Seller Sessions Amazon FBA and Private Label

Welcome back to Conversion Monthly! Danny McMillan is joined by the full team — Sim, Matt Kostan, and Dorian — plus special guest Anna, who launched a reusable microfiber cleaning cloth roll on Amazon UK. Anna's product is clever — an eco-friendly alternative to paper towels that's washable and comes in multiple colors. But the listing isn't converting. The team digs into exactly why and what to fix. What's Covered in This Episode: Main image problems — Why Anna's current main image fails to communicate what the product actually is, and how showing roll thickness, sheet count, and color options can dramatically increase click-through rate Baseline click share testing — Matt runs a 100-person UK shopper poll revealing Anna's listing captures only 10% of clicks against competitors The power of color — Shoppers gravitate toward listings showing multiple color options, and the team discusses how bolder, richer colors (not pastels) pop on search results Secondary image ordering — Dorian's favorite test reveals that simply reordering existing images based on what shoppers care about most (reusability and washability) can boost conversions without changing a single image Title strategy — Why keyword stuffing kills readability and how "speed bump keywords" like "washable" or "tear-away" differentiate you from competitors Cost-saving as a conversion lever — Framing the product as a money-saver versus annual paper towel spend gives instant price justification Before-and-after imagery — "Show me, don't tell me" — why context-driven images outperform generic product shots German marketplace analysis — What the German Amazon sellers are doing right with richer colors, dynamic angles, and clean layouts New main image results — After updating the main image with Dorian's mockup, click share jumped 60-70% in testing Key Takeaways: If shoppers can't tell what your product is from the main image, nothing else matters The order of your secondary images matters as much as the images themselves — answer objections early Titles need to balance keyword volume with readability — a title nobody understands won't convert regardless of search volume Look at what competitors in other marketplaces (especially Germany) are doing for image inspiration Test before you invest in final designs — quick mockups and polling save time and money Connect with the Team: Matt Kostan — matt@productpinyon.com Sim — LinkedIn (also recruiting brand managers) Dorian — LinkedIn Anna — LinkedIn

Danny McMillan and Shubhash Sharma are back with another Claude Sessions episode covering both the back end and front end of building your Amazon business infrastructure with AI. Shubhash walks through exactly how to register for Amazon's Seller Partner API — your free, direct access to your own sales, inventory, pricing, and order data — no third-party subscriptions required. Danny then breaks down the 165-feature design system he built to eliminate AI slop from websites, landing pages, and app interfaces. Part 1: Amazon SP-API Setup (Shubhash) What SP-API is — Amazon giving you a key to your own data warehouse: live inventory, real-time orders, pricing, catalog data, and sales reports 5-step registration process — Register as developer, create an app, select permissions, self-authorize, and connect to Claude Code to build dashboards Common rejection reasons — Usually a missed checkbox or vague answer about data usage. Keep answers focused on personal brand development and safe data storage Advertising API is separate — Different credentials, different registration, different refresh token. You cannot reuse SP-API tokens for ads What you can build once connected — Custom dashboards, forecasting engines, inventory alerts, automated reporting — all built by Claude Code without knowing Python Danny's guardrails — Hire a $50 Upwork specialist to help with paperwork submission, keep them on retainer for when APIs go down (especially Q4, Black Friday, Prime Day) Part 2: The 165-Feature Design System (Danny) The AI slop problem — Default fonts (Roboto, Arial), purple-blue gradients, three-column card layouts, floating animated orbs, oversized border radius — all telltale signs of generic AI output 15 anti-patterns cataloged — The system actively fights against common AI design defaults Four-phase pipeline — Decide, Design, Build, Refine — with 15 databases and components extracted from 11 repos Gap analysis scoring — Rates output out of 60 points. Seller Sessions Live went from 33 to 50; Databrill went from 48 to 55 Psychology of design baked in — Hick's Law (limit choices to 5-7), Miller's Law (chunk information in groups), Jacob's Law — all running automatically in the background "Pretty doesn't convert" is a cop-out — Apple, Ralph Lauren, Sony all prove that quality design builds trust. The real issue was budget — now AI removes that barrier Design is about subtraction — Cut 69% of animations in one project. Overcooking destroys user experience 25 quality gate techniques — Color tokens, typography rules, contrast ratios, accessibility (100+ rules), spacing, and composition patterns Claude Loom workflow — Record feedback via Cmd+Shift+L, Claude extracts screenshots and browser URLs, and the system pushes back if changes violate the design system Key Takeaways: SP-API is free and gives you direct access to your Amazon data — do it tonight The Advertising API requires a completely separate registration process Have a backup developer on standby for API downtime, especially during peak sales periods AI-generated interfaces all look the same because they default to the same fonts, colors, and layouts A design system isn't about making things pretty — it's about trust, conversion, and consistent user experience across all devices Before your customer reads a single word of copy, your page load time and visual quality have already made an impression Coming Next: Shubhash experiments with running AI models locally on an old MacBook using Ollama — cutting token costs to zero. Connect: Shubhash Sharma — LinkedIn Danny McMillan — sellersessions.com

Subash, e-commerce ops lead at Not A Square who scales brands to multi-seven/eight figures, joins to discuss AI-powered operations. He shares a TikTok case where a Claude-built support agent lifted satisfaction quickly. They cover documenting processes before automating, security trade-offs of local agents like OpenClaw, and why deep focus on one platform plus persistent memory (ChromaDB) prevents context loss.

Adam Jagger, founder of a women's knitwear brand selling jumpers on Amazon. The team dissects a stalled relaunch and shopper feedback. They test Zara-inspired low-angle mains, strip back busy secondaries, and run pre-launch polls. Visual overhaul yields a big simulated click-share lift and clear steps for fashion listing fixes.

Adam "Heist" Runquist, an Amazon seller, consultant, and marketplace analyst. He unpacks Prime saturation and why future member growth is nearly tapped out. He examines the shift from first‑party retail to ad‑driven revenue and how seller margins are being squeezed. He explains why Rufus could flip Amazon into a discovery platform and urges extreme listing efficiency powered by AI.

Danny and Ritu dive deep into Anthropic's new Cowork feature in Claude Desktop - the good, the bad, and the ugly. Ritu shares a cautionary tale about file deletion gone wrong, while Danny demonstrates his custom skills pack that protects users from common pitfalls. What You'll Learn: What Cowork is and how it differs from Claude Code and Claude Desktop Why the rm -rf command can permanently delete your files (and how to prevent it) How to set up deny lists in your Claude settings to protect critical files The power of skills and bootstrap files for consistent, reliable outputs Decision panels: letting Claude guide you through complex choices Cascade skills: research to article to slides in one automated flow Key Timestamps: 00:00 - Introduction to Cowork 02:13 - Ritu's file deletion disaster story 08:37 - Understanding rm vs rm -rf commands 10:01 - Setting up deny lists for protection 16:00 - Evolution from Claude Desktop to Claude Code to Cowork 25:55 - Skills deep dive: orchestrator, quality gate, flow state 39:48 - Research cascade skill demonstration 43:18 - Decision panels walkthrough 48:58 - 2026 predictions: Ambient AI and pixel-free interfaces Resources Mentioned: Danny's Skills Pack (available to listeners) Typora - Markdown editor ($14 lifetime) Time Machine backup for Mac users Git for version control Connect with Ritu Java: LinkedIn Connect with Danny McMillan: LinkedIn | Seller Sessions

Conversion Monthly - The panel kicks off 2026 with predictions on AI-driven creative workflows, agentic shopping behaviours, and the tools reshaping Amazon seller operations. Host: Danny McMillan Panel: Sim Mahon, Dorian Gorski, Matt Kostan Episode Summary The newly rebranded Conversion Monthly show returns with its expert panel to discuss 2026 predictions for Amazon creative optimisation. The conversation covers how AI workflows have evolved since early 2025, with Dorian noting how N8N has become significantly more accessible through built-in AI assistants. Sim shares that his team can now create final, upload-ready main images in a single AI generation. The panel discusses agentic shopping and how AI-driven product discovery may fundamentally change conversion optimisation. Matt highlights the trend toward hyper-specific product positioning, where sellers create separate ASINs for the same product targeting different demographics. Danny introduces Claude's new Co-Work feature as a significant leap that removes technical barriers for sellers wanting to build automations. The panel agrees that "human in the loop" will be the defining phrase of 2026. Sim reveals his investment in 51 Folds, a prediction platform using Bayesian networks. Key Takeaways One-shot main images are now reality - AI image generation has reached the point where final, upload-ready Amazon images can be created in a single prompt Hyper-specific product positioning is trending - creating separate ASINs for the same product targeting different demographics aligns with AI recommendations Technical barriers to automation are evaporating - tools like Claude Co-Work and improved N8N AI assistants are making workflow automation accessible "Human in the loop" defines 2026 - the winning strategy combines automated data collection with human strategic oversight The big three AI providers have stabilised - Anthropic, Google, and OpenAI now dominate, reducing shiny object syndrome Video generation remains the next frontier - while image generation is solved, video still requires scene-by-scene refinement Chapter Markers 00:00 - Introduction and 2026 Outlook 00:58 - Dorian on the Pace of Change Since 2025 04:07 - N8N Accessibility and Self-Build Workflows 05:33 - One-Shot Image Generation Capabilities 07:23 - Video Generation Limitations 10:26 - Business Systems, ClickUp and Future-Proofing 14:37 - Hyper-Specific Product Positioning 20:06 - Keplo 2026 Direction 22:26 - Competitive Advantage and AI Accessibility 25:01 - The Big Three AI Providers 28:46 - 51 Folds Investment and Bayesian Prediction 33:14 - Panel 2026 Priorities 38:12 - Wrap-Up Resources Seller Sessions Website Seller Sessions YouTube Sim Mahon on LinkedIn Dorian Gorski on LinkedIn Matt Kostan on LinkedIn

Broad Match: Adapting to Amazon's Evolving Landscape: Insights for 2026 Episode Overview In this episode, Danny McMillan and Adam Heist discuss the changes in Amazon selling strategies as we approach 2026. They emphasize the significance of adapting to new search algorithms and shifting consumer behaviors to ensure success in the competitive marketplace. This episode explores amazon selling strategies, search algorithm evolution with practical insights for immediate implementation. Key Takeaways Sellers need to rethink traditional SEO practices in light of new individualized search results. Embracing change and new technologies is essential for remaining competitive in the evolving marketplace. Chapter Markers Time Chapter Description 00:00 Reflections on the Past Year Adam Heist reflects on 2025, stressing the importance of taking time for strategic planning after the holiday season. 05:30 The Shift in Search Dynamics Discussion on how Amazon search results are becoming more individualized, reducing sellers' control over visibility. 10:15 The Impact of Rufus on Seller Strategies Adam shares insights on the Rufus algorithm and its significant effect on conversion rates and product discovery. 15:00 Adapting to the New Normal Danny emphasizes the need for sellers to rethink their approaches as customer behavior changes. 20:45 Embracing Change and Opportunity Both hosts encourage sellers to embrace technological changes as opportunities for growth. Notable Quotes "The successful sellers of the future will be those who can navigate the evolving landscape." Resources Mentioned 🔧 Tools & Platforms: Rufus Algorithm: A new algorithm that significantly alters the way search engine results pages operate on Amazon, affecting sellers' strategies. 🔗 Guest Links: No guest this episode 📖 Seller Sessions Resources: YouTube: Seller Sessions Channel Website: Seller Sessions Rufus Blueprint: Complete Amazon Algorithm Guide Honeymoon Period Research: Scientific Analysis Seller Sessions Live 2026: Conference Registration Subscribe to Seller Sessions YouTube: Seller Sessions Channel Website: Seller Sessions

Main Image Monthly: Optimizing Beauty Products for Conversion: Insights with Aaron Graybill Episode Overview In this episode, Aaron Graybill discusses the challenges and successes of launching her whipped beef tallow lotion, focusing on product formulation, customer feedback, and the importance of visual optimization for increasing conversions. The conversation delves into strategic improvements for product listings and customer expectations in a competitive beauty market. This episode explores beauty product formulation and challenges, strategies for visual optimization in e-commerce with practical insights for immediate implementation. Key Takeaways Customer education is essential to address concerns and improve conversion rates, especially for niche products like beef tallow lotion. Visual aesthetics in product listings significantly impact customer perception and purchasing decisions. Chapter Markers Time Chapter Description 00:00 Introduction Danny McMillan introduces Aaron Graybill and the discussion around her beauty product. 01:15 Product Backstory Aaron shares the backstory of her whipped beef tallow lotion and challenges faced with product formulation. 02:44 Managing Customer Expectations Discussion on balancing profitability while addressing customer concerns about product quality. 05:27 Understanding Product Differentiators Insights into the unique selling points of her product compared to competitors in the beauty niche. 06:15 Product Image Optimization Danny discusses the importance of optimizing product images using data analysis. 07:06 Visual Appeal vs. Informational Content Exploration of visual optimization strategies to stand out in online listings. 35:52 Key Takeaways and Next Steps Final thoughts on applying insights from the episode for product improvements. Notable Quotes "Pressure makes diamonds." Resources Mentioned 🔧 Tools & Platforms: Clickbait Thumbnail Generator: A tool developed to generate catchy thumbnails for video content to increase engagement. 🔗 Guest Links: No guest this episode 📖 Seller Sessions Resources: YouTube: Seller Sessions Channel Website: Seller Sessions Rufus Blueprint: Complete Amazon Algorithm Guide Honeymoon Period Research: Scientific Analysis Seller Sessions Live 2026: Conference Registration Subscribe to Seller Sessions YouTube: Seller Sessions Channel Website: Seller Sessions

Broad Match: Images Outside The Echo Chamber: The Power of Product Opportunity Explorer Episode Overview In this episode, Adam shares insights on leveraging Amazon's Product Opportunity Explorer tool to enhance product marketing strategies and conversion rates. The discussion highlights the importance of clean imagery, understanding customer demographics, and optimizing listings based on data-driven insights. This episode explores amazon business strategies, product optimization techniques with practical insights for immediate implementation. Key Takeaways Utilizing Amazon's Product Opportunity Explorer is crucial for identifying growth opportunities and optimizing existing product listings. The importance of clean, professional imagery cannot be overstated; it plays a significant role in customer perception and trust. Chapter Markers Time Chapter Description 00:01 Introduction and Updates Danny and Adam discuss the challenges of launching the episode and set the stage for the topics to be covered. 00:57 Exploring Product Opportunity Explorer Adam dives into the functionalities of Amazon's Product Opportunity Explorer and how it can uncover product growth opportunities. 07:08 Understanding Customer Needs A detailed examination of how Amazon's tool provides insights into customer needs, keywords, and the competitive landscape for product optimization. 08:35 Application of Insights for Image Optimization Adam discusses how to apply insights from the Product Opportunity Explorer to optimize images and listings, enhancing conversion rates. 16:44 Comparison of Different Marketing Strategies Danny raises the importance of evaluating different marketing approaches and how traditional methods may not always deliver results. 18:38 Analysis of Social Priming and Consumer Behavior The conversation shifts to social priming and its impact on consumer behavior, discussing how it relates to image strategy. 55:37 Conclusion and Final Thoughts Danny and Adam wrap up the discussion, emphasizing the need for sellers to adapt strategies based on data and market conditions. Notable Quotes "If you haven't checked out Product Opportunity Explorer, it could be one of the biggest hidden gems and the biggest data developments that I've seen within Amazon in years." Resources Mentioned 🔧 Tools & Platforms: Product Opportunity Explorer: A feature in Amazon Seller Central that helps sellers identify product opportunities based on consumer demand and competitive analysis. Google Docs: A tool used for organizing and extracting data from the Product Opportunity Explorer tool. 🔗 Guest Links: No guest this episode 📖 Seller Sessions Resources: YouTube: Seller Sessions Channel Website: Seller Sessions Rufus Blueprint: Complete Amazon Algorithm Guide Honeymoon Period Research: Scientific Analysis Seller Sessions Live 2026: Conference Registration Subscribe to Seller Sessions YouTube: Seller Sessions Channel Website: Seller Sessions