Rory Holland, Fintech Marketing Pioneer and Founder and CEO of Fintech Marketing Agency CSTMR.
AI: we can’t escape it. It seems like every other day there’s a new tool, guru, or study I need to pay attention to. Can we all relax for a second? Yes, it’s fair to say that this era has been marked by a profound shift in the way we interact with the world. And while I recognize that AI is one of the factors at the heart of this change, there is still more to be done. This is especially true when it comes to my professional field: financial services and fintech marketing.
In a nutshell, here’s what I see: Marketers are worried about the possibility of being replaced by machines. Business executives don’t want to pay too much for marketers to use the machines. Regarding the first, I think I speak for my peers when I say that effective marketing depends on critical thinking, experience, and creative instinct. AI is not there yet.
Now, when it comes to the financial services brands I work with, they are willing to pay a premium for the marketing services and expertise that drive business growth. And yet, if AI can produce the same results as a grizzled marketing veteran, why should they invest in expensive human expertise? Because even if we let bots do what they do best (and I think we should), the marketing use cases are limited, the results are pretty vanilla, and the lack of creativity and intuition human is obvious. Translation: Generative AI, despite all the hyperbole and hype, is just another productivity tool. It is a complement, not a replacement.
Large Language Models (LLM) for Dummies
To better understand how generative AI can be best leveraged in digital marketing, it’s important to also understand the technology that powers tools like ChatGPT: major language models (also known as LLM).
Let’s imagine that you are in a huge library containing billions of books. You have a question and there is a librarian who has read every book. You ask your question and the librarian gives you an answer based on what he or she has read. It’s a bit like an LLM. LLMs are like super-intelligent computer programs. They have been trained on a large amount of data and are designed to understand and generate human-like responses based on patterns present in that data.
So while LLMs can provide information that appears knowledgeable, they cannot think or reason like humans. Responses may not always be accurate or reliable, particularly on topics or in areas that require specialized expertise or real-time information (such as digital marketing).
Now that that introduction is out of the way, let’s look at two practical use cases for generative AI in marketing.
Use case #1: Effectiveness of A/B testing
One area where generative AI has potential is in producing derivative ad creatives for A/B testing.
The initial phase of any paid media campaign involves a significant amount of human input. This requires out-of-the-box thinking in developing the core concept, copy, visuals, and overall design of the campaign. This is where the human element is crucial: marketers leverage their expertise, creativity, and understanding of a brand’s target audience to create an asset that resonates with that audience.
Once this original advertising creative is developed, generative AI becomes a powerful tool for efficiently producing derivative creatives. For example, if the original creative features a specific messaging theme, AI can create variations tailored to different audience segments while still maintaining the overall theme. This could include, for example, rephrasing sentences, incorporating synonyms, or changing the creative’s call to action.
The ability to quickly produce variations means that iterative testing can be carried out much more efficiently. In other words, it makes the process scalable.
Final (but important) thought: if you A/B test two mediocre creatives, one will still win. Make sure you do the work necessary to avoid celebrating the lesser of two evils.
Use Case #2: Blog Post Development
Over the past year, there has been a notable increase in the number of articles circulating in my network that seem too mechanical – some might even call “robotic”. Given that ChatGPT debuted in 2022, I find the timing more than suspicious.
In any industry (but especially financial services), consumer trust is everything. An over-reliance on AI for content creation will lead to a homogenized landscape of boring, often worthless ideas that erode the very essence of the brand identity that sets one company apart from another. An original idea: let’s avoid the content apocalypse.
Here’s how you (and your team) can leverage AI in a support role to support content development:
• Ideation and brainstorming: AI is an effective tool for topic ideation, especially in verticals that don’t naturally lend themselves to compelling storytelling.
• Development of main lines: With a little initial research, AI can help create detailed outlines, suggesting a logical flow for the article as it highlights key points to be covered.
• Quality assurance/revisions: While the nuanced task of copy editing is best handled by professionals, AI can provide some helpful initial suggestions for improving grammar, word choice, and fluency.
Note that I didn’t mention search engine optimization (SEO). For what? Although there are ways to AI can streamline your SEO workflows (e.g., semantically categorizing keywords), there are many marketing tools designed specifically for SEO. They do most things better. Use them.
Generative AI: a complement, not a replacement
I think AI is here to stay, but as marketers we need to tread carefully. Not because machines will take over, but because human creativity is something to be cherished, especially in marketing.
As we integrate AI into our workplaces, it is crucial that we maintain a balance in which the technology amplifies our potential without overshadowing the qualities that make us unique as marketers: our intuition, our empathy, and our ability to think creatively.
The goal of every marketer should be to find harmony. To find the right balance. Leverage AI as an extension of our hard-won capabilities and experience.
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