How to Design an AI Marketing Strategy

What the technology can do today—and what’s next

by

and

Dhruv Grewal

by

and

Dhruv Grewal

From the Magazine (July–August 2021) · Long read

Giulio Bonasera

01

How to Design an AI Marketing Strategy

02

Why You Aren’t Getting More from Your Marketing AI

03

Don’t Buy the Wrong Marketing Tech

Summary.

In order to realize AI’s giant potential, CMOs need to have a good grasp of the various kinds of applications available and how they may evolve. This article guides marketing executives through the current state of AI and presents a framework that will help them classify their existing projects and plan the effective rollout of future ones. It categorizes AI along two dimensions: intelligence level and whether it stands alone or is part of a broader platform. Simple stand-alone task-automation apps are a good place to start. But advanced, integrated apps that incorporate machine learning have the greatest potential to create value, so as firms build their capabilities, they should move toward those technologies.

Idea in Brief

The Challenge

At many firms, the marketing function is rapidly embracing artificial intelligence. But in order to fully realize the technology’s enormous potential, chief marketing officers must understand the various types of applications—and how they might evolve.

The Framework

Classifying AI by its intelligence level (whether it is simple task automation or uses advanced machine learning) and structure (whether it is a stand-alone application or is integrated into larger platforms) can help firms plan which technologies to pursue and when.

Implementation

Companies should take a stepped approach, starting with rule-based, stand-alone applications that help employees make better decisions, and over time deploying more-sophisticated and integrated AI systems in customer-facing situations.

Of all a company’s functions, marketing has perhaps the most to gain from artificial intelligence. Marketing’s core activities are understanding customer needs, matching them to products and services, and persuading people to buy—capabilities that AI can dramatically enhance. No wonder a 2018 McKinsey analysis of more than 400 advanced use cases showed that marketing was the domain where AI would contribute the greatest value.

A version of this article appeared in the July–August 2021 issue of Harvard Business Review.

Next In

Why You Aren’t Getting More from Your Marketing AI

Chances are, you haven’t asked the right questions.

Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, a visiting scholar at the MIT Initiative on the Digital Economy, and a senior adviser to Deloitte’s AI practice. He is a coauthor of All-in on AI: How Smart Companies Win Big with Artificial Intelligence (Harvard Business Review Press, 2023).
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Abhijit Guha is an associate professor of marketing at the Darla Moore School of Business, University of South Carolina.
DG

Dhruv Grewal holds the Toyota Chair in Commerce and Electronic Business and is a professor of marketing at Babson College. He is a coauthor of Marketing and Retailing Management and the author of Retail Marketing Management: The 5 Es of Retailing.