At the risk of stating the obvious artificial intelligence (AI) is a subject of great interest in marketing. Indeed, beyond marketing too at the moment. There is a lot of discussion of how companies can take advantage of the opportunities (and avoid the downsides). Raj Venkatesan and Jim Lecinski have a new book that sets out a framework for AI in marketing.
Outlining The Potential From AI
Venkatesan and Lecinski outline a tool to help marketers adapt to the new world. They call it the AI Marketing Canvas.
To get everyone in a position to understand the discussion they first outline the basic ideas underlying their work. For instance, they give a variety of definitions. These include terms like artificial intelligence (AI), machine learning, and deep learning. They then tell the reader how this all fits together.
The authors note how you can convert unstructured data into structured data. It is then much easier to use in traditional analysis. They describe this as dimensionality reduction.
Dimensionality reduction – the process of reducing a large number of random variables under consideration to a smaller set of principal variables.Venkatesan and Lecinski, 2021. page 88
When you have got everything into a more usable form you can use, for example, your numerical assessment of the sentiment within a text in a regression when you are predicting sales or something similar.
A Framework For AI In Marketing
Their canvas is actually a way of organizing how to transition to using AI in your business. The manager can ask themselves a bunch of questions and so assign themselves to one of five stages. Broadly speaking you want to advance through the stages to get to a situation where you are using AI more effectively in your firm.
The fifth stage involves changing from an inward focus on the use of AI to becoming a ‘network’. The authors warn this is hard. Indeed, it may not be appropriate for all firms. To be honest, if you get to stage 4 of their canvas you’ll be doing much better than most.
Possibly the most useful element of the book, for me at least, was the examples. The Louisiana State University drinks dispenser that can customize offerings to exactly your needs. The work of Unilever and Starbucks in integrating AI into their approaches to customers. [I must confess that Starbucks’ insight “that many drinkers don’t put sugar in their tea” (Venkatesan and Lecinski, 2021, page 192) seemed like something most English people I know could have told you. I guess it sounds more persuasive coming from an AI].
For teachers, they also have some great advice on websites to visit. These will perk up lessons.
The author’s framework for AI in marketing is a nice addition to the field. It is certainly a field that can well do with some demystification.
For more on Machine Learning in Marketing see here.
Read: Raj Venkatesan and Jim Lecinski (2021) The AI Marketing Canvas, A Five-Stage Road Map To Implementing Artificial Intelligence In Marketing, Stanford Business Books