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Advanced Ranking on Amazon in Q4: Garfield Coore In this episode of Seller Sessions, Danny McMillan welcomes back Garfield Coore, a top-ranking strategist, to break down Amazon’s algorithm. Garfield shares insights for sellers to maximize organic rank, external traffic, and achieve ranking stability as Q4 peaks., Garfield shares essential techniques for sellers looking to stay competitive and profitable. Key Takeaways The Three-Stage Ranking System: Primary Ranking Events: Roughly 90% of ranking impact comes from core behaviours on Amazon. Key actions include searches leading to a product page, add-to-cart from a search click, and purchases from a search pathway. Garfield stresses avoiding variations that interrupt the ranking pathway. Keyword Cohorts: Leveraging keyword "families" (using Amazon’s Opportunity Explorer) helps products gain ranking bleed-over. Start ranking with smaller keywords, allowing spillover to higher competition terms. Territorial Influence: Minor ranking factors include BSR and inventory location, affecting regional rank. BSR reflects category sales ranking relative to competitors. Conversion Events Beyond Sales Clicks, page visits, and add-to-cart actions all serve as ranking events, which Garfield calls “conversion events.” Focus on generating quality traffic to accumulate these events, which can boost rank without immediate sales. PPC Strategy: Maximizing Click-Through Rate PPC placement relies on expected revenue from clicks, not relevance. Garfield explains that a history of clicks improves PPC placement probability. Timing Event-Driven Ranking Garfield advises starting campaigns for seasonal events early to establish a low-cost rank before high-demand periods. For example, healthcare and weight loss products should begin ranking efforts before New Year’s resolutions in January.
Reach Garfield - https://www.facebook.com/garfield.coore
Out Now on SellerSessions.com The Cold Reality of the Honeymoon Period And External Traffic 👉 https://sellersessions.com/the-cold-reality-of-the-honeymoon-period-and-external-traffic/ If you have problems with the links, check the link in our bio! Engage with us! Your opinion matters! Drop us a comment 📣 and join the conversation. Remember, sharing is caring—so hit the like button 👍❤️, give us some love, or share this post with someone you think will enjoy it! 🔄 Seller Sessions Live, 2025 Grab tickets now https://sellersessions.com/seller-sessions-live-2025/ Watch this podcast in its full glory Out now on YouTube - https://www.youtube.com/@SellerSessions -
Advanced: Master Amazon Ranking: Bite-Sized Insights from the Whiteboard Episode Summary
In this episode of Seller Sessions, hosts Dan and Oana take a deep dive into Amazon's ranking mechanism, focusing on the Bayesian update process and its impact on product visibility. Inspired by their previous series on the complexities of the "cold start," Dan and Oana aim to simplify the algorithm’s operations, allowing sellers to apply these insights to common Amazon business challenges, from managing stockouts to ASIN resets.
The Bayesian update plays a crucial role in Amazon's ranking formula, guiding the platform's initial "guess" for each new product’s rank and continuously refining it as user interaction data accrues. They explain the difference between prior and posterior predictions:
Initial Prior Prediction: When a new product launches, Amazon evaluates similar products based on shared attributes and performance data, assigning a starting rank that’s essentially a best guess. Posterior Prediction: As users engage with the product (clicks, scrolls, purchases), this real-time behavior helps Amazon fine-tune its ranking, transitioning from a speculative ranking to a data-informed position.The duo also references two pivotal Amazon patents from 2022 and 2023, which document how real-time interaction data (e.g., clicks and conversions) informs ranking recalculations every 2-24 hours, depending on available data. This Bayesian cycle is fundamental to Amazon's dynamic ranking shifts, especially in crowded categories where initial guesses are quickly updated with interaction-driven insights.
Key Takeaways The Role of Bayesian Updates: Sellers learn how the Bayesian update transforms initial ranking predictions by integrating real-time user data, continuously recalculating product rankings. Exploration vs. Exploitation: Amazon prioritizes real user data over hypothetical scenarios, relying on actual behavior to shape ranking results. New Products vs. Returning Products: Newly listed items start from scratch, but if a product goes out of stock and returns, it resumes with past data, allowing quicker integration of new engagement data. Ranking Frequency: Ranking updates may occur every 2-24 hours, creating a near-real-time feedback loop that adjusts based on ongoing user interactions.Dan and Oana emphasize that traditional concepts like the "honeymoon period" are less relevant due to Amazon’s continuous ranking adjustments. As technology advances, rankings are now recalculated frequently, meaning sellers should focus more on engagement metrics than waiting for prolonged ranking boosts.
This episode demystifies complex Bayesian methods in Amazon’s ranking algorithm, offering insights that will help sellers understand how to strategically navigate the platform’s data-driven system.
Out Now on SellerSessions.com - "The Cold Reality Of The Honeymoon Period And External Traffic"
https://sellersessions.com/the-cold-reality-of-the-honeymoon-period-and-external-traffic/
If you have problems with the links, check the link in our bio!
Your opinion matters! Drop us a comment 📣 and join the conversation. Remember, sharing is caring—so hit the like button 👍❤️, give us some love, or share this post with someone you think will enjoy it! 🔄
Seller Sessions Live, 2025. Grab tickets now: https://sellersessions.com/seller-sessions-live-2025/
Watch this podcast in its full glory. Out now on YouTube - https://www.youtube.com/@SellerSessions
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Building a Full-Funnel DSP Strategy For Amazon Sellers Danny welcomes Sam Lee, an Amazon DSP expert with years of experience at companies like Thrasio. Sam provides insights into the Amazon DSP (Demand Side Platform), a less accessible yet powerful tool compared to Amazon’s PPC. DSP allows for advanced targeting using Amazon’s first-party data, perfect for those ready to expand beyond traditional ad methods. Danny and Sam dive into the essentials of DSP, covering campaign structures, targeting methods, and common pitfalls that many brands face when venturing into DSP. What is Amazon DSP? Sam explains that Amazon DSP is different from traditional Amazon PPC in accessibility and functionality: Barrier to Entry: DSP isn’t as easy to access as Seller Central; it requires Amazon-approved agencies or meeting certain spend thresholds. Initial Challenges: Early misuse led to its reputation issues, as many advertisers applied blanket strategies, not optimizing DSP for unique brand/product needs. Building the Full Funnel Sam emphasizes a strategic approach to DSP that adapts to product price points and buying cycles, avoiding a one-size-fits-all approach: Understanding Customer Journey: Higher-priced products require longer consideration windows, so retargeting timelines should vary. Tailoring Campaigns by Product Type: A $10 product doesn’t need a 30-day retargeting window, while a $200 product may need up to 45 days to properly engage the audience. Key Metrics for Success in DSP To evaluate DSP campaign effectiveness, Sam discusses focusing on core metrics: Return on Ad Spend (ROAS) and Total ROAS as primary performance indicators. Effective Cost Per Detail Page View: Lower costs (below $1) signal efficient DSP campaigns, with top performers achieving $0.50 or less. Percent of Purchases New-to-Brand: Indicates how well DSP attracts fresh customers, avoiding retargeting those already inclined to purchase. Sam highlights Amazon Marketing Cloud (AMC) as a tool to monitor customer touchpoints in the purchase path, offering more transparency into DSP’s role in converting new users. DSP Budgeting Insights One misconception Sam dispels is that DSP requires excessive budgets to yield results: Optimal Spend Range: While larger budgets provide more data for refinement, DSP can still be tested effectively at lower levels if PPC campaigns are fully maximized first. Synergy Between PPC and DSP: He advises investing as much as possible into PPC until returns diminish, then strategically layering DSP to further boost conversions. Evaluating DSP Managers When hiring or assessing a DSP manager, Sam recommends looking for these critical skills: Sales Deduplication Knowledge: A solid understanding of deduplicating sales between DSP and PPC, often through merchant tokens, which ensure accurate attribution. Customized Campaign Strategy: Effective DSP managers tailor retargeting windows and budgets based on product price points and sales cycles, avoiding generic settings. Expertise with Streaming and Video Ads: Familiarity with OLV (Online Video) and Streaming TV (OTT) can add value to campaigns, especially for brand awareness. Streaming TV and Online Video (OLV) Advertising Sam and Danny discuss the advantages of Streaming TV (OTT) and Online Video (OLV) as part of DSP’s offerings: OTT vs. OLV: OTT, or Over-the-Top Media, is a more premium option, placing ads on streaming platforms like Hulu and Prime Video, while OLV covers a broader online space (e.g., ads between games or online content). Use Cases: Streaming ads are highly effective for certain brands but come with higher costs, while OLV offers a budget-friendly alternative for brands targeting broader, online-savvy audiences. DSP for Non-Amazon Sellers One of the most forward-thinking DSP strategies involves leveraging Amazon’s first-party data for external brands: Application for Non-Amazon Sellers: Brands not selling on Amazon, like car companies or public services, can still use DSP to target potential customers based on Amazon’s deep data insights. Geotargeting and Demographics: For example, public transit services like LA Metro have used DSP to target specific areas, showing the versatile applications of DSP data. The Role of DSP in Amazon’s Search and Ranking Algorithm Sam shares advanced insights on how DSP impacts Amazon’s ranking system through behavioral targeting: Bayesian Update System: Amazon’s algorithm adapts based on live data (clicks, conversions), helping high-performing products “win” visibility quickly while demoting less successful items. Behavior-Driven Launch Strategy: For launches, a well-optimized DSP campaign can create significant early traction, contributing to better search rankings. Common Pitfalls and Misconceptions in DSP Sam addresses frequent DSP errors that agencies and brands make: Misleading Attribution: Lack of merchant tokens can lead to inflated success metrics, misleading clients on actual DSP effectiveness. Uniform Strategy Application: Applying the same retargeting window or budget across all campaigns, regardless of product type or target audience, can dilute DSP’s impact. Amazon as a Search Engine First Both Sam and Danny agree that Amazon’s primary goal is search relevancy, driven by conversion rates and user experience: SEO Principles on Amazon: Amazon prioritizes high-conversion products to ensure users find relevant, desirable items. Successful DSP campaigns enhance this by generating high-quality traffic. Cold Start Problem: New products face Amazon’s cold-start challenges, where initial performance metrics determine future visibility. DSP’s behavioral targeting can boost early sales velocity, easing this process. Closing Thoughts Danny and Sam conclude by reinforcing Amazon’s profit-centric nature, encouraging sellers to align with Amazon’s goals to maximize DSP benefits. For sellers looking to experiment with DSP, Sam advises working with knowledgeable agencies or managers to avoid wasted spend and achieve incremental gains over PPC alone. Reach Out to Sam Lee: Company: Trivium Co. Contact: [email protected] Looking for a Free PPC Audit? https://www.databrill.com/
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Real-World AI For Amazon Sellers : How We Use It to Drive Business Success Introduction Ritu Java is the CEO and Co-founder of PPC Ninja, a company that offers Amazon PPC Software to agencies and brands, along with PPC Management Services. She leads a team that manages Amazon Sponsored and DSP Advertising for sellers with 6, 7, and 8-figure revenues. With over a decade of experience in eCommerce, Ritu has guided hundreds of Amazon sellers through the complexities of Amazon Advertising. AI for E-Commerce Ritu also runs the AI for E-Commerce Newsletter, which has been active for 18 weeks and has 1,900 subscribers. Out Now on SellerSessions.com: The Cold Reality Of The Honeymoon Period And External Traffic If you have problems with the links, check the link in our bio! Your opinion matters! Drop us a comment and join the conversation. Remember, sharing is caring—so hit the like button , give us some love, or share this post with someone you think will enjoy it!
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Testing 100 Amazon Product Listings with Rufus: My Findings Capabilities of Rufus on a Product Detail Page with Andrew In this episode, Andrew, a former Director of Amazon for Touch of Class and current Amazon Lead for the National Fire Protection Association, dives into the powerful features of Rufus and how it transforms the way customers interact with product detail pages. Andrew's Background: Former Director of Amazon for a luxury home brand, Touch of Class (8 eight figure brand) Created top-rated Amazon Custom GPTs Amazon Lead at the National Fire Protection Association Self-taught in SEO, SGE, and Generative AI applications Holds a black belt in traditional Taekwondo and enjoys pickleball Rufus' Core Capability: Text Retrieval Rufus uses Optical Character Recognition (OCR) to extract text from product information, customer reviews, and visuals. This technology allows for a comprehensive data analysis that can enhance the accuracy of product details and reviews. Rufus in Action: Extracts relevant insights from text, images, and customer feedback Moves beyond basic search terms, offering a more intuitive search experience for users Delivers highly relevant product information by utilizing advanced AI techniques Conclusion: Andrew explains how Rufus represents the future of product search and engagement, making customer interactions with product detail pages more insightful, efficient, and responsive to user needs. Watch the full Version on Youtube
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Bayesain Updates - Changing the Game of Ranking In this episode of Seller Sessions, Danny and Oana unveil their latest collaborative article, which delves into Amazon's patents and algorithms, particularly focusing on the evolution from 2022 to 2023. This monumental piece—over 10,000 words—aims to be the most extensive public resource on Amazon's A9 algorithm, tracking its history and impact. Article Origins and Team Effort -Danny and Oana teamed up for several papers, each expanding in scope. Their latest collaboration incorporates insights from two patents and 15-16 additional scientific papers. -The goal: Analyze the algorithm changes between 2022 and 2023, highlighting key differences and their implications for sellers. Key Themes Covered -BERT, Cosmo, and External Traffic: Deep dive into these technologies and how they impact ranking, visibility, and traffic management. -Sales Velocity and Cold Start Mechanisms: The duo explores how Amazon’s cold start problem has evolved, driven by Bayesian updates and machine learning. -Honeymoon Period Myth: A thorough debunking of the concept, explaining why it no longer holds true after algorithm changes in 2022. Data-Driven Approach This project digs into how Amazon now processes data, with updates to ranking and product visibility happening every 2-24 hours. The emphasis is on personalization, driven by Amazon’s focus on conversion likelihood, making an optimized launch strategy critical. Amazon’s Shift Towards Personalization -Amazon’s increasing focus on tailored customer experiences, from personalized search results to dynamically adjusted product titles. -Concerns about how machine learning models, like Cosmo and Rufus, will continue to evolve and potentially override manual optimizations sellers make. Tune in to gain the edge on launching your products and mastering Amazon's constantly evolving system. READ THE ARTICLE HERE
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Building a Brand from Scratch Why Nafiseh Razavi Is the Face of Her Growing Brand In this episode of Seller Sessions, we explore a fresh approach to selling with guest Nafiseh Razavi, founder of StudyKey, an educational tool for language learners. Key Takeaways: StudyKey is a compact educational tool aimed at helping language learners study away from digital distractions. Nafiseh’s journey is pretty unique because she is both the creator and the face of her brand (most sellers prefer to stay in the background) , promoting a personal connection with her customers. She emphasizes how being hands-on has helped her keep costs down while also ensuring that the product is represented exactly as she envisions. Building a Brand from Scratch: The motivation behind StudyKey came from Nafiseh’s personal experience learning Spanish and recognizing what was missing in her own language learning journey. This insight shaped the product, which is designed to reduce screen time and encourage outdoor studying. Challenges & Strategies: Financial constraints led Nafiseh to take charge of her social media and content creation, ensuring authentic brand representation. She discusses the importance of balancing quality with quantity in social media posts, preferring a hands-on approach to engaging with her audience. Product Promotion & Social Media: Nafiseh shares her process for creating content, using real-life scenarios to integrate her product naturally into daily activities. She emphasizes consistency in posting, aiming for daily content while focusing on quality over volume. Advice for Aspiring Entrepreneurs: For those looking to take a similar approach, Nafiseh advises stepping out of your comfort zone and embracing the role of being the face of your brand. She highlights the importance of persistence, learning from mistakes, and continuing to improve with every step. Future Plans: Nafiseh is focused on scaling her brand, expanding beyond Amazon, and creating more products to support her community of language learners.
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Amazon Sellers: Boost Conversions with Main Image Strategies – Part 3 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. This month, we work on a SnoozeShade Stroller Cover, innovated and decorated by brand owner Cara Sayer. Your Takedown Team Sim Mahon (8-figure Seller) Matt Kostan (ProductPinion, Multiple 7-figure brands) Peter-Paul Maan (Intellivy) 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 e-commerce, 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. Matt Kostan (ProductPinion, multiple seven-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 k*ller 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. Peter-Paul Maan is the Head of Sales and Partnerships at Intellivy. Peter-Paul stands at the forefront of e-commerce, transforming sales into journeys. His approach ensures products are perfectly aligned with consumer desires, leading to successful launches and satisfied customers. He is the go-to expert for those aiming to master their Amazon strategy and authentically connect with their audience.
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The Science Behind RUFUS - Expert Insights on Amazon's AI Gamechanger The Science Behind RUFUS Rufus Revealed: Expert Insights on Amazon's AI Gamechanger On this episode, we do a roundtable featuring Dr. Ellis Whitehead, who used artificial intelligence to enable laboratory robots to autonomously run and analyze scientific experiments before AI was a buzzword. Oana Padurariu, who is the Head of Amazon at Trivium, is also featured. Her stock is rising as she drops groundbreaking knowledge around the science of ranking and is a rising star in the Amazon community. Jeffrey Anderson already has an exit under his belt and is in high demand with software companies and agencies for his technical genius. Rufus Revealed: Expert Insights on Amazon's AI Gamechanger Key Points Custom Large Language Model (LLM): Rufus uses a custom-built LLM trained with specific shopping data, including the entire Amazon catalog, customer reviews, and community Q&A posts, providing tailored answers to shoppers. Retrieval-Augmented Generation (RAG): Rufus goes beyond its training data, pulling relevant information from reliable sources like customer reviews, product catalogs, and API data to generate accurate and helpful responses. Reinforcement Learning: Rufus improves over time by learning from customer feedback, constantly enhancing its ability to provide useful shopping advice . AWS Infrastructure and AI Chips: Amazon's custom AI chips, Trainium and Inferentia, enable Rufus to provide real-time responses at scale, with minimal latency, even during peak shopping hours. Streaming Architecture: Rufus provides real-time, token-by-token responses, ensuring that shoppers don’t experience delays while interacting with the AI assistant. About Jefferey Jeffery Anderson. He sold his business in 2021 and recently invested in a tea company. Jeffery's expertise lies in technical processes tailored for large sellers and agencies, along with providing software training. About Oana Oana Padurariu is the Head of Amazon at Trivium, an advertising whiz with a flair for SEO and PPC. From political science dreams to Amazon mastery, she's led brands across the US and EU to success. Now, she channels her passion for the Amazon puzzle into leading her team to innovate and excel in the competitive e-commerce space. About Dr Ellis A Data Scientist and Algorithm Expert.Ellis has a proven track record in his ability to solve complex problems and turn them into simple solutions through software engineering, mathematics, and data science. He has been deeply involved in the success of the groundbreaking Amazon software tool, Jungle Scout. Ellis became inspired to solve these complex problems after completing his PhD in applied artificial intelligence to enable laboratory robots to autonomously run and analyze scientific experiments.
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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.
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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
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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
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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.
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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
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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
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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.
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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/
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Fraser Smeaton: The $50M Amazon Success Story From Losing to Winning Early Years and Career Beginnings Fraser Smeaton’s journey began in the field of Electrical Engineering at university, but his career soon shifted to the corporate world. He spent eight years working in Marketing and General Management roles, where he gained invaluable experience in business strategy and market dynamics. From Side Hustle to Full-Time Entrepreneur In 2009, Fraser started a side hustle that quickly grew into a full-time business. The venture gained rapid traction, going viral within its first year, which led Fraser to leave his corporate job to focus entirely on his new business. Initially, the business was promoted through its website, heavily supported by Facebook advertising, which drove significant growth in the early years. Expansion and Early Challenges As the business grew, Fraser expanded into wholesaling, including becoming an Amazon vendor. This period of expansion, which lasted until 2012, was marked by rapid growth. However, the company soon faced the challenges that come with scaling up. As competition increased and costs soared, the demand for their products began to decrease. The Low Point and Strategic Shift By 2015, Fraser's business faced over £1 million in losses, leading to a workforce reduction by half. Fraser noted that third parties sold their wholesale products on Amazon and decided to sell directly on Amazon to capture retail and wholesale margins and control sales. Refocusing on Amazon Pivoting to Amazon as the main sales channel was pivotal for the company. Success hinged on refining all Amazon-related processes—procurement, logistics, pricing, content, SEO, advertising. Fraser's belief in cumulative small improvements and launching over 150 new products each year drove substantial growth. Navigating the Pandemic The pandemic presented new challenges, particularly as the business struggled while other sectors flourished. However, Fraser’s quick action to control costs and focus on improving internal processes helped the company navigate through this difficult period. Instead of retreating, they used this time to refine operations, setting the stage for future success. Current Success and Business Moat Today, Fraser’s business generates over $50 million annually and employs more than 60 people. The company’s competitive advantage lies in its ability to manage complex operations profitably in a tough category. This expertise has allowed the business to thrive in an increasingly competitive landscape. Looking for a Free PPC Audit? https://www.databrill.com/
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Ranking in Realtime Part 1 - with Colin Raja This is a multi-part series that goes behind the scenes of ranking a product from start to finish. Colin will take you through every single step, from all the preparation to execution to the results. This is part one; we will provide weekly updates live (every Thursday) so you get to see in real time the whole process, the good, the bad, the ugly, and everything in between. Covered in this episode: Keyword Selection: Start by identifying the keywords that are most relevant to your product launch. Choose ones that are both impactful and realistic to target. Product Definition: Shape your product based on the chosen keywords. Align its features, design, and messaging with these keywords to boost visibility and market relevance. Market Gap Analysis: Look for gaps in the market by examining keywords that are less competitive and current trends. This strategy will help you differentiate your product. Pre-Design Testing: Before diving into the design phase, use tools like Canva to create preliminary mockups. This step helps you get a feel for potential AI-generated images and sets the stage for your designer. Design Process: With your mockups ready, work closely with your designer to finalize the product's design. Incorporate feedback and utilize testing tools to refine the design further. Follow along on Youtube - https://www.youtube.com/live/6CpfvwMzXCE?si=c4ta2ABo42mkisrn
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Main Image Monthly - Making Magic with Main Images Welcome to our new monthly show, where we bring in some of the world's best Amazon conversion optimizers. If you know the difference between Russell Brunson (Templates) and Peep Laja (The Godfather of Conversion Rate Optimization), then you have come to the right place. 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 (8fig Seller) Andri Sadlak(ProductPinion / 8fig Seller) Dorian Gorski (Generated over $1 billion Client in sales) Matt Kostan (ProductPinion , Multiple 7 figure 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. Dorian Gorski is a seasoned Amazon expert with over 11 years of experience, partnering with top brands and Fortune 500 companies. He has founded several creative ventures that have collectively generated over $1 billion in sales for his clients. Currently, Dorian specializes in data analysis and optimizing conversion and click-through rates. Matt Kostan (ProductPinion, Multiple 7-figure brands). With 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.
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