Prompt Playbook: Marketing Foundations PART 1
Steve Jobs stood on stage in 2001 holding a small white device. He could have said "5GB MP3 player with FireWire connectivity and 2MB cache buffer."
Instead he said: "1,000 songs in your pocket."
Same product. Completely different positioning. And it changed everything.
Microsoft's Zune had better specs, larger storage, wireless sharing. But their message was all about technical features. Apple's iPod had inferior technology but superior positioning.
It doesn't matter how good your product is if you can't communicate why someone should care about it. The best product doesn't win.
You've built something that works. Your beta testers love it. But if you can't explain it in a way that makes new people want it, you'll struggle to grow beyond your initial supporters.
This week is about fixing that gap - turning what you've built into something people understand and want. We’re putting together your basic marketing assets and getting ready to launch.
Let’s get started
Summary
Talk their language
Building marketing assets for our waitlist launch
Component parts that become landing page
User language beats feature lists
Real outcomes over technical specifications
Descriptions that convert
The Week Ahead: Gathering Marketing Assets
This week we're gathering the marketing assets you need for your waitlist launch. Think of it like collecting the right ingredients before you cook - you need quality components before you can create something that works.
We’ll build towards an early bird waitlist launch to the communities that helped you during beta testing. That’s the goal. And to get there we need (deep breath):
Product descriptions using real user language (today)
Social proof from your beta testing (tomorrow)
Landing page assembly (Day 28) - this is when we actually build the page
Soft validation with champions (Day 29)
Waitlist launch to communities (Day 30)
We're not building the landing page yet! That's Day 28. Right now we're gathering the raw materials we'll need to make it effective.
We're also not launching payments yet - that's Week 7. This week is about building anticipation and collecting email addresses from people who want early access.
We’ll build up step by step to make this all doable!
Why User Language Beats Feature Lists
OK first let’s get the language we use about our product locked in.
You've spent weeks building your product. You know every feature, every technical detail, every clever bit of functionality you've created.
We actually have all this language in our research, product specs and build guides from before. It’s all in our AI chats. And it’s super tempting to recycle. Don’t!
Your users don't care about any of that language.
They care about the outcome your product delivers to them. They care about the problem it solves and how it makes their life better. That’s it.
They don’t care about how you built it. What you used. What neat technical tricks are involved. When you describe your product using technical features, you're speaking your language, not theirs. When you use the exact words they used to describe their problems and outcomes, you're speaking their language. That’s the switch we need to make.
Look at your Week 5 feedback. Notice the difference between how you think about your product and how they describe what it does for them. You might say: "Advanced workflow optimisation with intelligent task delegation." Blurgh. They might say: "Finally, something that helps me stop dropping the ball on important projects."
Their version wins every time. And we’re going to use it.
Mining Your User Research
Time to go back through all those conversations and feedback from Week 5. You're looking for three specific things:
Problem Language: How do they describe the issue you're solving? What exact words do they use? How do they explain it to others?
Outcome Language: When they talk about the results or benefits, what words come up repeatedly? How do they describe the change or improvement?
Emotional Language: What frustrations, relief, excitement, or other emotions come through in their feedback?
If three different people said your tool "saves time," use "saves time." If they said it "stops the chaos," use "stops the chaos." We want to mirror their exact words in what comes next.
Don't summarise or paraphrase. Use their exact words. If you did calls we want the full transcripts. If we talked via email or text get a file with the messages. We want the raw material. Your job is to become a translator between what you built and what they experience.
Writing Product Descriptions That Convert
What’s our goal here? We’re going to mine all that material and pull out a few different formats that we can use in marketing. You need descriptions for different contexts, but they should all use the same core user language. Start with the shortest and work your way up:
One-Sentence Value Proposition: The clearest, most compelling way to explain what you do using user language. This goes everywhere. This is your tagline.
Short Description (2-3 sentences): For social media, email signatures, quick explanations. Problem + solution + outcome.
Medium Description (paragraph): For landing pages, longer social posts, email announcements. Problem + solution + outcome + proof.
Long Description (multiple paragraphs): For detailed pages, blog posts, comprehensive explanations. Full story with examples.
The key is consistency. The same core message, just expanded based on context. We need them all. But they all come from the same root - the language of our users.
Thankfully we can get all of these from our users’ language using AI.
Your AI Prompt for Today
I need to create product descriptions using real user language from my beta testing feedback. Here's my collected feedback and conversations: [PASTE ALL FEEDBACK FROM WEEK 5] My product is: [BRIEF DESCRIPTION OF WHAT YOU BUILT] Help me extract and organise: 1. Problem Language: Exact words users used to describe the problem I'm solving
2. Outcome Language: How they described the results or benefits they experienced 3. Emotional Language: Frustrations, relief, excitement they expressed
4. Feature Translation: How they described what my product does (not technical features) Then create these descriptions using their language: 1. One-sentence value proposition (under 20 words)
2. Short description (2-3 sentences for social media)
3. Medium description (paragraph for landing page)
4. Long description (multiple paragraphs with examples) Use their exact words and phrases wherever possible. Focus on outcomes and benefits, not features and functionality.Feed in everything from your beta testing week. This is what AI is great at. Let the AI help you spot patterns and extract the language that actually resonates. We’re just guiding the process with the prompt.
Testing Your Descriptions
Before you build anything, test these descriptions with a few people who know your product. Send them to 2-3 of your beta testers with a simple question: "Does this make sense? Would you describe it differently?"
Also test them on people who don't know your product. Read them the one-sentence value proposition and see if they immediately understand what you do and who it's for. There should be no confusion.
Good descriptions pass both tests: they resonate with people who've used your product AND make sense to people hearing about it for the first time. We need both!
Your Deliverable Today
Create your complete set of product descriptions
Use the AI prompt to extract user language from your Week 5 feedback
Write your one-sentence value proposition using their words
Create short, medium, and long descriptions
Test with 2-3 beta testers for clarity and accuracy
Refine based on their feedback
These descriptions become the foundation for everything else this week. Get them right and the rest flows much easier. Get them wrong and the rest of the marketing assets will be compromised. This simple step of copywriting is super important - don’t rush it.
Build in Public Content
Share your learning process with a post along these lines
"Day 26 of AI Summer Camp: Rewriting how I describe my product.
Went back through all my user feedback from beta testing. The disconnect is mental.
I was describing features: 'AI-powered workflow optimisation' Users described outcomes: 'stops me forgetting important stuff'. Made me realise I need to listen more.
Their version is 10x better. Building my landing page with their language, not mine.”
What's Next?
Tomorrow we collect social proof from your beta testing - testimonials, case studies, and results that show your product actually works. Combined with today's user-language descriptions, you'll have the core content for a landing page that converts.
Keep Prompting,
Kyle