The empowering role of AI in marketing

As a marketer, you’re likely used to change. Being agile enough to pivot your channel plan or try a new A/B test comes with the territory, as does embracing the increasing array of mar-tech and optimizations tools available.

But once in a while, innovation strikes in a way that resets our entire operating system. I am, of course, talking about AI. Seemingly overnight, ChatGPT catalyzed a change that swept across the entire marketer’s playing field, resetting the rules of engagement almost overnight.

In parallel, customers now expect hyper-personalized content delivered to their channel of preference. Distribution channels that worked a year ago have saturated and slowed. And marketing best practices as we know them are becoming obsolete faster than before. It’s enough to knock even the savviest marketer off their stride. Don’t even get me going about the depreciating value of cookies, the new complexities of customer journey mapping, and identity layers in attribution modeling.

So, what can we do as marketing professionals to stay ahead of the change and adapt accordingly? One thing is clear: marketers need to find ways to do more, with less.

The World Bank says a looming recession has impacted almost all sectors. A third of companies have reported significant cuts to ad spend. And restructuring teams for leaner operations is still the most viable option for businesses reeling from the post-pandemic market softening across SaaS and eCommerce.

In a world where marketers have smaller budgets and bigger targets, I believe AI has the potential to be a growth partner and catalyst, helping us navigate through the uncertainty.

At Unbounce, we’ve spent years analyzing data around campaign trends, conversions, and AI-assisted campaigns, in order to provide tools and resources that help marketers grow smarter. One such tool is Smart Traffic, which leverages over a decade of data sourced from over two billion conversions. Through its AI capabilities, Smart Traffic helps marketers optimize their landing pages in order to get up to 30% more leads, sales and signups from their campaigns.

But not all AI tools are created equal. To help you wade through the AI hype and identify the highest leverage tools and opportunities for your team, here are some steps every marketer should take to expand their AI prowess.

The AI literacy gap

Whether we like it or not, AI is getting really good at pretending to be human.

Entire brand campaigns are being planned, created, and launched using AI tools. And they’re not throwaway attempts either – they’re getting really good. Take this GoFundMe campaign for example. Using a combination of AI-generated art and traditional animation techniques, the team created a stunning video campaign to tell the story of how communities benefit from donations through GoFundMe. What typically would take months to pull off, the team was able to do in a matter of weeks.

At Unbounce we decided to put AI’s capabilities to the test in a similar way. We wanted to see just how well it could create a campaign from scratch, for an amusing idea: selling trampolines to elephants. With our team at the helm, we employed a handful of AI tools to do all the heavy lifting: ChatGPT for campaign strategy, Midjourney for creative, and our Smart Copy builder for optimized landing pages. The result? The entire campaign was ready to go in 24 hours, selling trampolines to elephants with stunning speed and sensibility.

For marketers who have yet to dip their toes into AI, I can’t stress this enough: the trajectory of your career, and market performance is already irrevocably impacted by AI.

If you decide to stay on the sidelines and wait it out, you can bet there’ll always be a seat at the table for people who deliver results. But competition is increasing. As a marketing professional, someone out there with the same skills and background as you is doing laps around your output, depth of market insight, and performance optimization because of AI. Over time, this gap between the AI literate, and illiterate will only become more pronounced.

Setting the stage: the data maturity curve

If you’re like most, you’re probably wondering where to start with AI. In my view, it’s not where most people think.

Organizations consistently underestimate the role that data infrastructure plays in AI adoption. Many teams will attempt to get started with AI, only to find that their ability to use it is stunted because of poor data. So what should teams do to prepare?

Start to assess where you are on the data maturity curve. Meaning, how well does your data infrastructure help you make decisions in three, six, and 24 months from now? Typical mar-tech stacks have data inputs from every corner of the business, but often they don’t talk to each other. Your goal should be to get your data streams as closely aligned to a universal source of truth as possible.

Part of the work here is infrastructure-related, setting up systems for clear data routing and classification. But another part is team-related. Ideally, you need an equal partnership between data and marketing to move towards a data-governance approach that will set the stage for success with AI.

Your data infrastructure will likely need to evolve over time to get the most out of AI. Benefits like A/B testing and personalized content are all made possible from feeding your AI tools with meaningful, contextualized data, over a period of time.

The AI adoption curve

Regardless of where teams are on their data maturity curve, every marketer can take ownership of their own journey with AI. With new tools launching weekly, it can be tough to know which will be a good use of time.

One framework that can help you self-assess your AI literacy is to think in terms of an AI adoption curve. Rather than a series of steps, the adoption curve lets you know how your current learning trajectory sits in relation to the ever-changing AI innovation cycle. I like to think about the AI adoption curve in three phases: foundational tools, expansive tools, and advanced growth tools. Each of these build on each other, but none are mutually exclusive.

Foundational tools are ones that make you faster and more productive in your everyday tasks. For example, running documents through grammarly, doing industry research with ChatGPT, or using an AI-writing assistant to spin up a job post outline. They typically require the lowest investment in time and effort to get started with.

Expansive tools are ones that give your team new capabilities and capacity to execute with. Tools like DALL·E and Midjourney are great examples. They may take some focused time to learn, but offer creative ideation and design capacity for a lean team. They add leverage to your efforts, generally expanding what you’re able to aim for, and deliver on.

Advanced growth tools is the third bucket. I see this as a catch-all for the nascent AI tech that helps your team go beyond current market performance through experimental growth programs. Like hyper-personalized campaigns targeting off the back of rich data sets, for example. At Unbounce, we’ve found that organizations operating at this stage are seeing the biggest fruits from AI. For example, teams leveraging our Smart Traffic A/B testing tool typically see a 30% increase in average campaign conversions. This is possible because AI is marrying benchmark data from over 2 billion conversions, with unique organizational data, to drive outsized performance.

No matter what stage you’re in, I’d encourage every marketer to spend at least an hour a day learning and testing new tools. In practice, an hour a day is a good way to keep a pulse on

innovation relevant to your business, and stay ahead of the shifts.

A good place to start is to put into action five tips offered up by the AI Marketing Institute, on how to develop an AI growth roadmap. Form an AI council to hold space for conversations in your organization. Do an impact assessment, to see where you are on the adoption curve. Prioritize AI in your team education and training, and formally work to upscale your team. Make sure you’re developing responsible AI principles and generative AI policies to meet the growing demand of AI tools day to day. And lastly, build an AI roadmap to set intentions on how you will use AI to drive growth in your product, team, and sector.

As AI becomes more of a present companion in our day-to-day, now has never been a better time for marketers to lean into these growth tools. Both for powering creative campaigns, and the next stage of your career.