Zohar Bronfman is the CEO and cofounder of Pecan.ai, a predictive analytics platform built to solve business problems.
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Today’s marketing leaders know efficiency is critical. Every dollar needs to stretch as far as possible, especially when you never know how many of them might be in the next quarter’s budget.
Generative AI is getting plenty of air time as the solution to this problem. By creating hyper-personalized content at scale, automating creative production and offering support to marketers throughout their workflows, GenAI seems like a fast way to trim the budget around many marketing functions.
And marketing leaders are jumping on board. While just 14% in a recent Gartner survey said they’ve already invested in GenAI tools, another 63% said they plan to do so in the next 24 months.
That’s a remarkable leap, considering that just 35% of business leaders told Gartner that their organizations are often or almost always using a better-established, proven form of AI in business: machine learning.
To be sure, machine learning hasn’t been around that long. But ML and other forms of AI have been used in business for over two decades. Today’s technology is vastly improved and far more effective than in the early days.
And yet something about GenAI—the media buzz, its unusual “creative” ability—is leading businesspeople toward a rapid adoption. At the same time, many organizations still haven’t empowered their teams with even fundamental machine learning capabilities.
Marketers, Take A Step Back—Into The Future
In the rush to adopt GenAI and “keep up” with the latest tools, marketers are missing out on a far more impactful opportunity: using the business data they already have to gain meaningful knowledge of what their customers will do in the future.
Customer acquisition is challenging and expensive. Customer retention is even more difficult in a world of endless options and buying opportunities. And ad platforms constantly change their policies and the data they provide.
The constantly shifting and challenging environment can make marketers feel hopeless about their efforts to manually optimize budgets and campaigns. As soon as they think they have a handle on the latest customer trends and tech developments, a key advertising platform implodes or a hot new social media fad steals all the attention.
It’s too fast-moving for a marketing team to keep up despite all their best efforts. The glut of content created by GenAI tools isn’t going to help.
In an already content-saturated world, marketers will have a tougher time than ever when they seek the customers they want most across their various marketing channels.
Why GenAI Alone Won’t Optimize Marketing
GenAI’s capabilities are impressive and shouldn’t be ignored. But to solve the ongoing, everyday challenges that marketers face in finding the right customers (with the right message, at the right time), those tools are not a complete answer.
Instead, the real long-term return on investment will come from investing in AI that can help you bring in and retain customers efficiently and effectively. If you can anticipate which customers will be high-value over time, you can invest your resources optimally to keep them, giving them the VIP treatment they deserve.
That might mean creating variations of content that speak to them directly, sure. But you won’t know which customers you want to reach with that personalized AI-generated content unless you’re already using your marketing, customer and transaction data to its maximum potential to identify them accurately.
Building Connections In A Noisy World
The AI tool that can make that happen? Predictive analytics, with its ability to foresee future customer activity.
Machine learning models can make these kinds of predictions for each of your customers, helping you identify exactly which customers need what kind of attention and when. They can also reveal the likely impact of all your marketing channels and campaigns so you can allocate resources in the best way possible. Understanding customers' future activity can provide a roadmap for tailored campaigns that resonate deeply.
These applications are why predictive analytics still must be a high priority for marketing leaders. While GenAI may improve marketing efficiency in some areas, the more significant potential right now lies in quickly implementing predictive analytics that can directly address substantial marketing costs.
The right kind of AI can help marketers amplify meaningful engagement with their audiences and customers to drive real ROI—rather than just contributing to the noise.
Gen AI may generate content, but predictive analytics reveals the future. And efficiency isn’t just about reaching more customers but reaching the right customers. By embracing this technology, marketing leaders can foster long-term ROI, ensuring they make more informed decisions and craft data-driven strategies in a content-rich world.
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