112 Kellogg Insight manually provide the app with a lot of information about their skin, for example. “We’re not entirely there yet,” he says. But the idea is right. “It’s actually pretty neat that they’re even trying,” Pah says. Privacy Concerns Are Growing. Companies Are Responding. Another step in providing more useful recommendations involves incor - porating data from a wider range of sources than we have seen histor - ically. “So far, we haven’t moved much beyond this platform-centric world: some website recommends something else on the same website,” Pah says. There are some signs this is changing. A few years ago, for instance, Pah received an email from TurboTax asking whether he would be interested in a machine-learning product that reviewed his tax returns, credit reports, and bank-account information to provide him with customized financial-planning advice. “That’s a step in the right direction,” he says. “We’re starting to recognize that we need to bring in data from everywhere to make more specific and useful recommendations.” But this would ultimately require an increase in cross-platform data sharing, a prospect that many—including customers, regulators, and even the platforms themselves—are starting to reconsider. Based on insights from Adam Pah