111 Kellogg Insight what people write and track Instagram as a way to understand when and where you are showing up, as well as whom you should be targeting,” says Pah. Making Smart Recommendations Making recommendations is one of AI’s “oldest friends,” Pah says. Consider Amazon and Netflix matching customers’ past behavior with other products or movies they might like. Pah says the push to make more accurate recommendations is showing no signs of slowing—and here is another area where advances in natu - ral-language processing and image recognition are pushing the industry forward. Olay, for instance, has an app that allows customers to upload a photo of their own face so that its algorithm can suggest relevant skincare products. That’s a key advance, he says, given that most recommenda - tion engines are still based largely on what the consumer has previously bought. This can be a problem if customers have never before purchased a product in that category, are interested in truly novel products, or hav - en’t been happy with their earlier purchases. For instance, when it comes to skincare products, “I generally get what - ever is on sale,” Pah says. “So my past purchases are awful if you’re try - ing to help me actually take care of my skin.” Pah points out that the art of using image recognition to generate rec - ommendations is still being perfected: Olay’s app still requires users to Based on insights from Adam Pah