#495 - The AI Workflow for Winning Amazon Main Images episode artwork

EPISODE · Feb 11, 2026 · 42 MIN

#495 - The AI Workflow for Winning Amazon Main Images

from AM/PM Podcast · host Helium 10

Still guessing on Amazon listing images? Today's guest shares a simple AI image workflow that makes decisions easy—what to fix first, what to test, and how to know it’ll win.   If your AI-generated Amazon images look “technically perfect” but still don’t convert, you’re not alone, and you’re not missing more prompts. In this AIM (AI Monthly) session, our Amazon creatives expert guest breaks down the real issue. AI and designers can execute, but they can’t decide strategy for you. That’s why sellers often spend thousands on creatives that look good, yet still fail to drive more clicks and sales.   Hannah Lyss Tampioc is the Founder and CEO of Mad Cat Creatives, and her team has worked with more than 300 brands. She walks through how shoppers actually buy on Amazon and explains why each image serves a different purpose. Your main image needs to stand out in mobile search results. Images two and three should help shoppers quickly understand what they’re getting. The rest of your images and A+ Content should build confidence by answering objections and removing hesitation. The key is figuring out whether you have a click problem or a conversion problem, then fixing the right part of your image stack instead of randomly “refreshing” everything.   The centerpiece of the episode is Hannah’s SORT framework. First, you spot the priority so you know what to fix first. Next, you gather the right context by pulling mobile search screenshots, competitor pages, reviews, and Rufus questions. Then you use that information to reason through the data, so your AI outputs are based on real buyer language instead of guesses. Finally, you test before committing by validating your image ideas with polling tools like the Helium 10 Audience tool, powered by PickFu, before you publish. You’ll also see a real example using Bradley Sutton’s Project X Coffin Shelf listing, where small changes like aspect ratio, mobile-first sizing, and packaging callouts helped the main image stand out more when it mattered most. By the end, you’ll know exactly what to fix first and how to follow a repeatable AI Amazon image workflow that confirms your next update will win before you publish. In episode 495 of the AM/PM Podcast, Bradley and Hannah discuss: 00:00 – Introduction 01:27 – The Missing Ingredient To Your Amazon Listing Images 02:31 – Meet Hannah & The “Named My Son Helium” Story 06:05 – The Real Issue: Strategy Beats Design + AI 09:02 – The Job Of Each Amazon Image Stack 11:17 – The SORT Framework Overview 11:41 – Click Problem vs Conversion Problem (What To Fix First) 12:23 – What To Gather Before You Design Anything 23:17 – Coffin Shelf Case Study: Mobile Size Wins 30:46 – ChatGPT Prompts & Gemini Image Generation Workflow 35:05 – “Main Image In 10 Minutes” & Gemini Tip 37:03 – Secondary Images: Use GPT For Briefs + Prompting 39:50 – Helium 10 Discount Code SSP20 + Q&A 42:04 – Where To Find Hannah (LinkedIn) & Mad Cat Creatives

Still guessing on Amazon listing images? Today’s guest shares a simple AI image workflow that makes decisions easy—what to fix first, what to test, and how to know it’ll win.

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#495 - The AI Workflow for Winning Amazon Main Images

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This episode was published on February 11, 2026.

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Still guessing on Amazon listing images? Today's guest shares a simple AI image workflow that makes decisions easy—what to fix first, what to test, and how to know it’ll win.   If your AI-generated Amazon images look “technically perfect” but still...

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