This AI system finds winning ads at scale

Key Concepts

• Message Testing: A system for testing different ad messages (hooks, headlines, stories) to identify the most resonant wording for a target audience.
• AI Automation System: A system leveraging AI and a spreadsheet to automate market research, hook generation, static ad creation, and ad importing.
• Static Ads: Simple image ads with a hook or statement, used to isolate and test the effectiveness of the message.
• Traffic Ads: Ads optimized for driving traffic, used in message testing for cost-effective data acquisition.
• Hooks: Short, attention-grabbing phrases or questions designed to pique the interest of potential customers.
• Personas: Representations of ideal customers, used to tailor ad messaging.
• Angles: Different ways to position a product to appeal to different customer needs or desires.
• Meta Marketing API: Facebook's API for programmatically managing ads.
• Make.com: An automation platform used to connect different applications and services.

Message Testing System Overview

The video details a system for rapidly testing ad messages to identify the most effective wording for a product. The core idea is that the words used in advertising are crucial for convincing prospects, and a systematic approach is needed to discover the best ones. The system uses AI automation to generate and test thousands of ad variations quickly and cost-effectively.

Step-by-Step Process

1. Market Research (Prerequisite):
   • Define the target prospect's problems.
   • Use Google queries to find relevant forum posts, Reddit threads, social media discussions, and Amazon reviews.
   • Process the collected data using tools like Notebook LM to extract customer wording, pain points, and values.
   • The video references a previous video on the channel titled "Market Research is Easy" for a detailed explanation of this process.
2. Variable Definition:
   • Define variables to test, such as:
     • Persona: The target customer profile (e.g., consultant, content creator).
     • Call Out: A specific term to address the target audience (e.g., advisors instead of consultants).
     • Message Framework: The type of message (e.g., sentiment, pain prompt, desire, future state, story-based).
     • Angle: How the product is positioned to solve a specific problem or fulfill a desire.
     • Model: The AI model to use (e.g., Cloud, ChatGPT-4, O3 mini).
3. Hook Generation:
   • Use the defined variables to generate a large number of hooks using AI.
   • The system uses a spreadsheet as a base, with columns for Persona, Call Out, Message Framework, Angle, Model, and the generated Hook.
   • The spreadsheet triggers webhooks to initiate AI automations.
4. Human Supervision and Refinement:
   • Review the generated hooks and remove or modify the ones that are not high quality.
   • This step is crucial to ensure the quality of the tested messages.
5. Static Ad Creation:
   • Select a template for the static ad (e.g., true/false, headline).
   • Use an automation tool (the video mentions a tool with a variable-based template system, link in description) to generate images with the hooks.
   • The tool allows using variables like "headline" and "call out" in the template.
6. Ad Importing:
   • Use the Meta Marketing API and Make.com to import the generated ads into the ad account.
   • The system uses the image link to create ads with the image within it.
   • The ad name is a concatenation of the Persona and the beginning of the hook for easy identification.
7. Message Testing Campaign:
   • Create a testing campaign in the ad account dedicated to message testing.
   • Create ad sets within the campaign.
   • Run traffic ads with a simple headline and a link to a landing page or even a Typeform.
   • Set up a rule to stop ads after approximately 500 impressions.
8. Result Analysis:
   • Analyze the results (click-through rates) to identify the best-performing hooks.
   • Focus on ads with significantly higher click-through rates (e.g., 5-10%).
   • Identify the personas and angles that resonate most with the audience.
9. Iteration and Refinement:
   • Iterate on the best-performing hooks by creating variations, changing the emotion, or transforming questions into stories.
   • Repeat the testing process in phases to refine the messaging.
10. Application of Findings:
    • Use the insights from message testing to inform the creation of:
      • Video sales letters (VSLs)
      • Landing pages
      • Value propositions
      • Overall product presentation

Technical Details

• Spreadsheet as a Base: The system uses a spreadsheet (Google Sheets or similar) to manage the variables, generated hooks, and ad data.
• Webhooks: Webhooks are used to trigger automations based on changes in the spreadsheet.
• AI Models: The system supports different AI models (Cloud, ChatGPT-4, O3 mini) for hook generation.
• Meta Marketing API: The Meta Marketing API is used to programmatically create and manage ads in Facebook.
• Make.com: Make.com is used to connect the spreadsheet, AI models, and the Meta Marketing API.
• Traffic Ads: Traffic ads are used for message testing because they are a cost-effective way to acquire data.

Key Arguments and Perspectives

• Words Matter: The video emphasizes that the words used in advertising are the most important factor in convincing prospects.
• Systematic Approach: A systematic approach to message testing is necessary to identify the most effective wording.
• AI Automation: AI automation can significantly speed up the message testing process and reduce costs.
• Human Supervision: Human supervision is crucial to ensure the quality of the generated hooks.
• Data-Driven Decisions: Advertising decisions should be based on data from message testing, rather than guesswork.

Notable Quotes

• "It doesn't matter how good your product is... what matters is... the words you use to help your prospect to convince themsel that your product is the solution to their problem."
• "Without it [the message testing system] everything you do is irrelevant. You are basically guessing."

Conclusion

The video presents a comprehensive system for message testing that leverages AI automation to generate and test thousands of ad variations quickly and cost-effectively. The system emphasizes the importance of using data-driven insights to inform advertising decisions and highlights the crucial role of human supervision in ensuring the quality of the tested messages. The key takeaway is that by systematically testing different ad messages, businesses can identify the most effective wording for their products and significantly improve their advertising results. The system is not just about the technical implementation but also about the marketing mindset of focusing on the words that resonate with potential customers.