For Generative AI in Marketing, Strategy Equals Success

AI isn’t new to marketing. Anything but. For years, artificial intelligence has been baked into ad targeting and performance analytics, sentiment analysis and social listening, copy testing and content personalization, and email and search engine optimization. In many cases, machine learning has been churning away in the background, making the art of marketing more scientific and the work of marketers more efficient, effective, and — some would argue — more consumer-centric.

Then along comes ChatGPT, followed in rapid succession by the release of OpenAI’s more powerful GPT-4 model, and all of a sudden AI is brand new again. Marketers have been quick to heed the hype, shifting their attention and even their budgets away from recent darlings like NFTs, Web3, and the metaverse. Indeed, 2023 has been the Year of the GPT — with big brands like Coca-Cola embracing early (if, in my opinion at least, uninspired) experimentation; martech mainstays like HubSpot, Salesforce, and Adobe turning LLM-driven tools into a must-have feature; and just about everyone else going ga-ga over prompt engineering and the ways in which GPTs can crank out content at superhuman speeds.

Marketers do love a good call-t0-action. And if generative AI had a CTA, it would be: get up to speed or get left behind.

Indeed, I’d tell my clients the same thing. Experiment. Learn. Get your hands dirty. Try it (even if it’s too soon to trust it)

But if that’s all you do, you’re missing the point — and you’ll miss the boat. Or worse, you’ll board the wrong boat, pursuing generative AI as yet another shiny object on this month’s marketing innovation punch list.

In the worst case, this kind of narrow consideration misses the mark — leading you to invest energy into doing things that benefit neither your company nor your customers. The world is not waiting for you to 10x your output of low-quality, look-a-like content, no matter how easy ChatGPT makes it to do so.

Instead, experiment and explore with your strategy in mind.

Consider what marketing challenges a powerful generative toolset can help you address, and which objectives it can help you achieve. How can generative AI help you market better (not just cheaper or faster), differentiate you from your competitors, or connect your company with its customers in a deeper and more meaningful way? How can AI narrow or close any gaps that may exist in your consumer experience, or provide you with new ways of delivering value at critical points across the customer lifecycle?

Don’t make the mistake of turning generative AI into a solution in search of a problem. First, define the problem. And then figure out if generative AI is the right solution. Where it is, you’ll open the door to smarter, stronger, more strategic experiments that might actually deliver real value for you, your company, and your customers.

These are exciting days, indeed. But as is generally the case when it comes to marketing’s shiniest objects, I’d like to believe that level heads will prevail.

As you venture deeper into the realm of AI-driven marketing, I hope you’ll commit to prioritizing the needs and experiences of your customers. Generative AI, exemplified by GPT-4 or brought to life in whatever marketing technologies you have at hand, presents an opportunity to revolutionize the ways in which you connect with your audience and create meaningful, lasting relationships. It’s your responsibility to harness this transformative technology with intention and foresight, crafting innovative strategies that elevate your marketing efforts beyond mere quantity and into the realm of genuine, customer-centric impact.

Embrace the potential of generative AI, not as a fleeting fad, but as a powerful ally in your pursuit of delivering real value to your business, your brand, and the people you serve.

Picture of Greg Verdino

Greg Verdino

Greg Verdino is the Founder and CEO of CognitivePath, a marketing AI consultancy. His career spans 30+ years in marketing and technology innovation. Greg is the author of microMARKETING: Get Big Results by Thinking and Acting Small, and the co-host of No Brainer: An AI Podcast for Marketers. He has earned graduate certificates in AI from Cornell University and the London School of Economics.

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