As of 2015, it is no longer really controversial to name data and its successful use as one of the key arrows in any retailer’s quiver. Retailers are almost always on the hunt for new and better ways to capture and leverage the data – in the backend, on the saleS floor, as part of customer acquisition and customer retention – because the digitally reinvented conventional wisdom is that the more the retailer knows, the better they can build.
What a merchant is “building better” depends on what their specific focus is at the time — merchandising, logistics, conversions, transaction security, driving repeat visits, etc. — but whatever it is and whatever channel it’s happening in, data is certainly set to make it better.
With such a heightened focus on dialing into the data on the part of merchants, not to mention the near explosion in startups that exist purely to facilitate greater facility with said retail analytics, it seems hard to imagine a serious complaint that retailers are under-utilizing data. Sure, occasionally misusing their data is always an option, as there are many stories of retailers leveraging their data into personalization that was way, way too personal for anyone involved. But not paying enough attention to their data or failing at interest in capitalizing it — that accusation is harder to imagine.
And yet, that is exactly what Dr. Alexandra Samuel is arguing is a fundamental problem in her latest piece for The Wall Street Journal. Retailers have lots of data, and with the coming advent of the Internet of Things, they will soon be sucking ever more amounts of data. And while the Harvard Business Review contributor and corporate media coach thinks that great news, it is also building into a rather large and underdeveloped opportunity to put that data to useful work.
Well in essence, merchants don’t want to play nice like they learned to in kindergarten — and they certainly don’t want to share all that data they’ve work so hard to gather. Instead, Samuels notes, they’re hoarding it in an attempt to protect it from the prying eyes of competitors — and as an unintended consequence protecting themselves from its benefit.
“That’s understandable,” Samuel notes. “A combination of competitive anxiety and security concerns means that businesses are loath to release their wealth of data. But those fears mean they are missing the much larger opportunity that data offers.”
Letting consumers have insight into their own data — and the aggregated data of others — brands Samuel argues, can influence their behavior, and if done right, guide some of that spend.
The Power Of Peer Pressure
Take for example, she notes, a media streaming company trying to grab up one of the more streaming enthusiastic demographics out there: parents of young children. She notes that a parent that can gain insight into something they might otherwise think to keep track of, say how many hours their children spend watching explosion-heavy cartoons. It might move a parent to cut back on screen time.
This effect is especially powerful, Samuel notes, when consumers are exposed to data aggregated from other similar consumers. The aforementioned parent might not be natively bothered by the knowledge their children are spending two hours per day watching cartoon characters explode things until they find out that other children their age are watching less than half that amount. Such information could trigger parents to cut back screen time.
“Or maybe I’ll sign up for that educational content the company has been promoting,” Samuel notes, “since I see that other children divide their time between watching cartoons and science shows much more than my son does.”
In a slightly different variation on the competitive parent and the edge provided by giving better data out, she notes booksellers have an incentive to offer data on book sales that are not just correlated to what titles sell the most — but also what books are bought by parents who buy more books than anyone else, the logic being parents who are often buying books presumably have children who are heavy readers.
“I can get a list of children’s bestsellers anywhere, but as a parent, I want to buy the books that will actually foster my child’s lifelong passion for reading,” Samuel mused. “That not only helps me be a more frequent customer today (by helping me choose what to buy) but also wins my long-run loyalty to a brand that shares my values.”
The Emerging Trend
Increases in openness in data sharing, particularly when it comes to retail information, may be slow in developing. There might be benefits to be gained, but taking one’s data, particularly the aggregated consumer information, to generate “blog posts and infographics, reports and press releases,” as Samuel suggests, but such sharing might rightly feel risky to a retailer.
She may be right that “any of [it] would be far more interesting, relevant and shareable than the typical content churned out by marketing teams,” but it would also provide a window into information that provides a competitive advantage merely because it is hard to come by.
Still, sharing has its fans, and some of them are pretty high profile.
Last week the notoriously-secretive-about-its-search-data Google announced its new Shopping Insights tool, which allows retailers to see what products are being searched for in 16,000 U.S. cities and towns. This early version scales across 5,000 products currently on sale through the Shopping ad service that month. The long-term plan includes a more extensive product list and updates that occur more often than monthly.
Google said the new tool is one of many tools designed to provide its merchant partners “with deeper insights about users’ intent and context.”
Now Google is at base a data analytics firm, so showing off its tools’ capabilities to merchants via a slight peek behind the search curtain makes sense — and will likely add to the approximately $2 billion in revenue Google Shopping currently captures.
Purer retail players (Amazon and Apple spring to mind) are less enthusiastic about sharing their data. The ecosystem can speculate — and in the case of Apple, PYMNTS does a better than good job of developing an estimate for Apple Pay’s use numbers — but the hard numbers, direct from the horse’s mouth, will remain a secret until the horse says otherwise.
Which seems, for now anyway, the likely future fate of retail data, particularly the really juicy stuff that might shock and amaze. Retailers may be able to cash in on sharing, but when they can convert more sales by holding, they probably will.