In the online world, it took us only a few years to get accustomed to the idea that firms can track our browsing behavior and predict our next steps.
People are full of contradictions, going through life saying one thing and then doing another. For example, people think they care a lot about data privacy, but they are often willing to use their data as currency.
We may have a gut-instinct to protect our privacy, but we are increasingly are also willing to trade that data for either convenience or money. As a professor of IT, business analytics, and marketing at New York University’s Stern School of Business, I have collaborated with telecom providers, advertisers and mobile-app developers to design massive real-world field experiments to understand just how quickly consumers are willing to give up their real-time location data to get personalized discounts.
For example, in one study conducted across 372 cities and towns in Germany, we involved the collaboration of 3,544 retailers, stores, and merchants. Firms uploaded coupons onto a mobile app, and by enabling their GPS feature and sharing their real-time location information, consumers were able to receive these deals. Consumer engagement rate of these location-based coupons exceeded that of other, more traditional mobile ads by a magnitude of three to 10 times.
In the online world, it took us only a few years to get accustomed to, and often even embrace, the idea that firms can track our browsing behavior and predict our next steps. But a similar revolution is about to hit us offline.
When it comes to our movements in real life, not cyberland, firms can measure when we walk past their physical stores, when we come through the front entrance, when we walk up to the fifth floor and so on. This kind of trajectory data about our walking patterns can be immensely useful in predicting our shopping preferences.
To find out whether consumers would be willing to give up their physical location in exchange for benefits, my co-authors and I conducted a set of elaborate studies at one of the largest shopping malls in China. The mall contains over 300 stores spanning 1.3 million square feet and attracts more than 100,000 visitors per day.
At the entrance of the mall, customers were offered the option of accessing free Wi-Fi service in exchange for allowing the mall to monitor their shopping trajectories and send them personalized coupons and ads as they went about their shopping. My initial expectation was a very small number of customers would opt in to this kind of explicit data-sharing relationship with the mall. But as it turned out, more than 75 percent of customers opted in, basically saying, “Take my data and give me an offer I can’t refuse.”
As these opt-ins become more and more common—and harder and harder to avoid—I believe a model will soon emerge in which people will pay a premium for data privacy. Put another way, people are beginning to demand a fair exchange for their data and want to negotiate the terms with brands to mutual advantage.
For example, last year when AT&T deployed its high-speed fiber internet service to compete with Google Fiber, it had an interesting pricing model in Kansas that captured this concept of a “privacy premium.” The service was priced at $70 a month to match the price of Google Fiber—but if subscribers chose to opt out of AT&T’s “Internet Preferences” program, which recorded users’ browsing and search history, they would have to shell out an extra $29 a month.
This kind of a market is now even more likely to emerge with the new Federal Communications Commission laws the Trump administration recently introduced that do not require ISPs to seek explicit permission to share sensitive data like financial or health information and browsing history. This will, in fact, be a real test for how much of a premium people will be willing to pay ISPs to protect their data privacy.
I believe the increasing recognition of give-and-take between customers and businesses is a good thing. If consumers want to avoid intrusive or irrelevant ads, they can disclose information about their preferences. By sharing their data, customers make it much easier for businesses to curate relevant offers for them, which in the long term makes the whole advertising process less annoying and overwhelming for the user and more successful for the advertiser.
In the future, the advertisements people watch on TV will even be customized on the basis of real-time physiological and emotional data provided by their wearable devices and transmitted through the smartphones to addressable TVs.
But mobile should be used as a butler or a concierge, not a stalker. Firms need to responsibly uphold their side of the deal: They need to surprise and impress consumers while helping them with their needs. After all, sometimes a marketing offer pops up out of nowhere at the right time and helps us, thanks to the data we’ve shared. We attribute it to coincidence, karma, luck, or fate. But it was all planned in advance, driven by data, curated just for you.
Instead of fearing sharing data, we should feel comfortable with it—and even start getting excited about it. Rarely do we enter an economic era when the technological upside is so positive for both consumers and the firms that live up to their end of the bargain.