A recent discussion on Retailwire asks, “Does Big Data Have to Be So Big?” APT SVP Jonathan Marek had this to say on the matter:
Slowly but surely the industry is coming around to the rational point of view on Big Data. Bigness is not a virtue in and of itself. Actionable data is one step closer to the right end goal, because it starts to build in the idea of getting an ROI on data analysis. And here, there is also rightly a Bayesian aspect. Executives must have a deep understanding of how their business works, so that they can rightly assign the right level of belief in what the data is allegedly saying.
Retailers also need to learn that certain methods of analysis create more actionable insights. To take a silly, non-ad example: if I scrape social websites and see lots of customers think I should paint my stores green, so what? Maybe that gives me a hypothesis. But it doesn’t mean there will be ANY return on that investment. If I actually do it in 10 stores and see a statistically significant sales lift big enough to justify the investment, then that is much more actionable. And then, if I can use lots of data (dare I say Big Data?) to sort out which stores or customers show the greatest incremental lift, then I can further target the investment for greater return.
That’s the key. Big Data => cash ROI, not “interesting sounding ideas that seem like they will probably make me money”. Too much of the Big Data space is still in the latter world.