Is AI ready to take over your marketing outreach to potential customers? Facebook’s owner, Meta, recently launched its BlenderBot 3 AI chat tool, yet so far the suggestion is that AI is still some way from completely taking the reins from your marketing team. Journalists quickly found the tool expressing some dubious views—not least about its parent company—telling the Wall Street Journal that Facebook has “a lot of fake news on it these days,” while asserting that Mark Zuckerberg’s business practices are “not always ethical”.
And yet the march of AI in marketing continues apace. Salesforce’s latest State of Marketing report found that 64% of marketers use AI. The demand for AI in marketing has been estimated at $12bn worldwide, and could rise to $108bn by 2028 [source: Statista]. A McKinsey analysis has identified marketing as one of the business areas that could benefit the most from AI. They estimate it could generate up to $2.6tn added value to marketing and sales. The challenge for CMOs is how they can use AI to secure their organization a slice of that value.
Some firms already use AI extensively. Common applications include automating processes, including targeting emails or online advertising, and creating ad content. For example, JPMorgan Chase has used the AI tool Persado to improve the wording used in its direct response emails and online display ads, honing in on word choices that deliver better customer responses.
Many organizations also use AI to sift customer data, seeking improved insights, a more detailed understanding of customer lifetime value (the revenue associated with a customer over the course of their entire relationship with the company), and more nuanced segmentation. As firms build a better picture of their customers, they can offer personalized recommendations and new products, much like Starbucks does with data gathered through its rewards program and mobile app. Also interesting is the use of AI and machine learning to support sales teams, for example in B2B companies, to identify next best actions: when to contact your best customers, the mode of contact, and what type of messages might be most effective.
These applications are delivering real value for businesses. However, for most companies, the current use of AI in marketing is generally ad hoc and piecemeal. I have yet to see AI and machine learning deployed in marketing in a truly well-thought-out and strategic fashion. These are game-changing technologies, but they are presently being used to improve execution on familiar marketing strategies. Using them to their full potential would mean ripping up and replacing old strategies—and that potential remains under-explored.
Where to play and how to win
In practice, the bigger opportunity for CMOs lies at the point where marketing and sales meet strategy. If strategy is about where to play and how to win, the real value for marketers lies in determining where a business should compete—and, equally importantly, where it should not.
CMOs should consider how they can use AI and machine learning to discover new markets or new product segments, or to pinpoint markets they would be better served by avoiding. For example, AI could lead a company to right-size its product or service portfolio, driving simplification if machine learning revealed that a streamlined offering was optimal. Another example might be to completely change the types of customers the organization targets. This is beginning to happen, but marketers are so far only scratching the surface.