The AI Marketing Canvas

“We urge you to become that marketing leader whose obsession is to find ways to use Al and machine learning not only to personalize the customer journey at every juncture, but also to add humanity back into your brands wherever possible."

-Jim Lecinski and Raj Venkatesan

The AI Marketing Canvas provides a roadmap for marketers to optimize experiences across the end-to-end customer journey leveraging AI and machine learning. The book is based on a broad set of interviews the two professors conducted, as well as their engagement with business leaders for education and training programs.

The book is not just for larger brands. It’s also written for emerging brands looking to achieve hyper growth and build competitive advantage through a culture of experimentation.

The Five Stages of Maturity

The AI-Marketing Canvas is organized around five stages of maturity that companies go through as they tap into the power of AI-and machine learning: Foundation, Experimentation, Expansion, Transformation, and Monetization. Early in their journey, companies nurture an agile test-and-learn approach working with leading platforms that apply AI and machine learning to do things at scale that wouldn’t be possible if humans had to do them. This helps them achieve the promise of personalization, which has been constrained by the human effort required to bring together the data, introduce greater creative variety, and run thousands of experiments. Rapid advances in AI are dramatically lowering the effort required. As companies progress through their journey across the five stages, they evaluate where to build, buy, or partner to strengthen capabilities across a broader set of use cases.

AI Relationship Moments

These AI-powered capabilities enable experience as a winning strategy, which is the focus of my own Substack I’m collaborating on with Randall Rothenberg called Winning Experience. In their book, Jim and Raj show how you can apply AI and machine learning across four distinct Customer Relationship Moments to build a stronger emotional connection with your customers. The customer journey starts with acquisition, leveraging AI to enhance targeting and optimize content-based experiences. While at Google Jim coined the phrase the Zero Moment of Truth (ZMOT) to describe how brands use search and social media to engage with customers prior to their initial purchase. The journey continues with retention, as customers make replenishment orders and engage with brands for experiences that go beyond the functional benefits of products and services. Growth occurs as companies deepen customer relationships, leveraging data and personalized experiences to get customers to buy new products or upgrade their service. Finally, advocacy is reinforced through experiences that foster deeper meaning, sharing, and community around the brand.

The authors lay out how AI has accelerated the evolution of data-driven marketing, bringing us closer to the promise of 1:1 personalization and real-time experimentation. We left behind the era of mass marketing in the 1960s, as brands adopted more segmented approaches to marketing in the period leading up to the millennium. Post 2000, brands leveraged advances in data analytics to move from a few segments to hundreds. More recently, breakthroughs in AI and machine learning are finally unlocking the full promise of personalized marketing, where a company can use AI-powered journey orchestration to tailor the experience for customers in the moment. As Jim and Raj put it, “when data and algorithms are the nucleus of the model, they become AI Relationship Moments.”

Networks and Nodes

Another core concept in the book is the interplay between networks and nodes. Networks are made up of nodes, for example how railway and telegraph networks were built with many interlocking nodes. Digitization of business models has increased the importance of network effects, where there is a winner-take-all dynamic where the more customers there are connected to a network, the more value there is to being part of that network. Amazon, Facebook, Netflix, YouTube, eBay, and AirBnB were early digital leaders tapping into network effects. Consumer brands act like nodes within retailers’ networks that help them reach consumers. Apple was originally a node but became a network when it launched its app store. Netflix and Amazon are examples of hybrid networks and nodes given the evolution of their value propositions into producing original content. As brands invest in building direct-to-consumer relationships, leveraging data to create more personalized experiences powered by AI and machine learning, they are becoming hybrid businesses, too, with characteristics of both networks and nodes.

In their book, Jim and Raj show how some companies are not only transitioning from nodes to networks along their journey to build a stronger culture of experimentation for AI Relationship Moments but are also in-sourcing capabilities and monetizing them through new business models. Amazon pioneered this early on when it built Amazon Web Services, leveraging its capabilities for cloud-based data analytics to let others ride on its networks’ rails. Walmart has leveraged its capabilities system for last mile logistics to provide solutions to local companies such as bakeries, auto parts stores and other SMBs. The book includes other examples like Starbucks, H&M, and Coca-Cola for how companies are monetizing their capabilities systems.

Key Questions to Address Along the 5 Stages of Maturity

The AI Marketing Canvas builds on the Business Model Canvas introduced by Alexander Osterwalder in his 2004 dissertation that put nine building blocks on a page. It is designed to help marketers address 9 key questions to navigate their journey to apply AI and machine learning across AI Relationship Moments and progress through the 5 stages of maturity.

The book lays out a set of questions at each stage of maturity. At the Foundation stage, questions are about whether you can create a 360-view of the customer synthesizing structured and unstructured data signals along the customer journey. Experimentation questions focus on aligning on priorities for value creation and which vendors to work with to unlock that value. Expansion questions help address where to go deeper vs. expand to other Customer Relationship Moments. Transformation questions address where, when, and how to in-source capabilities. Monetization questions are about business model shifts and when to create new revenue streams leveraging your capabilities.

The AI Marketing Canvas was a highly relevant book for modern marketers even before the rapid advances in AI over the past few years ignited by ChatGPT. It is even more relevant now that companies are grappling with exponential increases in the capabilities of AI models that can be applied across use cases, from websites to mobile apps to product launches to marketing campaigns to other content-based experiences. Opportunities to leverage AI and machine learning go well beyond automation and cost reduction. They enable targeting and personalization of experiences across the customer journey at scale.

The second edition for the book dives deeper into how AI is changing the game across the value chain for marketing: 1. Competitive & market analysis; 2. Audience insights and segmentation; 3. Brand and messaging strategy; 4. Media and channel strategy; 5. Creative and content development; 6. Campaign execution and deployment; and 7. Measurement and optimization.

AI tools enable companies to rapidly scan a broad set of data sources like social media, customer feedback, ratings and reviews, and other unstructured data to provide early warning signals for business risks and identify innovation opportunities. It enables companies to move beyond static approaches to customer segmentation, enabling real-time simulation and experimentation across a broader set of micro-segments. AI enables more scalable approaches to matching tailored creative with the right micro-segments. AI agents can increasingly mimic the expertise provided by frontline employees, enabling 24/7 personalized experiences. When combined with mobile apps, messaging, and chat, these agentic experiences enable agile experimentation and boost customer lifetime value as brands optimize next best content along the customer journey.

I hope this review sparks your interest to read the full book. The second edition of the book will be out in September on Amazon. I’m looking forward to having Jim on my podcast, The CX & Culture Connection around then, too.

If you found this review interesting, I also recommend checking out my Substack with Randall Rothenberg, CEO Emeritus of the Interactive Advertising Bureau, on Winning Experience. You can also find my podcast with Randall here.

Please leave your own thoughts about the book in the comments. I’m looking forward to the conversation!