The race is on to keep pace with the changes in marketing technologies.
With her launch of the 2023 Emerging Tech Trend Report at SXSW, Amy Webb shared from the stage, “Artificial intelligence should be part of every strategic plan, as it crosses multiple dimensions, from workforce automation, to digital transformation, to everyday business processes and business intelligence. It is imperative that executives and senior managers understand what AI is, what it is not, and what strategic value it adds to the business.”
At a recent Kellogg School of Management Marketing Leadership Summit in Chicago, Jim Lecinski, associate professor of Marketing at Northwestern University, told marketers there’s an “untapped opportunity to use AI and machine learning to gain competitive advantage.” A Whole Foods Market in New York’s Glover Park neighborhood launched a store using “Just Walk Out” technology that scans a shopper’s palms, tracking their every move and product selection via camera and sensors, according to The New York Times. The technology then sends the charges to a customer’s Amazon account when they leave the store. Imagine how marketers could detect shopping motivations and impulses to a greater extent.
In the past ten years, we have seen a steady introduction of marketing technology-enabled tools that have complexified tech stacks and left leaders wondering where to invest their time, talent and money. There are, among others: Metaverse, the rise of big data, data privacy and personalized content. Add to the mix influencers, social, mobile, e-commerce, performance media, paid search, personalized content and now the growing drumbeat of artificial intelligence and machine learning.
In this fast-moving environment, advice on evaluating technology is surprisingly sparse. It’s often fraught with complex ownership structures that string across IT, marketing, data transformation, business transformation and insights.
What Is AI?
Despite the frenzy of media coverage about AI in the past six months, the roots of artificial intelligence extend to the 1950s. Mathematician and Stanford professor John McCarthy, known as the Father of AI, coined the term artificial intelligence in 1955. McCarthy considered AI to be “systems that perform actions that if performed by humans would be considered intelligent.”
So, while AI isn’t new, marketing professionals express a mix of excitement and angst about the opportunities to lead with AI and machine learning, or ML.
“The pressure on marketing and insights leaders to be doing something with AI is enormous,” Sandra Moore, vice president at Hanes Brands Inc. and who attended the Kellogg Leadership Summit, said in an interview.
In conversations with marketing executives across industries, their points of view vary as to whether AI for marketing is a tool, capability or something more. Regardless of how senior-level marketers think about AI/ML, marketing’s job is to be the best iteration of predictive intelligence in the market. The best marketers are those who divine where the market is moving and announce what will motivate consumers.
Advice from leaders on where to start
When asked whether AI requires an all-in-now approach, Joel Yashinsky, CMO of Applebee’s, said, “Predictive intelligence has always been the job of marketing.”
“The pace of change has continued to run faster and faster,” Yashinsky added. “How to understand where to place the organization’s time, energy and resources makes essential a proven process through which to test and learn cross-functionally. This leads to fast fails, higher reward ideas moving more quickly and growth of the business.”
How do we get ahead?
According to Lecinski, the best practice for marketing leaders is to simply begin applying AI where they are. For example, CMOs might ask, “What experiments can we run with AI in relation to our existing capabilities and partners to begin looking for optimization opportunities?”
Using a tool is not the same as building a capability. Thinking about AI as a capability-building opportunity is where the long game lives. How does AI/ML capability begin to grow predictive intelligence against the business objectives of today? How would your organization begin the journey of growing and eventually selling its own data product? How might a brand-led consumer products organization become a consumer-data product company in 10 years?
“Leaders need to know what AI is already driving and what it can transform,” shared Melissa Anderson, co-founder and president of Public Good Software, an AI-powered marketing platform provider. “AI is endemic in so much of what we are experiencing already today: self-driving cars, our phones, the feed that we read each day. AI isn’t the Metaverse, it’s already here and installed in our lives.”
What would set an organization up for early success?“
In a world where most companies build their bottom-lines on data, [failing to integrate] artificial intelligence and machine learning into a brand's footprint will chisel away its competitive edge and market share over time,” said Asher Jay, CEO and founder at Henoscene.
Experts shared three first steps into AI/ML
- No shiny objects: Aligning the business strategy today with the deployment goals for AI/ML is key to growing an early understanding of impact.
- Installing an organizational AI champion to design and protect experiments is critical to moving experiments and investments forward and building a capability.
- Investing in education to develop a vision for what “better business” or “better experiences” would be generated if better prediction were possible.
As Lecinski repeatedly shared, “It’s not too late to be early!” And despite the hype that the machines have already taken over, it appears human marketers still have a lot of opportunities to capitalize on AI/ML as a way to win the consumer. The job of marketing doesn’t change, but the playbook has.
