Kellogg on Marketing, 3rd Edition

CHAPTER 20Leading with AI and Analytics

Eric T. Anderson and Florian Zettelmeyer

“How can we use AI and analytics to improve our marketing strategy and drive value?” Some form of this question routinely comes up in the analytics workshops run for leaders across industries. Even among marketing executives who are generally quite good at what they do, AI and analytics—we'll call it “AIA” here—remains a challenge for them, despite all the data they can access. In fact, in a survey of about 400 chief marketing officers, the leaders noted high barriers to using data, including lack of processes, tools, and talent for analytics.¹ That's a problem, given that as a marketing leader you need to draw on data‐driven decision making to create, sustain, and grow advantage for your business in an ever more competitive market. That reality is not going to change.²

Moreover, while it may be tempting to see AIA as a problem owned by AI, analytics, or data science groups, that's simply not the case. Every business leader, including those in marketing, has to see AIA as a leadership problem, take ownership of it, and use AIA proactively as part of their approach to strategy and tactics. Doing that effectively starts with gaining a working knowledge of data science, or what we call a high data science intuition quotient (DSIQ). It's important not to confuse DSIQ with expertise in data science; rather, DSIQ is about harnessing your existing critical thinking skills to gain a feel for what good ...