A Q&A with authors Raj Venkatesan and Jim Lecinski
What Inspired you to write The AI Marketing Canvas?
AI and machine learning are shuffling the deck on every level and in every category, just like digital and big data did a few decades back. This seismic shift will require Marketers to develop new thinking, new skill sets, new strategies and systems that will require the organizational culture to evolve as well.
Accordingly Marketers today are inundated with advice and information about AI and machine learning capabilities from trade books, podcasts, trade journals, opinion pieces posted on social media platforms, and more. The problem is, most of this material on AI and Machine Learning being offered to marketing leaders either focuses on the technology itself from a computer science perspective or on the high concept implications of AI on society. Further, much of the materials generated are vendor-driven and don’t provide what marketers need to move forward.
Therefore we were inspired to write, “The AI Marketing Canvas” to provide marketers with answers to these two key questions: (1) How should modern marketers be thinking about artificial intelligence and machine learning? and (2) How should marketers be developing a strategy and plan to implement AI into their marketing toolkit?
What the biggest change you’ve seen in marketing strategy as it pertains to AI while writing the book?
The combination of Big Data plus Machine Learning has tremendous potential to revolutionize all aspects of marketing. Those two forces have already had a tremendous impact on other areas of the firm like credit scoring and fraud detection, supply chain and logistics demand forecasting, and even recruiting and hiring.
Yet what we saw in talking to and researching many businesses for this book is that Marketing in general has been slower to adopt Big Data + Machine learning in a broad way. We found Marketers that do adopt this modern approach stand to reap tremendous benefits and create competitive advantage. That’s because of the closed loop feedback system that AI powered marketing can create. Specifically Marketers can use large amounts of data to make highly accurate predictions on everything from Product Development to Targeting to Message Development to Media Planning. Then the results of those predictions are fed back into the system to make even more accurate predictions the next time. It’s a very powerful and new approach to marketing.
Initially we thought the barrier to adopting AI in marketing might have been lack of technical knowledge or budget or perhaps the ability to measure its impact. In fact, lack of a plan, not having a clear roadmap, a best practice route to get started is a big hurdle. That’s why we wanted to lay out these 5 stages for implementing AI in your Marketing toolkit in this book.
AI is new for a lot of marketers. How is the book geared towards these readers who are incorporating AI into their existing company’s marketing plans for the first time?
We recognize that Marketers are a very broad group, some are quite technical--they already know and are using machine-learning in their marketing; whereas others are don’t come from a technical or data background and are just getting started on their understanding of AI and how it can be used in marketing. We wanted this book to offer value to both of those groups. For the marketer just getting started, we developed and included a section on the core concepts of machine learning to provide the necessary foundation required to then apply AI to marketing. For the more advanced reader this section is a good refresher, and also something that can be shared with others. For both groups, then armed with this understanding of what AI is, what it does and how it can be used...we then offer a five stage roadmap of how to get from “zero to hero” implementing AI into your marketing toolkit.
You provide a number of real-world examples, including Coca-Cola, Lyft, and Google among others. What companies are you seeing that are effectively using AI, or made it integral to their marketing?
offers a direct, actionable plan CMOs can use to map out initiatives that are properly sequenced and designed for success—regardless of where their marketing organization is in the process.
It is encouraging to see that many companies are using data driven marketing. The Covid pandemic accelerated the digital transformation of many firms and customers also embraced digital. An example from COVID times that we find interesting is Bloomingdales. They used data on customer purchases in Florida (which opened up earlier than other states) to predict bridal dress preferences of customers in other states. This really resonates with the central thesis of our book; use data to obtain customer insights and use these insights to personalize customer engagement.
Follow up, any for smaller/medium sized organizations?
We get asked the question of smaller/medium sized enterprises a lot. One the one hand smaller enterprises have fewer customers and hence also have challenges in training the AI algorithms. But the smaller enterprises can be agile, and have lesser legacy costs. They are able to manage and collect first party data better than their bigger competitors. This can provide them an advantage. For example, Warby Parker, the DTC eyewear firm, has a sophisticated technology platform that allows them to collect first party data online and in their physical stores. This provides them great insights about customers’ omnichannel preferences and allows the brand to engage with their customers through emails etc in a more personalized manner.
What do you hope marketers people take away from The AI Marketing Canvas?
To win, marketers must apply AI and machine learning technology to increasingly personalize each of these moments in their customer experience. AI for Marketing is more than a fad or mere hype--you need a plan! This book offers, in The AI Canvas for Marketers, a simple framework CMOs can use to map out initiatives that are properly sequenced and designed for success —regardless of where their marketing organization is in the process. It’s also a call to action for marketing leaders to confront and decide how they will address this critical pivot point in marketing. Follow the 5 step AI Marketing Canvas™:
- Organize your data so you are ready to AI in Marketing
- Tap external vendors, let a thousand flowers blossom
- Name a champion, expand efforts and begin to in-source.
- Prepare to make your big bet. Build vs Buy
- Turn your successful internal efforts into external platforms
Then track your progress up these 5 levels, applied across your customer journey. Now is your “AI Moment of Truth” so get started! It’s not too late to still be early.
this blog really helped evolve my knowledge.
Posted by: wiliam jones | August 21, 2021 at 01:08 AM