“Artificial intelligence is not a substitute for human intelligence; it is a tool to amplify human creativity and ingenuity.” — Fei-Fei Li, Co-Director Stanford Center for Artificial Human Intelligence

In the past year, there's been a lot of buzz about the potential of artificial intelligence (AI) to revolutionize industries. Tools like Chat GPT have been at the forefront of this conversation, sparking excitement and anticipation about the possibilities that AI brings.

But is the hype justified? If anything, it might be an understatement, especially when it comes to the world of marketing.

AI is a paradigm-shifting technology that will reshape the marketing landscape as we know it. With AI, marketers can accomplish more work of higher quality than ever before. And the best part? AI doesn't require massive teams or huge budgets, empowering even smaller organizations to compete with the output of large corporate marketing departments.

More Work, Higher Quality

AI has an uncanny ability to enhance both the quantity and quality of work produced by marketing teams. Firstly, AI speeds up content creation exponentially. It can generate original content like blog posts, emails, and social media updates in a fraction of the time it would take a human writer. This efficiency allows senior staff to focus on strategic tasks while AI handles content generation.

Secondly, AI can create multiple design variations within seconds. Marketers can use these designs for A/B testing, optimizing landing pages, and creating visually appealing social media posts. This eliminates the need for a professional designer and speeds up the design process.

Thirdly, AI can generate unique and creative marketing ideas based on input parameters. This capability enables marketers to brainstorm campaign concepts more efficiently and effectively. Furthermore, AI can quickly test multiple advertising ideas, leading to improved campaign performance through rapid iteration and optimization.

But it's not just about quantity and speed. The ability to quickly generate high-quality copy and images enables skilled marketers to enhance the quality of their work. It lowers the barrier to exploring and refining ideas—provided you guide AI with strong ideas and interact with its output effectively.

Not All It Seems

However, while the potential is undeniable, many organizations have found it challenging to unlock the full benefits of AI. Despite high hopes, the practical results often fall far short of expectations.

Three problems in particular loom large as organizations rush to adopt AI in their marketing efforts.

1. The Problem of Similarity

Language Learning Models (LLMs), such as GPT-3, generate ideas and copy based on the content they've learned from. This capability lowers the barrier to creating copy that sounds good, but it also leads to output that's remarkably similar to existing content.

The result? A flood of content that contributes to market noise and makes it more difficult for an organization to stand out from the crowd. While AI can help generate content quickly, the way most marketers today have been taught to deploy it, they struggle to create differentiating content and to capture a brand's unique voice and values.

2. The Temptation to Do Too Much

AI's efficiency has tempted many organizations into biting off more than they can chew. For example, testing three dozen half-baked ads will almost always underperform compared to testing four well-conceived hypotheses. Because AI lowers the cost to creating each ad variation, many organizations have been tempted into counterproductively testing for testing's sake.

Another example: Some organizations have even used AI to build hundreds or thousands of content pages hoping to win the SEO battle, neglecting the fact that none of those pages contribute meaningfully to helping them create a customer. While their vanity metrics—clicks, search rank, search win rate—benefit, there's little if any impact on the bottom line.

If you're not careful, the sheer volume of output you can generate with AI will give you the illusion of productivity, but without strategic direction, this approach will usually fall flat.

3. The Quality Conundrum

Historically, we've judged the quality of work by how professional it looks and sounds. AI definitely lowers the barrier to creating content that looks and sounds extremely professional. And if the improvements from GPT-2 to GPT-3 to GPT 3.2 to GPT 4 are any indication, this is only going to dramatically improve in the coming months.

This benefit, however, can create its own set of problems. AI often produces work that exceeds the ability of junior employees to evaluate it. Yes, a junior copywriter making $40-50k per year, armed with a good AI, can now produce content and ads that are more professional than that created by a majority of senior copywriters making twice that. But without a clear marketing strategy to guide the evaluation of this output, it often fails to advance the strategic and persuasive objectives of the organization.

While AI can create polished content, it's essential to remember that marketing isn't just about sounding professional. It's about communicating effectively with your audience, understanding their needs, and persuading them that your product or service is the best solution for them. AI, as advanced as it may be, still lacks the human touch necessary to truly connect with audiences on a deeper level.

Finding the Balance

So, how can organizations navigate these challenges? The key lies in balancing the use of AI with strategic human input. AI should be seen as a tool to enhance marketing efforts, not as a replacement for human creativity and strategic thinking.

When using AI to generate content, organizations should make an effort to infuse the output with their unique brand voice and identity. This might involve tweaking the AI-generated copy or providing more specific inputs to guide the AI.

Organizations should also resist the temptation to do too much just because AI makes it possible. Instead, focus on well-conceived strategies and hypotheses, and use AI to execute these effectively.

Lastly, while AI can produce professional-sounding content, organizations need to ensure this content aligns with their marketing strategy. This might involve senior staff or experienced marketers reviewing and refining AI-generated content to ensure it meets strategic objectives.

The Need for a Message-First Strategy

You will get a lot more efficiency and effectiveness out of the AI tools you adopt if you ensure you have a strong message-first marketing strategy.

What is a message-first marketing strategy? It's one that begins with the core ideas you need to communicate to attract the attention of your ideal customer, move them through their journey toward becoming a customer, persuade them to buy, and build an enduring relationship with them that strengthens your brand. It incldues:

1. In-Depth Psychological Profiles

Traditional buyer personas owe a lot to the age of mass media. Because the demographic data that media companies gathered to understand their audiences drove most advertising purchases, customer research naturally focused on demographics-driven profiles. Today, with the dominance of programmatic and behavioral response advertising, profiles need to begin by plumbing the psychological triggers and levers that determine the response to your advertising.

2. Detailed Message Documentation

Most organizations have only a handful of core stories that make up the majority of the messages they need to persuade a customer to buy. While they may need dozens of hundreds of different assets across their marketing mix, those assets reinforce those core ideas.

Given how vital those core stories and ideas are to the ultimate success of an organization's marketing efforts, it's surprising how few organizations ever document what those stories are nor do they focus their efforts on continuously testing and improving them. Indeed, in my more than 20 years as a professional marketer, none of my clients, from the Fortune 500s to the startups, have ever had that kind of strategic documentation before working with me.

3. Character-Based Brand Strategy

Donald Miller's Story Brand has popularized the idea that all brands need a story. While he builds his argument on "the hero's journey," in practice, his framework is a simplified sales letter. And yes, a sales argument (or selling story) is an important component of every brand's marketing. It's the most direct path to creating a customer.

That said, this approach to brand building ignores the most significant elements necessary to creating a charismatic brand, one that can build an authentic relationship with one's customers. A strong brand isn't a story: it's a character that has a distinctive personality, values, strengths, weaknesses, and motivations. The more authentic and relevant the brand is to your customers, the more readily they will come to know, like, and trust your brand.

This character-based approach to brand development has significant implications for how we can get the most value from our use of AI in marketing. Brand fidelity is no longer merely an exercise in design guidelines and visual cues. Instead, we need ways to prompt our AI tools to generate assets that maintain a consistent tone of voice and personality that brings our brand character to life.

We achieve that goal by building a six-factor model of the brand character and adopting an archetype that can give that brand character a deep psychological resonance with your customers. By embedding that character framework in knowledge-base documents and/or stylistic prompts, we can speed the development of on-brand copy to ensure that even your more overt sales-oriented marketing assets reinforce your efforts to strengthen your brand.

4. Message-First Media Calendar & Go-To-Market Plan

A messaging strategy and brand character strategy will accomplish little unless they are operationalized to drive an organization's marketing efforts.

The first step is to use the message and brand character to evaluate existing marketing efforts. Often, this exercise uncovers existing marketing efforts that are on-strategy that can be built upon. It also usually reveals gaps that exist and must be filled by developing new marketing assets and initiatives.

The in-depth psychological profile can also serve as a guide to understanding the customer journey. A map of the customer journey is often a useful guide to developing a comprehensive content calendar that can be used to ensure that the content and ads you develop with AI advance your overall strategic goals.

Conclusion

While AI holds tremendous promise for marketing, unlocking this potential requires a thoughtful approach. By balancing AI capabilities with human creativity and strategic thinking, organizations can harness the power of AI without getting lost in the noise.

Unlocking the full potential of AI to revolutionize one's approach to marketing requires a different approach to strategy than most positioning-based models in vogue today employ. By focusing on your ideal customer's psychographics, reverse engineering the messages necessary to persuade your prospects to become customers, and developing a robust framework for your brand character, you can prompt your AI tools to develop assets in ways you can be assured with advance your marketing goals.