The (Future) Impact of Generative AI on Marketing
What matters: Artificial intelligence has real-world applications that will inarguably make the day-to-day tasks of marketing practitioners easier, more efficient and more seamless, and could soon go from experimentation and novel use cases to common, popular tactics and even best practices among marketers.
This image was generated with the assistance of AI.
Generative AI is already being leveraged to suggest and create email content, create social ads and improve product descriptions.
Seemingly (and almost predictably), artificial intelligence and talk of AI are suddenly everywhere. In a matter of months since the release of OpenAI’s ChatGPT prototype to the public on November 30, 2022, its novelty swiftly turned to mass adoption, boasting over a million users by December 4. This wasn’t OpenAI’s first foray into publicly available AI, whose DALL-E product, capable of creating hi-res digital imagery from natural language descriptions, debuted over two years ago. But thanks to ChatGPT’s simple interface and familiar chatbot format, it soon reached over 100 million users by January 2023.
By March 2023, OpenAI had released ChatGPT Professional, a subscription version of the technology, providing developers with an API (application programming interface), and which subsequently led to a deluge of integrations and use cases that have left a smattering and dizzying number of applications for organizations—from Snapchat to Instacart—and functions—from customer service to sales.
And not surprisingly, the marketing and advertising industry as a whole hasn’t been immune to the popularity of exploring how to put generative AI to use. But aside from the now all-too-familiar creative and hypothetical brand collaborations and mashups, put-to-the-test ad copywriting, and most recently, attempted gags like submitting fake portfolios to recruiters in exchange for buzz, generative AI in marketing still hasn’t hit full stride—yet.
But it’s already being leveraged to suggest and create email content, create social ads and improve product descriptions. Beyond these examples, however, it has real-world applications that will inarguably make the day-to-day tasks of marketing practitioners easier, more efficient and more seamless. Here are three potential (and big) ways generative AI will impact marketing as we know it.
ENHANCED CAMPAIGNS AND USER EXPERIENCES
Most of us have seen the imagery that generative AI is capable of creating, ranging anywhere from silly but spot-on to contemplative and compelling. Programs like Midjourney, DALL-E 2 and Stable Diffusion are capable of turning a text prompt into an endless array of images in a matter of seconds. This could ultimately lead to a plethora of creative exploration, content generation and campaign ideation that can not only speed up the creative process but also initiate unique ways to engage with new and existing audiences.
In fact, this is has already become a reality. Just this week Adobe announced at its annual Summit the debut of Firefly, a new family of AI models integrated into its suite of products including Creative Cloud, Experience Cloud and Document Cloud to produce imagery, typography, ilustrations and other assets.
And more than one-off gimmicks or spoofs, generative AI in this capacity could, in turn, be leveraged to generate new and compelling campaigns that can then be implemented to enhance user experiences through the creation of dynamic and interactive content and product combinations based on preferences, user input or behavioral data, to improve upsell and cross-sell opportunities or increase levels of engagement.
What’s more, AI’s ability to debug and enhance software applications, programming and coding language can increase speed-to-market for things like apps, integrations, product launches and partnerships.
CONTENT PERSONALIZATION AT SCALE
Coupled with its ability to enhance user experiences, generative AI will revolutionize the ways brands, marketers and organizations personalize their content and campaigns at scale and with ease. Generative AI algorithms are capable of doing what individual data scientists, analysts or predictive models can currently do on steroids, moving from taking customer data—along with transactional and behavioral data—at the segment or sub-segment level, to creating truly individually customized brand experiences to supercharge database marketing. Imagine hyper-tailored offers, ads, products and experiences that are specifically designed to resonate with consumers at the specific individual level based on user history.
The upside to deploying highly personalized customer experiences isn’t just higher engagement rates and user stickiness. It could translate to more effective content, improved campaign performance, and ultimately, higher conversion rates and increased cross-channel, in-store or online sales.
ROBUST CAMPAIGN OPTIMIZATION IN REAL TIME
A knock-on effect to leveraging generative AI to create and deploy sophisticated, highly targeted personalized experiences at scale is its inherent ability to ingest customer, transactional and behavioral data to analyze and create predictive models that optimize campaign performance effortlessly.
And in turn, the machine learning models and algorithms that power generative AI (more on that here) means that things like campaign optimization, performance and predictive models can be constantly improved and iterated upon for further enhancement.
This will translate to less wasteful spending and higher return on investment for brands across their marketing mix, and will speed up the testing of new channels, audiences and when to dial up—or down—what is or isn’t moving the needle.
It goes without saying that marketing is nowhere near experiencing “peak” AI. If anything, its impact hasn’t even reached its infancy, meaning that how and to what extent the tools and technology that have suddenly become available will shape the customer experience is yet to be determined. What is clear, however, is that widespread and rapid adoption of artificial intelligence for everyday use could sooner rather than later go from experimentation and novel use cases to common, popular tactics and even best practice among marketers—including, for example, brand advertising, experience design, CRM and enterprise marketing technology.
The biggest test won’t be whether or not it’s put to use across the customer journey in new and unforeseeable ways; the real test will be if it’s put to use in ways that are responsible and ethical, and ultimately, in ways that put the customer first.
Daniel Welch is Chief Digital Officer at Salient Global.