Michael Diamond
New York University
Book synopsis:
Marketers expect artificial intelligence (AI) to have trillions of dollars of impact on businesses and the economy, yet many struggle to understand what it is and how to apply it to their efforts. But businesses do not need to begin by mounting a gargantuan AI initiative. Instead, the authors argue, deploying a little bit of AI can go a long way toward increasing a company’s productivity, efficiency, and performance. They describe AI’s current potential and offer a glimpse into a future in which marketers and machines unite to run personalized and complex campaigns with great simplicity. Paul Roetzer and Mike Kaput’s book, Marketing Artificial Intelligence, does an excellent job in three important areas:
- It builds the case for businesses to adopt AI in their strategy, technology, and talent;
- It explains the foundational concepts of AI and its subspecies – machine learning, deep learning, conversational AI, and more;
- It establishes foundational frameworks for businesses to use in analyzing opportunities, assessing vendors, and internally reflecting on their own talent, capabilities, and organizational maturity.
Along the way, the book provides a series of well-structured, pragmatic explorations of AI’s impact on brand building, campaign development, and experience design, as well as strategy making, business planning, and innovation.
Moving forward, a company’s capacity to wield AI to build richer engagements with customers will be one of the strongest single markers of competitive advantage.
Marketer plus machine
The book’s foundation is the idea that “AI enhances human knowl-edge and capabilities … [so that] the future is marketer plus machine.” The authors highlight how machine-based intelligence is driving an exponential rate of change in the marketing field.
Much of the authors’ insight about how AI enhances our marketing ability applies to how we come to understand consumer engagement (CE). Central to CE is the desire of
humans for greater personalization and control in a complex world of choices. Using AI in consumer engagement allows brands to give agency back to the customer.
Roetzer and Kaput’s central argument is that, moving forward, a company’s capacity to wield AI to build richer engagements with customers will be one of the strongest single markers of competitive advantage.
Human-centered and data-driven
Roetzer and Kaput’s book reflects the idea that deepening customer engagement will always be both human-centered and data-driven. The authors argue that the current state of AI can more concretely fulfill the ambitions of anticipatory design and the intuitive Internet, which have informed discussions of customer engagement over the past two
decades.
The authors unpack how AI delivers deeper insights about consumer experience and behavior than were previously available. They argue that given context, prior activity, and design elements, AI can accurately predict consumer behaviors, which can then improve the customers’ experience.
The book provides much-needed frameworks and benchmarking tools which marketers can use to gain a deeper understanding of customer engagement. These instruments provide a strong, emerging set of criteria, testable in specific, individual cases and include: the Marketer-to-Machine Scale, which classifies five levels of automation so users can better understand how strongly a vendor’s offerings might affect their business; and the 5Ps of Marketing AI, a framework which we can use to analyze the current technological landscape.
As for Roetzer and Kaput’s 5Ps, planning, production, personalization, promotion and performance, three are particularly germane to the development of customer engagement: planning, personalization, and performance.
Planning
Building intelligent strategies calls for constructing accurate “personas based on needs, goals, intent and behavior,” among other traits. Authentic and responsive customer engagement requires that advertisers understand how customers connect with market strategies, evaluate how these connections create value, and respond to customers as they create connections.
Personalization
Personalization, “powering intelligent consumer experiences,” ensures that AI can drive both a more targeted set of incentives and overtures to engage consumers and more relevant content and conversations, through which it continues to learn and improve.
Performance
Performance, “turning data into intelligence,” uses AI to evaluate the return on investment (ROI) of customer engagement efforts. AI helps to determine how to reallocate investments across initiatives in response to new behaviors, such as increases in customer loyalty and satisfaction.
The broader challenge for practitioners applying artificial intelligence to customer engagement, however, is that CE is “a multidimensional concept” with “relevant cognitive, emotional and/or behavioral dimensions.”1 AI’s ability to enhance and influence these interactions changes as AI approaches human sentience limits. The advancement of AI into the domain of human sentience, it should be noted, brings up ethical risks to companies’ reputations.
Marketing Artificial Intelligence is a practical, well-researched, and applied introduction to how marketers can explore the new opportunities and directions which AI has created to deepen and enhance customer engagement.
Author Bio
Michael Diamond is a clinical assistant professor of integrated
marketing and communications at NYU’s School of Professional Studies. He was previously the acting CMO of Time Warner Cable and a strategy consultant for media, entertainment, and technology companies with Booz Allen Hamilton.
Endnote
- Brodie, Roderick J, Linda D. Hollebeek, Biljana Jurić, & Anna Ilić. “Customer Engagement: Conceptual Domain, Fundamental Propositions, and Implications for Research,” Journal of Service Research 14, no. 4 (2011), 252–271.