Retailers have never known more about their customers. The question is whether they know what to do with all that knowledge.
That distinction is becoming increasingly important as consumers, regulators and lawmakers scrutinize how companies use personal data, particularly when it comes to individualized pricing. The controversy over so-called surveillance pricing illustrates the danger: Personalization can make shopping more relevant and convenient, but it can also leave customers wondering whether the retailer is helping them — or exploiting them.
David Wachs, founder and chief executive officer of Handwrytten, offers a useful way to think about the difference. He divides personalization into two categories: “extractive” and “generous.”
Extractive personalization uses what a company knows about a customer to capture more value from that individual — perhaps determining that someone is relatively insensitive to price and therefore can be charged more. Generous personalization uses data to provide something useful: recommending a relevant product, acknowledging an anniversary or simply thanking someone for a purchase.
The first approach risks destroying trust. The second can strengthen it.
Wachs suggests a remarkably simple test for determining which side of the line a retailer is on: Would you be comfortable telling the customer, face to face, exactly what you are doing?
Telling someone, “We’re charging you more because you use an iPhone and live in an affluent ZIP code,” probably wouldn’t go over well. Using purchase history to recommend something that genuinely fits that customer’s interests is another matter entirely.
But even well-intentioned personalization can go too far. Wachs calls it the “personalization paradox”: the point at which a company appears to know so much about someone that helpful suddenly becomes creepy.
That suggests another rule: Just because you know something doesn’t mean you need to demonstrate that you know it.
Handwrytten, which helps companies build customer relationships through personalized handwritten notes, deliberately limits specificity. A note might thank “John” for a recent wallet purchase, for example, without reciting the exact model, size and features of the wallet. Excessive specificity can raise a red flag rather than create a connection.
The same principle applies to targeting. Wachs points to automobile dealers that can identify consumers who are statistically likely to be in the market for another vehicle. Rather than telling recipients, “Our data says you’re ready to buy a car,” the dealership can simply invite them to test-drive a new model. The underlying targeting can be sophisticated without making the customer feel surveilled.
That may be the most important lesson for retailers and brands. Data should operate quietly in the background, making the customer experience better rather than continually reminding shoppers how closely they are being watched.
Personalization works best when consumers experience its benefits without feeling its machinery.
Retailers have enormous opportunities to use customer data to improve recommendations, recognize loyalty, celebrate milestones and communicate more meaningfully. Those efforts can ultimately generate more spending and greater lifetime value — not because companies have figured out how to squeeze another dollar out of each transaction, but because customers actually want to come back.
The goal shouldn’t be to demonstrate how much you know about your customer.
It should be to demonstrate how much you value them.
