Humans have generated more data in the past two years than in the rest of history put together. This extraordinary fact, cited to the point of triteness in the data science community, propels a growing obsession with the field of “big data analytics.”
Big data has the potential to be a game changer for business leaders; from sorting healthcare information to optimizing industry operations, the data revolution promises huge cost savings and maximized efficiency for companies that join the wave.
Perhaps there is no group that will benefit more from the field than the marketing team. What was once a job based on intuitive guesses and catchy jingles, the marketer today has thousands of terabytes of data at his fingertips, which adds a much more scientific component to the strategy. People consume in patterns, and those patterns are stored in reams of binary code scattered across storage devices around the world. Yet, how are the next generation of CMOs—a role scarcely requiring a single statistics course, let alone the massive training in data science that is required to sort the material—supposed to find the information that is useful to them in this enormous sea of data?
The obvious answer that many point to is to hire a data scientist, and many companies have astutely done just that. According to a recent Wall Street Journal article on the subject, IHC—the largest hotel company in the world—launched a big data-backed campaign that involved over 1,500 customized messages to target specific groups using a data sciences team. The company has reported a 35% increase in customer conversions compared to their previous campaigns. Such results are astounding. Expectedly, the data scientist profession is one of the hottest fields these days, and companies are easily willing to pay well into six-figures to have this expertise on their bench.
But most companies do not have the budgets to invest millions of dollars on an in-house data team; luckily, a wave of big data entrepreneurs have recognized the problem and taken the lead in providing solutions. Tableau, a company that made big ripples in the tech world last week when it went public as a $2.5 billion company, boasts of its software’s ease-of use. It advertises on its homepage: “Put the power of analytics in everyone’s hands.” The software involves basic drag-and-drop functions, and truly works simply and intuitively. Entire models and graphs can be built just by copying and pasting a set of numbers into the program; the intimidating mounds of data (Tableau is capable of analyzing huge sets) instantly become colorful, translatable graphs with clear results.
CMOs cannot afford to ignore the technological change; a recent Bloomberg study in Europe found online retailers who used big data analytic tools grew at a rate of 24% per year over a 10-year period, compared to their less savvy competitors who essentially remained stagnant. Because of great solutions like Tableau, the extraordinary findings that can be reaped from big data are no longer limited to the few who had the courage to tough out a decade-long tenure in the statistics department. The CMO must invest in data analyzing technology of some sort if he wants to avoid competitive disadvantage in the near future.
The companies that are reinventing big data analysis are following the model of many great organizations: taking something complex and making it simple. The marketer of the next generation—whether from a large corporation or a burgeoning startup—will not have the time to sift through data ad infinitum. They will need actionable insights on how to build a brand and which consumers to target. Guided by these new and simplified technology solutions, the CMO will be able to do what he does best—sell a product—even better than before, without shuffling through all the corks and screws.
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