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How to Reverse Engineer 8-Figure Ads in 3 Steps

This 3-step framework breaks down exactly how to reverse engineer high-converting ads from 8 and 9-figure brands and turn them into winning assets for your own brand in under 60 seconds.

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How to Reverse Engineer 8-Figure Ads in 3 Steps featured image - Growth blog post | Growthub

Scaling creative output without sacrificing quality is the single biggest bottleneck killing growth for DTC brands.

Most teams either burn out their creative directors trying to pump out volume, or they flood the market with mediocre assets that tank ROAS.

There's a better way.

This 3-step framework breaks down exactly how to reverse engineer high-converting ads from 8 and 9-figure brands and turn them into winning assets for your own brand in under 60 seconds.

https://youtu.be/fokR8O19DIA


Step 1: Goal Setting and the 5 Stages of Awareness

Every winning ad starts with one question: Where is your customer in their awareness journey?

The 5 Stages of Awareness dictate everything from your hook to your CTA:

🔹 Unaware - They don't know they have a problem

🔹 Problem Aware - They know the problem but not the solution

🔹 Solution Aware - They know solutions exist but not your product

🔹 Product Aware - They know your product but haven't bought

🔹 Most Aware - They know you and just need the right offer

5 Stages Breakdown Infrographic

Here's why this matters: An ad targeting someone "Unaware" requires a completely different creative approach than one targeting "Product Aware" customers.

Take the Gruns example from the video. Targeting cold, unaware audiences means leading with education and pattern interrupts. Targeting warm audiences means leading with proof and urgency.

Match your creative to the awareness stage, or watch your ad spend evaporate.


Step 2: Competitive Research and Funnel Mapping

Stop trying to reinvent the wheel.

The fastest path to winning creative is studying what already works for brands doing 8 and 9 figures.

Competitor Customer Journey

Here's the process:

Identify Reference Ads Pull high-performing ads from brands like AG1. Look for creative that's been running for 30+ days with high engagement. Longevity signals performance.


These Two Static Ad Frameworks dominate DTC right now:

🔹Product Close-up - Tight shots showcasing texture, quality, and premium feel

🔹USP Highlight - Leading with the single most compelling differentiator

Map the Full Funnel Don't just study the ad. Follow the entire customer journey from ad click to landing page to offer. The ad is one piece of a conversion system.

Customer Journey Breakdowns

When you understand why an ad works within its funnel context, you can adapt that logic to your brand without copying the creative.


Step 3: AI-Powered Execution

This is where the framework becomes a scalable system.

Using AI Agents and the Nano Banana model, you can take a reference ad, apply your custom brand kit, and batch-generate winning creative assets in 30 seconds.

The Workflow:

🔹Feed the reference ad into Sub-Agents - These analyze and describe every element: hook structure, visual composition, text hierarchy, CTA placement

🔹Apply your brand kit - Colors, fonts, tone, product imagery get layered onto the proven framework

🔹Batch generate variations - Produce 10, 20, 50 variations for testing without manual design work

Growthub Workflow Outputs

This isn't about copying. It's about understanding the principles behind winning creative and applying them at scale with your unique brand assets.


Key Takeaways

👉 Use the 5 Stages of Awareness to dictate every element of your ad

👉 Map the entire customer journey from ad click to landing page offer

👉 Build an AI Creative Ops infrastructure to produce ads at volume

👉 Deploy Sub-Agents to analyze and describe ad elements for faster generation

Blog Summary Graphic




Ready to 10x Your Creative Output?

This framework turns one winning ad concept into dozens of testable variations without burning out your team or sacrificing quality.

Watch the full breakdown above to see the AI workflow in action.

TL;DR

Learn how to effectively reverse engineer high-performing ads from 8 and 9-figure brands using a structured 3-step framework, enabling rapid asset generation that enhances growth potential for your own branding efforts.

FAQ

What is the purpose of reverse engineering ads?

Reverse engineering ads helps brands understand successful strategies to create effective marketing assets, enhancing growth.

How does the 5 Stages of Awareness impact ad strategy?

Each awareness stage requires a unique creative approach to engage the target audience effectively, from education to urgency.

What types of ads are most effective in DTC marketing?

Product close-ups and unique selling propositions (USP) highlight the key features that resonate with consumers, particularly when research is applied.

How can AI improve ad creation?

Growthub.ai can automate the ad generation process, allowing for rapid creation of customized marketing assets that maintain brand identity.

What factors indicate a successful ad?

Longevity and high engagement rates over 30 days are indicators that an ad resonates well with its target audience and performs effectively.

What is the Nano Banana model?

The Nano Banana model is a strategy that incorporates AI to streamline the creative process, optimizing workflow for advertising campaigns.

Why is competitive research important?

Studying successful competitors provides insights into effective tactics and helps avoid reinventing the wheel in ad creative.

What is the significance of goal setting in advertising?

Setting clear goals guides the ad's messaging and strategy, aligning it with the customer's awareness and needs.

How long does it take to generate winning assets?

By following the framework and utilizing AI tools at Growthub.ai, brands can create effective advertising assets in under 60 seconds.

What should I focus on when mapping funnels?

Understand each touchpoint in the customer journey from the ad click through to the purchase decision to ensure cohesive messaging.

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