Amazon Accelerate AI Tools: Product Titles & Recommendations
Hi Sellers,
Welcome to part two of Amazon Accelerate AI Tools. If you missed part 1 you can find it here: Amazon Accelerate AI Tools: Project Amelia. Today we are discussing how Amazon is leveraging generative AI to personalize recommendations to customers!
Amazon is leveraging generative AI to further personalize product recommendations and descriptions in our store. Based on a customer’s shopping activity, Amazon reviews each customer’s preferences to create personalized recommendations types on our homepage and throughout the shopping journey, as well as provide personalized product descriptions that are more relevant to customers.
For example, instead of providing generic product recommendations to customers such as “More like this,” we’ll provide more specific, personalized recommendations such as "Gift boxes in time for Mother's Day" or "Cool deals to improve your curling game" based on a customer’s shopping activity. Or, if a customer regularly searches for gluten-free products and they search for “gluten free cereal,” now AI will intelligently position the term “gluten-free” within product descriptions of the right products that appear in search results, ensuring it stands out prominently–even if Amazon or the selling partner has listed “gluten-free” at the very end of the product description.
By analyzing product attributes and customer shopping information, like preferences, search, browsing, and purchase history, we leverage a Large Language Model (LLM) to edit a product title to highlight features that we believe are most important to the customer and their current shopping activity. To ensure these titles accurately reflect what matters most to each individual, another LLM, known as an evaluator LLM, challenges and improves the results, assuring customers see the best possible product information.
What are your thoughts on how this could impact how you sell on Amazon?
Best,
Dominic
Amazon Accelerate AI Tools: Product Titles & Recommendations
Hi Sellers,
Welcome to part two of Amazon Accelerate AI Tools. If you missed part 1 you can find it here: Amazon Accelerate AI Tools: Project Amelia. Today we are discussing how Amazon is leveraging generative AI to personalize recommendations to customers!
Amazon is leveraging generative AI to further personalize product recommendations and descriptions in our store. Based on a customer’s shopping activity, Amazon reviews each customer’s preferences to create personalized recommendations types on our homepage and throughout the shopping journey, as well as provide personalized product descriptions that are more relevant to customers.
For example, instead of providing generic product recommendations to customers such as “More like this,” we’ll provide more specific, personalized recommendations such as "Gift boxes in time for Mother's Day" or "Cool deals to improve your curling game" based on a customer’s shopping activity. Or, if a customer regularly searches for gluten-free products and they search for “gluten free cereal,” now AI will intelligently position the term “gluten-free” within product descriptions of the right products that appear in search results, ensuring it stands out prominently–even if Amazon or the selling partner has listed “gluten-free” at the very end of the product description.
By analyzing product attributes and customer shopping information, like preferences, search, browsing, and purchase history, we leverage a Large Language Model (LLM) to edit a product title to highlight features that we believe are most important to the customer and their current shopping activity. To ensure these titles accurately reflect what matters most to each individual, another LLM, known as an evaluator LLM, challenges and improves the results, assuring customers see the best possible product information.
What are your thoughts on how this could impact how you sell on Amazon?
Best,
Dominic
2 replies
Seller_GYBivd6QH6hzX
Well, we'll lose some Amazon sales since a statistically significant number of our customer base are, like me, tired of tech bros shoving "AI" needlessly into every aspect of daily life, and will stop purchasing on Amazon as a result of that.
On the upside, we'll pick up some direct sales instead, so likely no major loss.
Our return rate will go up, since LLMs are notoriously (and somewhat ironically) terrible at being able to correctly interpret technical data, so people will be buying products the AI has wildly incorrectly assured them will work for their use-case, and they'll subsequently be opening returns most likely under "not as described on website" because the AI was wrong. We've already seen this from the "Rufus" fiasco, where Rufus was giving people answers about the components we sell in which literally every aspect of the answer was incorrect.
I really wish sellers (and buyers for that matter) were given the opportunity for input before these sort of far-reaching and wildly unnecessary changes were implemented, rather than the old "hey, we've just done this, do you think you'll survive?" approach, but eh... so it goes.
Amazon Accelerate AI Tools: Product Titles & Recommendations
Hi Sellers,
Welcome to part two of Amazon Accelerate AI Tools. If you missed part 1 you can find it here: Amazon Accelerate AI Tools: Project Amelia. Today we are discussing how Amazon is leveraging generative AI to personalize recommendations to customers!
Amazon is leveraging generative AI to further personalize product recommendations and descriptions in our store. Based on a customer’s shopping activity, Amazon reviews each customer’s preferences to create personalized recommendations types on our homepage and throughout the shopping journey, as well as provide personalized product descriptions that are more relevant to customers.
For example, instead of providing generic product recommendations to customers such as “More like this,” we’ll provide more specific, personalized recommendations such as "Gift boxes in time for Mother's Day" or "Cool deals to improve your curling game" based on a customer’s shopping activity. Or, if a customer regularly searches for gluten-free products and they search for “gluten free cereal,” now AI will intelligently position the term “gluten-free” within product descriptions of the right products that appear in search results, ensuring it stands out prominently–even if Amazon or the selling partner has listed “gluten-free” at the very end of the product description.
By analyzing product attributes and customer shopping information, like preferences, search, browsing, and purchase history, we leverage a Large Language Model (LLM) to edit a product title to highlight features that we believe are most important to the customer and their current shopping activity. To ensure these titles accurately reflect what matters most to each individual, another LLM, known as an evaluator LLM, challenges and improves the results, assuring customers see the best possible product information.
What are your thoughts on how this could impact how you sell on Amazon?
Best,
Dominic
Amazon Accelerate AI Tools: Product Titles & Recommendations
Hi Sellers,
Welcome to part two of Amazon Accelerate AI Tools. If you missed part 1 you can find it here: Amazon Accelerate AI Tools: Project Amelia. Today we are discussing how Amazon is leveraging generative AI to personalize recommendations to customers!
Amazon is leveraging generative AI to further personalize product recommendations and descriptions in our store. Based on a customer’s shopping activity, Amazon reviews each customer’s preferences to create personalized recommendations types on our homepage and throughout the shopping journey, as well as provide personalized product descriptions that are more relevant to customers.
For example, instead of providing generic product recommendations to customers such as “More like this,” we’ll provide more specific, personalized recommendations such as "Gift boxes in time for Mother's Day" or "Cool deals to improve your curling game" based on a customer’s shopping activity. Or, if a customer regularly searches for gluten-free products and they search for “gluten free cereal,” now AI will intelligently position the term “gluten-free” within product descriptions of the right products that appear in search results, ensuring it stands out prominently–even if Amazon or the selling partner has listed “gluten-free” at the very end of the product description.
By analyzing product attributes and customer shopping information, like preferences, search, browsing, and purchase history, we leverage a Large Language Model (LLM) to edit a product title to highlight features that we believe are most important to the customer and their current shopping activity. To ensure these titles accurately reflect what matters most to each individual, another LLM, known as an evaluator LLM, challenges and improves the results, assuring customers see the best possible product information.
What are your thoughts on how this could impact how you sell on Amazon?
Best,
Dominic
Amazon Accelerate AI Tools: Product Titles & Recommendations
Hi Sellers,
Welcome to part two of Amazon Accelerate AI Tools. If you missed part 1 you can find it here: Amazon Accelerate AI Tools: Project Amelia. Today we are discussing how Amazon is leveraging generative AI to personalize recommendations to customers!
Amazon is leveraging generative AI to further personalize product recommendations and descriptions in our store. Based on a customer’s shopping activity, Amazon reviews each customer’s preferences to create personalized recommendations types on our homepage and throughout the shopping journey, as well as provide personalized product descriptions that are more relevant to customers.
For example, instead of providing generic product recommendations to customers such as “More like this,” we’ll provide more specific, personalized recommendations such as "Gift boxes in time for Mother's Day" or "Cool deals to improve your curling game" based on a customer’s shopping activity. Or, if a customer regularly searches for gluten-free products and they search for “gluten free cereal,” now AI will intelligently position the term “gluten-free” within product descriptions of the right products that appear in search results, ensuring it stands out prominently–even if Amazon or the selling partner has listed “gluten-free” at the very end of the product description.
By analyzing product attributes and customer shopping information, like preferences, search, browsing, and purchase history, we leverage a Large Language Model (LLM) to edit a product title to highlight features that we believe are most important to the customer and their current shopping activity. To ensure these titles accurately reflect what matters most to each individual, another LLM, known as an evaluator LLM, challenges and improves the results, assuring customers see the best possible product information.
What are your thoughts on how this could impact how you sell on Amazon?
Best,
Dominic
2 replies
2 replies
Seller_GYBivd6QH6hzX
Well, we'll lose some Amazon sales since a statistically significant number of our customer base are, like me, tired of tech bros shoving "AI" needlessly into every aspect of daily life, and will stop purchasing on Amazon as a result of that.
On the upside, we'll pick up some direct sales instead, so likely no major loss.
Our return rate will go up, since LLMs are notoriously (and somewhat ironically) terrible at being able to correctly interpret technical data, so people will be buying products the AI has wildly incorrectly assured them will work for their use-case, and they'll subsequently be opening returns most likely under "not as described on website" because the AI was wrong. We've already seen this from the "Rufus" fiasco, where Rufus was giving people answers about the components we sell in which literally every aspect of the answer was incorrect.
I really wish sellers (and buyers for that matter) were given the opportunity for input before these sort of far-reaching and wildly unnecessary changes were implemented, rather than the old "hey, we've just done this, do you think you'll survive?" approach, but eh... so it goes.
Seller_GYBivd6QH6hzX
Well, we'll lose some Amazon sales since a statistically significant number of our customer base are, like me, tired of tech bros shoving "AI" needlessly into every aspect of daily life, and will stop purchasing on Amazon as a result of that.
On the upside, we'll pick up some direct sales instead, so likely no major loss.
Our return rate will go up, since LLMs are notoriously (and somewhat ironically) terrible at being able to correctly interpret technical data, so people will be buying products the AI has wildly incorrectly assured them will work for their use-case, and they'll subsequently be opening returns most likely under "not as described on website" because the AI was wrong. We've already seen this from the "Rufus" fiasco, where Rufus was giving people answers about the components we sell in which literally every aspect of the answer was incorrect.
I really wish sellers (and buyers for that matter) were given the opportunity for input before these sort of far-reaching and wildly unnecessary changes were implemented, rather than the old "hey, we've just done this, do you think you'll survive?" approach, but eh... so it goes.
Seller_GYBivd6QH6hzX
Well, we'll lose some Amazon sales since a statistically significant number of our customer base are, like me, tired of tech bros shoving "AI" needlessly into every aspect of daily life, and will stop purchasing on Amazon as a result of that.
On the upside, we'll pick up some direct sales instead, so likely no major loss.
Our return rate will go up, since LLMs are notoriously (and somewhat ironically) terrible at being able to correctly interpret technical data, so people will be buying products the AI has wildly incorrectly assured them will work for their use-case, and they'll subsequently be opening returns most likely under "not as described on website" because the AI was wrong. We've already seen this from the "Rufus" fiasco, where Rufus was giving people answers about the components we sell in which literally every aspect of the answer was incorrect.
I really wish sellers (and buyers for that matter) were given the opportunity for input before these sort of far-reaching and wildly unnecessary changes were implemented, rather than the old "hey, we've just done this, do you think you'll survive?" approach, but eh... so it goes.
