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Feb 5, 2013

Lies, Damned Lies, and Big Data



Is Big Data potentially the end of strategy for marketers? I don’t think so yet, but let’s take a look at the argument.

 Let’s start by defining what is a marketing strategy. Here’s how Wikipedia describes marketing strategy:

 Marketing strategy is a process that can allow an organization to concentrate its resources on the optimal opportunities with the goals of increasing sales and achieving a sustainable competitive advantage. Marketing strategy includes all basic and long-term activities in the field of marketing that deal with the analysis of the strategic initial situation of a company and the formulation, evaluation and selection of market-oriented strategies and therefore contribute to the goals of the company and its marketing objectives.

 We can distil this definition down to a series of functions which make up the marketing strategy process: allocation of resources, optimization of opportunities, analysis of the company or brand’s situation, formulation of sub-strategies (e.g. media, message, etc.) to achieve the objectives, and prioritization of those sub-strategies towards accomplishing the mission and goals of the company/brand. The notion that Big Data might make these functions automated, a ‘M2M created marketing strategy’ with limited need for human involvement, is based on the premise that for each of these processes, Big Data takes the guesswork and inference away from the marketer.

Take allocation of resources, for example. The old adage by Lord Leverhulme (and also credited to John Wanamaker) of ‘"half the money I spend on advertising is wasted; the trouble is I don’t know which half” is rapidly disappearing due to sophisticated analytics, measurable media channels, intelligent testing, and statistical modeling applied to virtually all marketing techniques. Data is at the heart of this change – where marketers used to simply blast messages out and credit/blame the creative or media for success or failure, today’s marketer knows who to send what message to, at the right time, through the right channel and can readily predict success. Or at least, in the case of GoDaddy’s latest Super Bowl ad , who will go ‘eugh’.

Similar arguments can be made for the other functions which make up the marketing strategy process. Increases in the volume and quality of data and data mining tools have changed how marketers prioritize opportunities, analyze their situation, and deploy sub-strategies. For example, where media presentations used to be at the end of the agency agenda well after the creative ‘drama’, it’s now towards the front and far beyond the ‘reach and frequency’ metrics of the last century. Much to the chagrin of the Creative Director, no doubt.

So if Big Data holds all the answers for marketers, surely we need only hire statisticians and techno-geeks as our CMOs? I tend to disagree, and align my views with those of Gord Hotchkiss. In a recent article, Gord made an interesting argument against the notion that Big Data may make strategy obsolete. He uses the analogy of driving a car to an unknown destination. In the pre-GPS days, you’d work out a strategy on how to get there – what major roads to take, the general direction, and how long it should take. Your strategy may involve planning the route, and estimating when you’re likely to arrive. It might have contingencies built in- e.g. suppose the Eisenhower Expressway still has that construction near Wolf Road? – and would rely on adjusting the strategy as you went to ensure you made it to the destination safely. With GPS providing data like turn by turn directions and upcoming road conditions, your need for a driving strategy has diminished – you simply execute the ‘tactic’ without need for a strategy. The role of a strategy is seen as filling in the data gaps for a marketer, where inference is needed. With fewer data gaps, the thinking goes, the less need for strategy. In short, Big Data conquers all. Arguing against this notion, Hotchkiss postulates that strategy is more than simply inference, but also synthesis and interpretation. It is these latter two characteristics that require the human element and experience. Big Data can provide the insights and fill in the gaps, but someone has to decide which of the mountain of insights are most important for the future strategic direction for the company or brand, as well as the impacts of external forces (government, competitors, culture) on that direction. Or to use the driving analogy, while the GPS may provide the optimal route and fastest time to our destination, sometimes the kids need the bathroom and the optimum is unattainable.












A modern strategist needs to rely on the insights from Big Data and deploy some artistic license and creativity in developing a strategy. Just as Apple famously never commissioned focus groups to launch the iPod, partly on the premise that no sane person would have ever wanted or needed 10,000 songs in their pocket, so must modern marketers rely on their experience, intuition, and imagination in developing compelling strategies.

For more compelling insights and thinking on marketing topics, please visit Robinson & Maites at http://robinsonmaites.com/