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:  

1. Sales Deduplication Knowledge: A solid understanding of deduplicating sales between DSP and PPC, often through merchant tokens, which ensure accurate attribution.
2. Customized Campaign Strategy: Effective DSP managers tailor retargeting windows and budgets based on product price points and sales cycles, avoiding generic settings.
3. 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/

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! 

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

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

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.

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.

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.

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.

 

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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.