The Secret to High-Quality AI-Generated Marketing Content

by Jeff Morgan, see original article here.

Want to dramatically improve the quality of your AI-generated marketing content?

The key is feeding the model with trusted data.

And one potentially overlooked source of trusted data is your messaging framework.

A messaging framework is a strategic document that outlines the core messages you want to communicate to your target audience. It serves as a guide for all marketing communications and ensures consistency and clarity across various channels and touchpoints.

Conveniently, it just happens to include everything generative AI needs to deliver high-quality, on-brand, on-message content.

Here's a breakdown of the components I like to include in a messaging framework:

Brand Glossary: Define key terms, phrases, and concepts that are central to your brand, industry, and target audience.
Brand/Product Naming Conventions: Approved company name, taglines, and usage guidelines.
Target Audience Definition: Clearly identifying the intended audience, their demographics, goals, challenges, fears, buying motivations, common objections, preferred communication channels, etc.
Value Proposition: A clear statement summarizing the primary benefits your product delivers to your target customers. It communicates the value customers can expect to receive and what differentiates the offering from competitors.
Messaging Pillars: The unique selling points that support your value proposition. Pair the top 3-4 prospective customer challenges with your product's key benefits, advantages, features, and proof points.
Style Guide: Your preferred writing style, tone, voice, cadence, etc.
Messaging Examples: Include samples of your very best ads, emails, articles, social posts, video scripts, etc.

Here's the prompt playbook:

Use Claude 3 Opus (yeah, the paid version). In my testing, it has consistently produced superior marketing copy to ChatGPT or any other model.
Upload your messaging framework.
Upload additional reference material. For example, if you want to write an article about how the statistics in a new research study support your value proposition, upload a PDF of the study.
Craft a prompt that answers the following questions:

In your dream world, who would be writing this content? (e.g., "Take on the role of a world-renowned <subject matter> expert who specializes in writing for <Brand Category> who sell to <Target Audience>.")
What reference material should be used? (e.g. "Using the attached messaging framework and <insert name of topic reference> as reference material,")
What is the medium, objective, and topic of what you want written? (e.g., "write an <medium>, designed to <objective>, that focuses on <topic>.")
Any special instructions? (e.g. This <medium> should not exceed <# of characters> and should use best practices for <instruction>.)

Now, putting it all together...

Perfect? No.

Pretty close to usable? Yes.

Saved a lot of time? Absolutely.

I'm confident that following this approach will allow you to create AI content that is actually usable in way less time.

But don't just take my word for it – try it out for yourself!

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