How to Design an AI Marketing Strategy

This article, published on July 01, 2021, by Thomas H. Davenport, Abhijit Guha, and Dhruv Grewal, serves as a strategic guide for Chief Marketing Officers (CMOs) aiming to effectively integrate Artificial Intelligence (AI) into their marketing operations. It underscores the significant potential of AI and provides a practical framework for categorizing and implementing AI applications within a business context.

Understanding AI's Role in Marketing

The authors stress that to fully capitalize on AI, CMOs must possess a thorough understanding of the various AI applications available and how they are likely to evolve. This includes grasping how AI can be strategically applied to enhance marketing functions, drive business growth, and create a competitive edge.

A Framework for Classifying AI Applications

The article proposes a dual-dimensional framework to help marketers classify AI initiatives:

Intelligence Level: This dimension ranges from basic automation of tasks to more complex cognitive abilities and decision-making processes.
Integration: This considers whether an AI application functions as a standalone tool or is part of a larger, interconnected system or platform.

This classification system is designed to assist marketing leaders in evaluating their existing AI projects and in formulating effective plans for future AI deployments.

Strategic Implementation of AI in Marketing

The article advocates for a phased approach to AI adoption, emphasizing a progression from simpler to more complex solutions:

Initiate with Simple Automation: The recommendation is to begin with straightforward, standalone AI applications that automate routine tasks. These are generally easier to implement, offer immediate benefits, and help build a foundational understanding and capability within the organization.
Advance Towards Integrated Solutions: As the organization's proficiency and maturity in using AI grow, the strategy should shift towards adopting more sophisticated, integrated AI solutions. These often leverage machine learning and have a greater capacity to generate substantial business value and competitive advantages.

Key Recommendations for CMOs

Strategic Alignment: Ensure that all AI initiatives are closely aligned with the overarching business objectives and specific marketing goals.
Capability Development: Focus on building internal expertise, talent, and the necessary technological infrastructure to support the successful adoption and scaling of AI.
Value Prioritization: Prioritize AI applications that demonstrate the highest potential for return on investment (ROI) and positive impact on customer engagement and business outcomes.
Continuous Learning and Adaptation: Stay informed about the latest advancements in AI technology and be prepared to adapt marketing strategies accordingly to maintain relevance and effectiveness.

By adopting this strategic and phased approach, CMOs can effectively design and implement AI-driven marketing strategies that foster growth, improve customer experiences, and solidify their organization's position in the competitive marketplace.

AI Marketing Strategy Framework