It is now clear that the Retail segment is investing in Big Data analytics sources and processes. The often cited reason is that retailers across the board are now seeing Amazon as a formidable competitor. The result is a desire among traditional “bricks and mortar” retailers to understand how online retailers, led by Amazon, are reaching their customers and to respond with a more competitive way to engage their own customers.
Hence, there is a strong interest among them to leverage data from social media feeds (Facebook, Twitter, etc.) and perform what has now come to be known as customer sentiment analysis. Williams Sonoma now has a VP of Customer Analytics to drive Big Data into its online and bricks and mortar marketplaces. His comment at a recent conference was: “We look at everything we’ve done to you and we can attach to you.” Soon, we may well see the emergence of the Corporate Analytics Officer.
But it’s not just the desire to leverage converge social media with individual customer data. Mobile communications and information platforms—smart phones and tablets—are also key to the way traditional retailers want to customize the retail floor shopping experience. In short, they want to combine the customized shopping experience of on-line shopping with the immediacy and fun of the boutiques and malls. And now a growing body of evidence says that Big Data is boosting sales and profits.
However, there is some risk for retailers worth considering: What happens when the analytics wizard gives customers false information? I’ll use myself as a case in point.
I’m coauthor of a book entitled “Inescapable Data – Harnessing the Power of Convergence.” You can find it on Amazon’s web site here. I freely admit that it’s not well written, out of date and out of print as well, but it does capture the essence of what we now call Big Data. But that’s beside the point I want to make.
Amazon as you’ve probably noticed has come up with all kinds of ways to offer you, in real time, other books and related products in which you might be interested. In my particular case, that includes other books by John Webster. Here’s the problem: They list the coauthor of the book as John G. Webster. Not so. You could buy “Inescapable Data” plus one more book from John G. Webster and discover some number of days later that the two books were totally unrelated to each other both in subject matter and authorship.
How would you feel at that point? Reactions could range from a mild shrug to anger and a sense that you’d been lied to. But no matter what your reaction, your trust in Amazon’s online shopping portal would be taken down a notch or two. And that’s my point. That’s where the risk lives for retailers who aspire to emulate this model. As a retailer, you want the enhanced shopping experience that analytics enables to foster customer loyalty. You’re trying to develop a sense that you know that customer on a more personal level. But what happens to customer loyalty and trust when the analytics engine makes mistakes?
Perhaps in this case you could follow Amazon’s lead again. I’ve informed Amazon about the erroneous link to John G. Webster, but it’s still there. I conclude that one of two things is going on. Either Amazon’s analytics processes have no way to check whether or not customers are being told the truth, or Amazon doesn’t really care whether or not they’re being misled. Sales are up. OK, so we lose a few customers because the machine makes mistakes. No big deal.
As a retailer, you could come to the same conclusion: that the benefit of real time analytics and the enhanced shopping experience that results is well worth the inherent risk of making mistakes that produce the exact opposite result. However, if you conclude otherwise it may be hard to find an alternative. You may conclude that a Big Data wizard that corrects himself when he makes mistakes hasn’t been born yet.