Sim Mahon, an eight-figure seller with six private label brands, joins forces with Matt Kostan, who leads consumer insights at ProductPinion, and Peter-Paul Maan from Intellivy. They dive into strategies for optimizing Amazon listings, focusing on main images to boost conversions. The trio discusses the importance of consumer research in product development, effective presentation, and addressing buyer objections. They also explore innovative visuals and the impact of emotional connections in marketing, ultimately revealing how visual elements can significantly enhance sales.

Dr. Ellis Whitehead, a data scientist specializing in AI, discusses the revolutionary custom large language model, Rufus, designed to enhance the shopping experience on Amazon. Oana Padurariu shares insights on optimizing product listings, emphasizing key attributes like gluten-free options. Jeffrey Anderson, a former Amazon seller, highlights challenges in advertising with Rufus, particularly regarding reporting features. All three guests explore the power of reinforcement learning, showing how Rufus continually evolves through customer feedback, dramatically improving personalized shopping.

Seller Sessions - The Man Behind the Honeymoon   In this episode of Seller Sessions, Danny McMillan welcomes Anthony Lee, the innovator behind the term "honeymoon period" in the world of Amazon FBA. Anthony dives into the history of this ranking strategy, clarifying misconceptions and discussing its evolution, while touching on advanced topics related to Amazon algorithms and the role of AI in e-commerce.   The Honeymoon Period Debunked Anthony discusses the origins of the "honeymoon period," a concept he coined around 2015 when data showed unusual ranking activity in Amazon listings around the six-month mark. Initially, it appeared that there was a grace period where rank was closely tied to sales history, leading to faster ranking boosts for new products. However, over the years, as Amazon’s algorithms shifted towards keyword relevance, this phenomenon became outdated. Today, relying on the honeymoon period as a ranking strategy can be risky, as Amazon’s focus is now on more sophisticated factors such as relevance and real-time data.   Understanding Amazon's Cold Start Anthony explains how Amazon's "cold start" period, originally lasting up to seven days, has shortened dramatically. This cold start phase allows the algorithm to gather enough data on a product to understand its relevance, but it is no longer something sellers can easily game. He emphasizes that many outdated strategies, such as manipulating sales velocity during this time, no longer yield the results they once did.   The Importance of Attributes and AI The conversation highlights how attributes—both front-end (keywords, titles) and back-end (image metadata, product details)—are becoming critical to Amazon's ranking engine. Anthony reveals how tools like Amazon's AI-powered Recognition and Comprehend can analyze product images and listings to assess relevancy and performance. Sellers should optimize both their text and images to align with Amazon's ever-evolving search algorithms. Anthony also hints at the future of e-commerce with AI, as more sophisticated machine learning models like Cosmo and AtroBERT help Amazon improve relevance in real-time searches.     Moving Away from Gimmicks Both Danny and Anthony criticize outdated methods like reissuing ASINs to reset rankings or over-relying on past strategies that don’t align with Amazon’s current approach. Instead, they advocate for a focus on product quality and data-driven decisions. As margins become tighter, leveraging tools and understanding Amazon's new algorithmic systems—like knowledge graphs and semantic models—become crucial to winning in a competitive marketplace.   Conclusion Anthony Lee urges sellers to focus on building strong, high-quality products and adopt a data-driven approach to launches, rather than relying on outdated tricks. As Amazon continues to refine its search algorithms, it's essential to stay ahead of the curve by embracing new technologies and methodologies, including AI tools for product optimization.

Product Titles & Descriptions - How Amazon Plan To Take Control   In this episode of Sellers Sessions, Max Sinclair discusses major shifts for sellers, focusing on AI-driven personalization and its impact in the coming months.   Key Topics: Personalized Product Descriptions Amazon will now dynamically change product titles and descriptions to fit individual customer searches. For instance, if a user searches for “gluten-free cereal,” Amazon’s AI may push that keyword to the front of a title. This shift takes some control away from sellers, raising concerns about SEO and content optimization.   Challenges for Sellers Sellers may struggle with these automatic adjustments, as AI-driven changes could remove or rephrase important keywords. While this may feel disruptive, Max suggests that Amazon is implementing these changes because they work better for customers... Only time will tell!   AI-Generated Bullet Points Amazon is also using AI to suggest more concise and standardized product bullets. While these edits aim to create consistency, they don’t necessarily focus on increasing conversion rates, which has caused frustration among sellers.   Future of AI Agents Amazon is rolling out AI assistants like Amelia, which will help sellers with tasks like tracking metrics and escalating support issues. Max believes that, while these AI tools are still in development, they will soon become powerful resources.   The MCM Model Max introduces MCM (Multitask Pre-trained Customer Model), a new AI designed to enhance product recommendations. He predicts it will soon become essential for sellers to understand how it works.   Looking for a Free PPC Audit? Visit https://www.databrill.com

Danny and Oana return for part two. In this episode, Danny goes more in-depth on Fig. 5 of the patent; this time on how it impacts external traffic and how the system punishes giveaways. Mastering the Cold-Start System and Beyond In this episode, we focus on the other areas cold-start system and how to position new products for long-term success. We explore key strategies for overcoming the challenges of launching a product without historical user data, including the importance of attributes and machine learning to generate early traction (and impact of AI for matching etc). Why Giveaways Always Drop Off Giveaways can give an initial boost in rankings, but they often lead to a drop-off once the influx of free traffic ends. We discuss why this happens and the pitfalls of relying too heavily on giveaways, which can create unsustainable patterns that hurt your long-term performance. External Traffic: The Double-Edged Sword External traffic can boost rankings and visibility, but it can also harm your performance if it brings low-converting visitors. We break down: How good external traffic can help with ranking. Why poor traffic with low conversions can negatively impact your visibility. Best practices for generating high-quality, targeted external traffic that supports long-term growth. Conclusion Effectively managing the cold-start phase, avoiding the trap of unsustainable giveaways, and understanding the impact of external traffic are critical to maintaining strong rankings. By applying these strategies, you’ll boost performance, increase conversions, and avoid common pitfalls in e-commerce ranking systems. We also cover Gaslighting Ranking and tips on how to avoid it while Oana gives insights on the advertising part of the article. We discuss what is required for a strong ranking strategy relating that to the patents and what main approach to take when launching on Amazon.   Follow Along on Youtube

Main Image Monthly - Image Teardowns for Better Conversion   Welcome to our monthly show on all things images and conversion, where we bring in some of the world's best Amazon conversion optimizers.   Each month, we will take an ASIN and run tests using all our technology, then bring it back to the table and break down our findings. Showing you how easy it is to test, how to test properly, and how to use your imagination.   "The magic you are looking for is in the work you are avoiding."   Your Takedown Team Sim Mahon (8-figure Seller) Andri Sadlak (ProductPinion / 8-figure Seller) Matt Kostan (ProductPinion, Multiple 7-figure brands) Adam Heist (7-figure Seller and Multiple Brands)   About Our Guest Panelists Sim Mahon runs an eight-figure business with six private label brands spanning various categories. Over the past eight years, he has navigated the highs and lows of eCommerce, from eBay to Amazon, and from Vendor Central to Seller Central. His journey has equipped him with a wealth of experience and insight into the dynamic world of Amazon.   Adam "Heist" Runquist is an experienced Amazon seller who grew an outdoor products brand from 8 to 9 figures. He now owns, invests in, and advises Amazon native brands, hosts a YouTube channel (and a monthly co host on Seller Sessions) for Amazon sellers, and serves as an investor and advisor to D1 Brands. Known for his expertise in the Amazon marketplace, Adam guides new and established sellers towards growth and success.   Matt Kostan (ProductPinion, Multiple 7-figure brands) has over a decade of experience in selling on Amazon, Kickstarter, and retail. He has built multiple seven-figure brands from the ground up. At ProductPinion, Matt leads a team dedicated to helping Amazon sellers grow their sales through real consumer insights from hundreds of thousands of shoppers.   Andri Sadlak (ProductPinion / 8-figure Seller) is not a serial killer but a serial immigrant and entrepreneur. Now running an eight-figure brand, Andri started his journey by launching his first FBA business in 2017 and selling it three years later before co-founding ProductPinion, a leading conversion optimization tool for Amazon sellers.

The Advanced Series Part 2   Rekognition - For Advanced Users   Jeffery Anderson is back, taking us into the lab and sharing insights from one of the sharpest minds in the industry.   In 2021, he sold his business and has now invested in a tea company. Jeffery excels in creating technical processes for big sellers and agencies and offers software training. He also operates a training and recruitment center in the Philippines focused on software skills.   What's getting covered this week in the lab? Pre-purchase questions discovered by Rufus Post-purchase objections using AI and reviews Real customer video walkthrough using ProductOpinion Creative brief for graphic designers Amazon Rekognition (super advanced level) Amazon listing generator (surprise results) and the downfall of trusting Amazon Rekognition   We're committed to transparency, showing you the creation process live, without holding anything back. Stay tuned for a series that promises to deliver actionable content and resources by its end.   Follow along on Youtube

The Cold Reality of the Honeymoon Period & External Traffic Part 1   Now let's get to the fun part. Who hasn't heard of the Honeymoon Period?   Follow along via video   Everyone in the Amazon industry has heard about the so-called "Honeymoon Period," and after years of crafting strategies around an observation (by Anthony Lee in 2015, which he himself, as a very smart man, denounced using scientific literature), it is time for us to try to get closer to the truth.   And that is why in the article, you will find references to 15 scientific papers and 2 patents on the A9 Algorithm - the one from 2022 and the updated one from November 2023.   Before anyone starts getting concerned about the latest patent update being from almost a year ago, know that semantic matching, BERT, and COSMO will be presented in the article (and Danny's video). The reason is simple: we have the baseline, and what gets added are layers. You will see how the move Using LLMs for processing data and updating rankings in (close to) real-time matches perfectly with the COSMO framework and what RUFUS is currently doing with the results.   The scope of the video is to allow you to peek at what is coming and what will be presented in the article, as we will be working around the technical details of what really works when you launch a product on Amazon and what the myths are surrounding the Honeymoon Period phenomenon.   30-60 day grace period where Oana goes in-depth in this article (I will also cover 7-14 days) Getting the Honeymoon Period every time Resetting the Honeymoon Period (with the ASIN deletion) Having a bad honeymoon period   The point of this is to focus your time and attention on what matters versus theories without scientific data to back them up.   In the video, there is only a short intro showing one of the figures presented in the patent; it focuses on the specific moment when a product appears for the first time in search. This image is from the 2023 patent; however, in the article, you will find an in-depth description and comparison between the 2022 and the 2023 algorithm updates as Amazon introduced a more sophisticated method of refining and displaying search results. That will allow you to understand what changed from 2022 to 2023 when it comes to launching products on Amazon and not only that but also ranking and gaining visibility for already established products. The article is the result of many hours of work and recording, going back and forth. As we want to ensure it is easy to read for everyone, technical details are included since we are quoting and writing from scientific literature. But do not worry; there are a couple of things everyone needs to understand that will make things easier without delving into the technical details of how the algorithm works.   These are: Prior Predictions Posterior Predictions Prior Predictions using the Bayesian formula Learn these, and you will understand ranking on a whole new level.   Follow along via video

Ranking in Real Time Part 3 In this episode of Ranking in Realtime, Colin Raja returns for part 3 of the series, focusing exclusively on finding highly converting keywords. Using past PPC performance data alongside tools like Datadive, Brand Analytics, and SellerSprite, Colin shares strategies for optimizing keyword selection to enhance campaign effectiveness for launching.   Key Focus Areas: PPC Performance Review: Analyzing historical data to identify top-converting keywords for launches and relaunches.   Tool Utilization: How to leverage Datadive, Brand Analytics, and SellerSprite to uncover new keyword opportunities and improve search visibility. Conclusion   By analyzing PPC data and utilizing powerful tools, sellers can identify high-impact keywords, enhance visibility, and boost sales on Amazon.   Missed Part 2? Colin explored advanced Amazon strategies, including category optimization, competitive analysis, semantic mapping, NLP models, and Amazon Recognition to enhance listings and predict user behavior. He also covered phased PPC strategies to refine keyword focus over time.   Check out Episode 1 to start from the beginning and learn more about ranking strategies on Amazon!   Looking for a Free PPC Audit? Visit Databrill.

Ranking in Real Time: Part 2   Semantic Mapping, Node Leveraging & More...   In this episode, Colin Raga returns to delve deeper into advanced Amazon strategies, focusing on category optimization, competitive analysis, and semantic mapping.   Colin begins with category optimization, emphasizing the value of cross-category opportunities. Next, Colin discusses competitive analysis. He highlights the importance of comprehensively listing competitors' product types and identifying gaps where you can differentiate your offering.   The episode also introduces advanced tools like semantic keyword mapping, NLP models, and Amazon Recognition. These tools help refine your listing by identifying related keywords, predicting user search behavior, and optimizing product images.   Colin wraps up by stressing the importance of a phased PPC strategy, starting with broad campaigns to gather data and refining them over time to focus on high-performing keywords. Looking for a Free PPC Audit? https://www.databrill.com/