32 Kellogg Insight cases for applying artificial intelligence to personalize the information and content to engage with customers at each step in the journey.” Building out a comprehensive, unified model of the customer experience sounds straightforward enough, but Sawhney explains that it can be sur - prisingly complicated in practice. Many executives lament the lack of a common database about their customers, for instance. “The frustration that they voice is, ‘We don’t have the data in one place. We have depart - ments and business units and geographies and silos. And unless we can stitch all the stuff together—and by the way, we don’t even have the same definition of a customer across the business units—we don’t have a seamless customer ID that we can track through all of those silos.’” This insight often leads companies to create a single platform to house data across all channels, stages, and interactions—and which can also house an automation engine. These are steps Sawhney strongly recom - mends that companies take before they begin to think seriously about making any other investments into analytics. “In order to be able to get full value from the analytics and AI efforts, you do need to put the foundations in place,” says Sawhney. Building a Better Funnel Once you’ve built out a unified model of the customer experience and developed a customer-data platform capable of tracking individual cus- tomer interactions, you are in a good position to test how to bring “care is the new commerce” to life. Specifically, this means determining which moments in the customer Based on insights from Mohan Sawhney