valuable source of data for the Centre for Disease Control (based on search data, rather than hospital admissions and Doctors reports). Big Data doesn’t discriminate and it doesn’t require a pre-defined sample, so it’s how we’ve helped a brand uncover a male audience for what they assumed was a female beauty product. Despite the fact that not a person on the team expected to see that – and, normally, we wouldn’t have looked. And it’s why we believe that clients need to “own” their own data. Because, as data becomes more valuable, clients need to be able to mine it themselves and they need to be able to open up access to any agency they work with. So all of us, particularly planners, can dig in to find new insights, new opportunities and new connections.
So, with all this in mind, how good is Warc on what is still a ‘growth topic’ in its infancy, rather than an embedded subject or a major brand with numerous case studies? Well. Surprisingly good, I’d say – I quickly found a trove of articles, thought pieces, news and talks. I’ve picked my top 5 – things you absolutely should take the time to read – and a great example of the sort of content that’s swimming around on Warc. This content is not normally available, but you can access it for free by signing up for a free trial (click through and you’ll get to a page where you can sign in or sign up for the free trial):
“To plan in Planning 2.537 is to be on the front lines. Planning will see the transition from data ownership to data usage, and with this there will be an urgent need for many brands to reposition their offering. If data becomes standardised, then the ‘what’ part of data becomes less significant; the playing field moves from data ownership to intelligent data usage. And this is where the strategic prowess of the agency’s planner will flourish. […] To the individual planner, this means a more proficient understanding of data and how it can be used, and to what advantage. Knowing what data is important to the brand, why it is important, and how it can be leveraged to create a more compelling brand proposition will be critical.”
Author: Joseph Morgan (the Glue/isobar planner, not the actor)
The influx of data can cause two responses in planners: that it is cumbersome to the intuitive nature of their creative style or that it is an opportunity to take the intuition out of planning and ground it all in research. However, regardless of approach, data is set to play a growing role in the future of planning. As increasing numbers of websites require the same basic data from its users, consumers will tire of repeatedly supplying their data. Instead, they will carry with them a set of data that can be accessed by the company they are interacting with. As the web changes, planning will take on a transitional role during the shift from data ownership to data usage.
Why I think you should read it:
One of the shortlisted entries for the Admap 2012 prize. It’s like reading William Gibson on Planning, but less “noir”. Great thinking that gets you thinking.
“Insight professionals must become more like storytellers to make the data they present more engaging – and more likely to be acted on by clients.”
Ray Poynter, senior vice president at Vision Critical
Author: Joseph Clift (Web Producer for Warc)
A report from Datacentric, an event organised by Warc. Among the major themes discussed by presenters are: that the rise of “big data” has helped firms to tap new sources of information about customers, giving them the ability to optimise communications in real time; that clients are using online data in a variety of ways, and with varying degrees of success; and that the regulatory environment, particularly for web cookies, is likely to get considerably tougher in future.
Why I think you should read it:
It’s fair to say, they nailed the ‘regulatory environment for cookies’ prediction, even if the end result wasn’t quite as tough as everyone expected/feared! You get a sense of the opportunities beginning to open up at a client and agency level. There are practical examples in here. And, frankly, Ray’s quote is a gem.
“For many of us, being exposed to the hosepipe of data makes it harder to engage with data in the same way. Some of us default to the ostrich position, others seek a silver bullet that we hope will make analysing everything else less necessary. And the temptation to boil the ocean doesn’t help us much either – digging deeper and deeper, becoming more and more precise.”
Author: Mark Earls (@herdmeister)
Today’s marketers have access to massive amounts consumer data but they need to learn to use the ‘data hydrant’. It is important to be less precise – to draw bigger conclusions from large datasets by spotting important patterns, rather than smaller ones at lower levels of granularity. There is greater access to more data than any previous generation of marketers have ever had – which could help with understanding consumers. It’s important not to get bogged down in detail and instead focus on the overall patterns.
Why I think you should read it:
Mark Earls writes that “it is important to be less precise – to draw bigger conclusions from large datasets by spotting important patterns, rather than smaller ones at lower levels of granularity” in a typically brilliant piece of writing that eschews granularity for ‘patterns’ of data that show over-riding insights. And he’s right, too. One of the big issues that will threaten ‘Big Data’ is the misuse and resulting poor insight that is wrought by a heavy-handed analysis. Not least that, with so much detail, where do you look? And how do you sift for insights amongst all those ‘findings’? But that’s a topic for another day. Or just read Mark’s piece.
“In a world where data is freely available in infinite volumes, the role of the market researcher is no longer about collecting data. It is about interpreting data, curating content, and compelling action. As the futurist Af Rolf Jensen once proclaimed, “The highest-paid person in the first half of the next century will be the “storyteller”. The value of products will depend on the story they tell.” This could not be truer of the research profession and most certainly applies to today’s environment.”
Authors: Shelley Zalis, Jill Wiltfong, Graham Saxton and Michael Rodenburgh.
This paper argues that traditional, structured research is becoming more and more difficult. People are ‘always on’ as they connect in a socially networked mobile environment, exchanging words, pictures and videos. The more they experience this dynamic, two-way engagement, the less they want to be involved in old and slow research methods. Shelley Zalis, of OTX Ipsos Open Thinking Exchange, argues that the future is about ‘socialising’ research so that consumers are engaged in ways that capitalise on and mimic their expectations in today’s world.
Why I think you should read it:
This is a great piece of thinking from a cluster of authors (all part of the Ipsos Open Thinking Exchange). They may be focused on the impact of Big Data on the world of research, but it’s a great read. They’re arguing for the future of research and the shift in role of the researcher, but in a mind-expanding way that makes you want to hire them instantly. I just wish I knew which of them was the real pioneer!
“Computers are becoming mentalists. A big breakthrough has been the delivery of the promise by Big Data to tell the story of markets and customers in a way that nobody could do before, and to do this in a faster and richer way than ever before. Moreover, concerns about Big Data not answering the ‘why’ questions have proved misplaced. Big Data, with intelligent interpretation, data triangulation and intuitive interpretive flair, is now providing the ‘what, when, where, how and why’.”
Authors: Elisabetta Osta and David Smith.
This ESOMAR paper’s authors present a view of what market research will look like in 2030. They discuss Big Data, facial expression recognition, experience immmersion rooms, customer insight facilitators, man-to-machine communications and instant infographics. In essence, it will make sense for the most adept researcher in the business to become the CEO.
Why I think you should read it:
This is a fantastical view of what’s shifting and how it will affect both marketing and research in the next 18 years. It’s laced with real, current references, but it’s speculative and intentionally provocative. They’ve written in a way that’s got a sense of humour on top of an interesting perspective, which makes it all the more readable. Even if you don’t accept the end point, I’d bet you see a lot of it come true.