[ BDSN ] 🌙 No such thing as a "honeymoon" period on Amazon

🌙 NO HONEYMOON PERIOD - JUST HUSTLE: START STRONG

In a detailed article recently published by Dream 100 member Danny McMillan and Oana Padurariu, the pair explain why data shows there is no evidence to support a “honeymoon” period today for new product launches.

They explain how launching products on Amazon has undergone significant changes, largely due to advancements in AI, algorithm updates, and refined search mechanisms.

The once-prominent "honeymoon period," which sellers believed provided new products with a temporary visibility boost, is now considered a myth. Amazon's ranking system has evolved to rely on data-driven approaches from day one, without offering guaranteed boosts for new items.

Instead, it employs a system that uses prior prediction values based on similar products' historical performance to initially rank new items, and then transitions to posterior prediction values once real user data starts accumulating.

Key Shifts in Product Launches

1. Cold Start Problem: When a product first enters Amazon's system, it lacks any historical data (like clicks or purchases) that would inform the algorithm about its relevance. This is called the cold start problem.
   
   Amazon now tackles this using machine learning models that create prior predictions, giving new products some visibility based on similarities with other items.
   
   However, the real challenge comes in generating real interaction data to refine these rankings, a process known as Bayesian updating.
   

2. AI and Semantic Search: AI-driven advancements, such as the integration of semantic search models and the COSMO framework, have made the system far more sophisticated. Instead of relying purely on keyword matching, Amazon now analyzes product context and user intent.

   
   This shift means that sellers must optimize listings not just for keywords but for deeper relevance and engagement, as Amazon’s algorithm evaluates products in terms of how well they match user expectations semantically and contextually.

3. External Traffic’s Role: Unlike older methods, relying solely on Amazon's internal ranking mechanisms is no longer sufficient. Generating external traffic—through platforms like Google Ads or social media—has become crucial for building initial engagement.
   
   However, this traffic needs to be highly relevant; poorly targeted traffic can negatively impact product rankings, as Amazon’s system penalizes listings that don’t convert well from incoming traffic.
   

4. Content Optimization: High-quality content remains essential. Clear product images, compelling descriptions, and detailed specifications help increase engagement, which is vital during the cold start.
   
   Since Amazon’s system continuously updates a product’s rank based on user interactions, good content helps ensure higher conversion rates early on, making the transition from prior predictions to posterior data smoother and faster.
   

5. Continuous Learning and Real-Time Adjustments: Amazon’s ranking system is highly dynamic. The latest algorithms incorporate Bayesian updates, allowing the system to refine a product’s rank in real-time as new data emerges.
   
   This means that product visibility is not fixed; instead, it evolves based on how well the product performs in the marketplace, making constant optimization a must for sellers.

6. Seasonality and Contextual Search: Season-aware models and contextual relevance now play a more significant role in determining product rankings, especially during seasonal events.
   
   By adjusting attributes like product categories and descriptions based on emerging trends, sellers can align better with customer searches, enhancing discoverability.

Myth-Busting the Honeymoon Period

The belief in a fixed 30-day window where new products get a ranking advantage is outdated. Today, Amazon’s system does not provide a blanket visibility boost for new products.

Instead, initial ranking depends on how well a product matches with successful existing items through the prior prediction process. As real interaction data accumulates, rankings are continuously refined through Bayesian methods, ensuring that only products performing well retain visibility.

Implications for Sellers

Launching products successfully on Amazon today requires an in-depth understanding of how the platform’s algorithm functions. Sellers must focus on:

• Driving targeted traffic from both Amazon and external sources.

• Optimizing content to increase conversions and build positive user interaction data.

• Leveraging advanced AI-driven tools to understand and align with Amazon's evolving search mechanisms.

• Understanding that continuous testing and optimization is key as the system adapts to real-time data.

The landscape of Amazon product launches has become more competitive and sophisticated, demanding a combination of data-driven strategies, AI integration, and precise traffic targeting for long-term success.

🪐 THERE’S NO SUCH THING as a COSMO AI ALGORITHM

Kevin Dolan is a leading expert in the field of AI and e-commerce, particularly known for his work with Pacvue AI Labs, where he focuses on the intersection of artificial intelligence and online marketplaces like Amazon.

He has an extensive background in reading and analyzing Amazon's scientific papers, which makes him one of the most knowledgeable individuals when it comes to understanding Amazon's AI initiatives and their potential impact on sellers.

Dolan has been closely studying the evolution of AI technologies from their conceptual roots in the 1980s to their modern-day applications, especially after the advent of transformer models around 2019, which have revolutionized fields like natural language processing.

His in-depth knowledge comes from reading a vast number of Amazon's scientific papers, particularly those published under Amazon Science. He tracks Amazon’s AI advancements, which have been accelerating rapidly, especially over the last few years

According to Dolan, Amazon's research output increased significantly around 2021-2022, with a surge in published papers about AI, semantic search, and customer interaction models.

These papers reveal Amazon's commitment to improving the customer experience through AI, which he describes as becoming more sophisticated, especially with tools like Rufus, COSMO, and Project Amelia.

His insights are grounded in this meticulous review of Amazon's internal research and his professional expertise in the field of AI.

As Amazon integrates more AI tools into its ecosystem, sellers need to understand how these advancements affect their business, without falling prey to myths or unnecessary fears.

Here are some insights he shared in a recent Serious Sellers Podcast:

1. Amazon’s AI Initiatives:

   • Amazon has been investing heavily in AI tools and research, including projects like Rufus and COSMO, aimed at enhancing search results and customer interactions.

   • Rufus, Amazon’s AI assistant, helps improve search by answering customer questions and refining search intent. However, it’s still in early stages and isn’t revolutionary yet.

   • COSMO focuses on semantic search, understanding the deeper meaning behind customer queries and product listings, not just exact keywords. This means Amazon’s search algorithms are evolving to connect products with customers based on the product's use and customer needs.

2. Myth: You Need to Drastically Change Your Listings:

   • Sellers don’t need to overhaul their listings to adapt to AI. The best practices remain the same: focus on clear, accurate descriptions of your products, addressing specific customer pain points.

   • While AI can help surface relevant products even without exact keywords, well-optimized listings that highlight key benefits and use cases still perform best.

   • Keyword stuffing (cramming a listing with every possible keyword) is outdated. Instead, focusing on natural language that addresses how your product solves customer problems aligns well with AI-driven search enhancements.

3. AI Tools for Sellers:

   • Amazon is rolling out more AI-driven tools to help sellers, like Project Amelia, an AI chatbot in Seller Central, aimed at simplifying seller tasks. While promising, it’s not yet clear how game-changing it will be for day-to-day seller operations.

   • Sellers can also use third-party tools like Helium 10 to leverage AI for more efficient keyword filtering and PPC campaign management. AI helps automate tasks like creating ad campaigns or refining keywords, reducing manual workload.

4. The Role of Reviews and Customer Data:

   • AI tools like COSMO can pull insights from customer reviews to help Amazon better understand product use cases (e.g., pregnant women benefiting from certain shoes). However, it’s still crucial for sellers to actively monitor reviews and update listings with relevant information.

5. Dispelling Falsehoods:

   • There’s no need for sellers to panic or make drastic changes. Claims that sellers need to “completely revamp” their keyword strategy due to AI are overblown. AI might help some under-optimized listings perform better, but sellers following best practices will remain competitive.

   • As AI tools evolve, they might make it easier for sellers to optimize and understand customer behavior, but successful strategies remain focused on accurate product descriptions, customer-centric content, and well-rounded listings.

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🗣️ 12 TED TALKS to TEACH YOU MARKETING PSYCHOLOGY

In a recent LinkedIn post, Jon Brosio emphasizes the power of mastering psychology for sales success and recommends 12 TED Talks that can teach you more about psychology than a four-year college degree.

Here's a summary of each:

1. Seth Godin - How to Get Your Ideas to Spread: Learn why extraordinary, bizarre ideas succeed and how to capture attention.

2. Derek Sivers - How to Start a Movement: Understand the psychology of movements and how to incite action.

3. Carol Dweck - The Power of Believing That You Can Improve: Explore the science of the "growth mindset" and its transformative potential.

4. Barry Schwartz - The Paradox of Choice: Learn how fewer choices lead to happiness and more rational decision-making.

5. Rory Sutherland - Life Lessons From an Ad Man: Uncover the psychology behind advertising and how perception shapes success.

6. Dan Ariely - What Makes Us Feel Good About Our Work?: Discover why feeling appreciated and making progress fosters meaningful work.

7. Simon Sinek - How Great Leaders Inspire Action: Learn how great leaders inspire by focusing on the "why" behind their cause.

8. Philip Zimbardo - The Psychology of Time: Explore the role of delayed gratification and "time perspective" in achieving success.

9. Daniel Goleman - Why Aren't We More Compassionate?: Understand the importance of emotional intelligence and compassion in business.

10. Mihaly Csikszentmihalyi - Flow, the Secret to Happiness: Discover how the psychology of flow and creativity leads to happiness and fulfillment.

11. Manoush Zomorodi - How Boredom Can Lead to Your Most Brilliant Ideas: Learn how boredom sparks creativity, especially in marketing.

12. Nadja Yousif - Why You Should Treat the Tech You Use at Work Like a Colleague: Gain insights on leveraging and humanizing tech in the workplace

⚒️ 3 COMPLEMENTARY TOOLS to HELP YOU CRUSH IT

In the October 7 edition of BDSN, I emphasized how important it is to add meta data to your images, not just alt text. You can use Photoshop (a paid tool for professionals) or Canva, but there is also a non-paid tool that can do it too.

It’s called Photopea, and it works similar to Photoshop online, but without needing to pay.

Just drag your photo in, then go to => File and click on the box in the lower left to choose which fields to add. I suggest adding Title, Image Description and Keywords at a minimum.

Once you add the fields, fill them in with your a data and save the file. Use this image file for all your uploads to Amazon, Walmart, Shopify, etc. Google, Amazon and many of the AI tools will read and index the data in your images.

But don’t stop there. You should also optimize your images for faster load times to boost search ranking in some cases, as well as reduce the weight in emails to help bypass spam and junk filters by using a tool like Tinify (also no charge).

If you are sending emails to your Amazon customers, be sure to do both steps above first, then send a test email before you do the large email blast in Weber., MailChimp etc. to another complementary tool called Mail Tester to check your spammyness and modify accordingly before sending to get better results from your promotion.

✌🏼 See you again on Thursday …

The answer to today’s STUMP BEZOS is
Only 11% of buyers of Amazon businesses get the value expected