The Reclamation of Strategy

As has been shown time and again in the past few years, big data is surely one of the most important investments that a brand can make. Of course the stakes are huge — consulting and technology firm Capgemini has suggested that data can improve performance by 41 percent over a three year period.  So it’s no surprise that management consulting firm A.T. Kearney predicts the value of the big data tech market will rise to US$114 billion by 2018. Given the potential returns, what board would hesitate to sign off on a significant investment in big data?

But successfully using big data to improve a business means more than just collecting the information, or even analyzing it — companies must develop a strategy for how to use the information to build their brands. Unfortunately, many firms are using big data tactically, rather than strategically. Marketers, in particular, are not realizing the full potential of big data — rather than using it to strategically build brands, it’s mainly used to drive programmatic advertising.  This is highly tactical marketing, given the focused, granular tailoring of activity to shift specific behavioural performance metrics.

Perhaps this method might be justified if it was effective, but the jury is still out. While there are undoubtedly many success stories, a clutch of recent studies has questioned the degree to which brands are getting return on their investments. Gartner, for instance, reported that 60 percent of big data projects globally through 2017 will fail to go beyond the pilot and experimentation stage, and will be abandoned.

So what is a brand to do? There’s an entire industry full of consulting and technology companies eager to persuade organizations that the barriers to realizing greater insight and ROI from their data assets is merely further investment in big data technology. But this is not sufficient. To get real ROI from big data, marketers need to reclaim their strategic heritage and use big data to understand their markets in fundamentally new ways. Here’s what that might look like:

At the individual level: Social scientists have long been aware that different psychological attributes, such as our personalities, influence our purchasing decisions. However, this has largely been met with a shrug of the shoulders by marketers, not least because these factors can be hard to measure. Marketers have instead preferred attitudinal data which typically has a more direct (and easier to understand) relevance to consumer activities that marketers can influence.

However it is rapidly becoming clear that big data not only tells us what customers do but also how they think. A study by researchers at Microsoft and Cambridge University demonstrated just how much of our inner lives are revealed by very simple pieces of data. They found that Facebook likes revealed a wide range of information about participants from their personality to their voting preferences (even though these were not explicitly identified in the likes). So marketers now potentially have many more levers to play with from their big data assets. Technological advances have now made it a lot easier to start applying this information to good effect — rather than blind A/B testing, marketing communications can now be shaped by a strategic understanding of what underpins preference. For example, many brands are now starting to use this to undertake persuasion profiling of their customer base to understand what types of nudges are most effective at shaping customer activity.

At the social level: Another way in which marketers can make more strategic use of big data is to start exploring the way in which social relationships are revealed through data patterns, something very hard to do by other means such as market research surveys. Many of our beliefs, attitudes and behaviors are shaped by our social connections rather than, as classical marketing would suggest, our own individual preferences and experiences. A good way of thinking about this is to consider forest fires: The fire itself has its own properties in the way it spreads, which we can’t necessarily explain by examining the way in which individual trees burn. Big data allows us to look at the way in which social effects rather than individual preferences are shaping markets. There is now a huge amount of data which tracks exactly how behavior operates at a social level — phone logs, social media, messaging and so on. Studies by people such as Microsoft researcher Duncan Watts have demonstrated how patterns of relationships are themselves critical to preference formation in markets such as music downloads.

Network theory (which identifies the different patterns in the way we communicate with each other) is also relevant here, which Watts demonstrated with his Big Seed marketing strategy. He used large scale mailing lists for an initial “seeding” of viral messages to determine how social effects lead to sharing, to maximize the spread of a campaign. This approach never got widely adopted, perhaps reflecting the way in which marketers continue to resist looking at the world through the lens of individual influence rather than seeing the way in which the spider’s web of relationships is, in itself, a critical means of understanding how to build influence. Perhaps the time has come to re-evaluate this.

At the cultural level: An even more strategic opportunity for marketers is to explore data sets to understand how cultures are changing.  A good example of this is Google’s Ngram service, a digital database of about 4 percent of the world’s books published since 1800. This can help us to understand the ways in which ideas and language have evolved over time. Work by anthropology professors Alex Bentley and Michael J. O’Brien suggests that our use of buzzwords (which appeared in print) spread by social diffusion (copying) rather than reflecting the changes and developments in the topic itself. Hence, in their words, “when humans are overloaded with choices, they tend to copy others and follow trends, especially apparently successful ones.” This approach can of course provide brands with guidance on how to deliver campaigns by shifting their focus toward cultural learning rather than expecting an audience to adopt a message simply because the content is sound.  The point is that a new product may unarguably be an improvement on previous versions but if we ignore cultural learning as a means of communication then adoption rates may falter.

It takes something of a leap of faith to see the full creative potential of big data for marketers. Senior decision makers generally don’t yet fully understand the opportunity while the teams analyzing the data often have a technical rather than a marketing strategy skill set. The opportunities are sitting between these roles, failing to be identified and resourced. But the prize for those brave enough to go looking is invaluable. As human attributes can be identified from data trails, then marketing messages can now be delivered in a way that resonate and hit home so much more effectively. If we start to use data to identify how social relationships can influence attitude and behaviour change then marketing campaigns can take a powerful new direction, giving a whole new meaning to how we think about viral. And as data analytics show us which trends are in decline and which are in ascendance, then brands can put their best foot forward, anticipating consumers rather than reacting to them.

This article first appeared in strategy+business