In the Age of AI, CMOs Still Need to Take Risks

Posted on by Maya Mikhailov
cheetos jewelry
No amount of data could have ever predicted there would be a market for Cheetos-themed luxury jewelry.

Artificial intelligence is a disruptive and game-changing tool, and can help brands target customers like never before. But, an over dependence on AI will lead to CMOs falling into predictable patterns that can undermine long-term goals. 

Gathering data is old hat to many digitally native CMOs, but with the rise of AI, CMOs will have to change how they think about data in new, critical ways.

Simply having data is no longer enough to make it actionable or usable to AI-based tools. Suddenly CMOs have to care about data sources, quality and freshness. AI is not a panacea for any set of data, as it requires a minimum level of attributes to be useful and accurate. Historical data may even lead to inaccurate conclusions.

Thinking About Data In New Ways

Never before has it been more important for CMOs to not only partner internally with teams leading analytics, but to also have their own team of data scientists reviewing the inputs and outputs of these new AI-driven systems. The operational plan of any successful program will require not only creativity, but a strong framework of how to ingest and assess the resulting data.

While data quality may be a foundational element of AI, unlearning previous tried-and-true marketing techniques will be a bigger challenge for the modern CMO. Consider the practice of developing personas, an age-old way of audience identification and targeting. CMOs identify their brand’s core target personas, and create elaborate presentations about their fictionalized attributes and behaviors. Marketing plans are executed based on “What would ‘Betty’ want?” or “How would ‘Susan’ feel about this campaign?” In contrast, the CMO of the future will let the AI tell them how to market to individual consumers through behavioral analysis of terabytes of data gleaning insights into the individual, rather than pre-existing groups.

The AI driven CMO will also forget about A/B testing as any campaign can be A – Z tested simultaneously. Microtargeting at lightning fast speeds with machines making decisions on creative and language will let optimal results emerge for audience segments. This isn’t the reactive marketing that we now know. This is revolutionary marketing, where CMOs will provide the guardrails of execution to machines jumping from channel to channel constantly optimizing and refining.

Yet, as much as AI should and will revolutionize marketing, CMOs cannot abdicate their responsibility as storytellers and provocateurs.

AI and Learning From the Data

Marketing leaders are expected to deliver on innovation. In the past, innovation in the marketing world meant taking a risk that paid off. CMOs worked on experience and gut instinct to create greatness. The rise of digital marketing changed all the rules—intuition had to be backed by data points and constant measuring of ROI. While some still worry whether purely data-driven approaches reduce the wonder or emotion of marketing, AI will put data-driven marketing techniques on steroids. There will be no aspect of digital or analog marketing that AI cannot parse and analyze for optimization.


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Herein lies the rub. Machine learning needs data sets to learn, and all that data in marketing will be historical in nature. Much like weather, the short-term predictions will often be accurate, but the marketing equivalent of a random late spring snow storm can always pop up to cause chaos.

In the world of providing proof points and ROI, it will become increasingly easy to rely on AI to make decisions on the next best action in a campaign. AI can run though scenarios based on past results and generate an answer on the highest probability path of success. This means the role of CMO as oracle of a brand will likely change.

Walk the Path Less Taken

But what about the non-predictable paths to success? What about those home runs which can cement a brand in the minds of consumers for years to come? How will CMOs convince their CEOs, CFOs and boards to take a swing at a low probability idea that might yield massive results, rather than going the safer path?

Take for example Cheetos. A few years back, Cheetos announced a gift collection ecommerce site timed with traditional retail holiday promotions. The site sold pretty much everything but the popular snack, from cologne and branded leggings to bronzer and a $20,000 jewelry set. No AI parsing through Cheetos marketing data sets would ever tell their CMO to sell pricey baubles. But with over 100M impressions, countess press pieces, social medial trending topics and a complete store sell out (yes, even the $20k jewelry set), Cheetos became the hot holiday season story. It’s these brave, and sometimes silly, choices that can resonate deeply with consumers in an age where marketing is becoming increasingly formulaic.

AI will change the rules of the game for CMOs. However, with all the benefits of AI, over dependence risks making marketing generic. Marketing bots will emerge that will only follow predictable patterns and appear to consumers as noise. It is the new role of the CMO to have the courage to make that “gut call” that may fail, but could also be the pivotal moment that sets their brand apart.

Maya Mikhailov is SVP of Synchrony.

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