Retailers have become so adept at capturing and analyzing consumer data that there is now a real risk that they might alienate customers by revealing just much they know about our lifestyle, habits, and preferences. So if retailers want their big data investments to pay off, they must tread carefully.
Big data exploitation in retail is no longer restricted to tracking and responding to broad trends; it’s become very . Which is great if the result is that customers find exactly what they were looking for; less so if it feels intrusive or invasive.
Analytics technology is now so sophisticated that, by drawing on an individual’s loyalty-card records, payment histories and browsing habits, retail marketing programs can detect an alcohol problem, whether someone has lost their job (because spending drops and premium brands are replaced by “value” purchases), if they’re away on holiday, and much more besides. (A few years ago, before she knew herself.)
This is not to imply that retailers are necessarily doing anything wrong or sinister (customers may well have given consent for this kind of data usage). But it can be unnerving to think that every time we browse online or in a store, that activity is being monitored to build a picture of our entire lives. Just think how often we are pestered with unsolicited promotions related to a product we may have glanced at only once.
as they enter or pass by stores. Their activity can be registered—even if they don’t have a loyalty card or store app. In the US, meanwhile, regulations are now that safeguards protecting internet search histories are being dismantled. So the scope for overstepping the mark is growing.
Snooping vs. problem-solving
If retailers want to impress and retain customers, rather than undermine their trust, they need to turn their attention to more beneficial ways of applying algorithms and data discovery.
In , retailers are exploring ways of minimizing sales returns—a problem so costly across e-commerce that the likes of Amazon have gone so far as who do this too often. In the US alone, merchandise in 2015, roughly 8 percent of total sales, according to the National Retail Federation. Returns are a pain for customers, too: who wants the disappointment and hassle of having to send something back because it’s not quite right? A common cause of apparel returns is over-ordering, because consumers haven’t been confident of getting the right size; this is something the industry is now trying to address with new combinations of .
Another option is to use customer intelligence to provide a more responsive logistics service. Amazon has patented a shipping model that , so it can have the products waiting in a nearby warehouse for faster delivery. Combine this type of strategy with automated drone deliveries and the customer experience might soar while the cost of logistics (even the need for delivery partners) diminishes.
. The end justifies the means. Just as, if I go to my regular bar, it suits me that they’ll have my favorite drink ready for me before I’ve even taken a seat because of how well they know me. Though if that happened in a bar I’d never been to before, that would be unsettling. Context—and consent—matter.
If the result of deeper customer insight is something genuinely useful to the consumer, surrendering anonymity and sharing data becomes . People do appreciate easier access to the items they want, it does make their life easier if they don’t have to parcel up returns, and a timely recommendation can be useful in the right circumstances. So really, retailers just need to be a bit more thoughtful about how they apply their knowledge.
What isn’t in dispute is the . Figures from suggest that organizations that are able to exploit customer behavioral insights outperform their peers by 85 percent in sales growth, and more than 25 percent in gross margin. So keep building those data vaults and adding ever more sophisticated real-time analytics; the rest is down to using the insights to best effect.
This article is published as part of the IDG Contributor Network.