Amazon’s AI Revolutionizes E-commerce Search
As Amazon intensifies its focus on artificial intelligence-powered shopping, sellers on its vast marketplace face the challenge of optimizing their content while navigating the complexities of this emerging technology. The e-commerce giant, like many of its tech counterparts, continues to heavily invest in AI through data centers, advanced chips, and real estate to power these innovations. The technology’s popularity has surged since the introduction of OpenAI’s ChatGPT in late 2022.
Amazon has rolled out a suite of AI-driven tools for both merchants and customers, including the consumer-facing chatbot assistant, Rufus. The company launched Rufus to all U.S. users in July, ahead of its crucial Prime Day sale. Since then, AI search has become increasingly integrated across Amazon’s platform. For example, Rufus is now available in Amazon’s main search bar, alongside a widget at the bottom of the screen that opens the bot’s chat interface. Users also encounter AI-generated recommendations on product pages, along with AI-generated summaries of customer reviews. According to Adweek, Amazon has even begun incorporating ads into Rufus’s chatbot interface.
In January, during a keynote presentation at the National Retail Federation (NRF), Doug Herrington, CEO of Amazon Worldwide Stores, emphasized the crucial role of AI in Amazon’s operations. “AI is becoming transformative for our business, and we really haven’t had a technology revolution as large as this since the start of the internet,” Herrington stated.
The Customer Experience Shift
For customers, the increasing presence of AI on Amazon’s marketplace marks a significant departure from traditional search methods. Shoppers can now use conversational phrases like, “Is this jacket machine washable?” and “What should I consider when buying a new laptop?” to find what they need, moving beyond reliance on Boolean operators, keywords, or product names.
Adapting to AI Search: Challenges and Opportunities for Sellers
For Amazon sellers, the key question is how to optimize content for AI and how well consumers will adopt to this new approach to e-commerce search. “The way search works now is fundamentally different from traditional SEO,” explained Max Sinclair, a former Amazon employee and founder of Ecomtent, an agency that helps e-commerce brands with AI-driven search strategies. “Large language models don’t operate on keywords alone; they interpret context and intent. That means brands can’t just stuff listings with long-tail keywords and expect the same results. They need to focus on structuring product information in ways AI understands.”
Despite AI’s relatively early stage, Sinclair indicated growing interest from brands, reporting that Ecomtent’s topline revenue has increased by 35% monthly. This growth is attributed to the demand from brands and sellers seeking to adapt to AI on Amazon.
At the end of last year, an Amazon spokesperson informed Modern Retail that customers have asked Rufus over half a billion questions. Using industry benchmarks, Ecomtent estimated that Rufus accounted for nearly 14% of Amazon’s overall searches in October. Sinclair said that this figure could reach 35% by the end of 2025 as more consumers embrace AI.
Impact and Optimization Strategies
For some, optimizing for AI has resulted in sales increases. According to Pattern, an e-commerce accelerator that has been tracking the impact of AI-driven search optimizations, brands that revise their product listings to align with AI-driven search parameters see a median revenue boost of 15-20%.
A scholarly paper about Amazon’s AI search technology, authored by scientists within Amazon’s science division and published in early 2024, found that AI-driven personalization resulted in a 0.7% increase in conversion rates. While this might seem small, given Amazon’s scale, the authors noted that it represents hundreds of millions of dollars in additional annual revenue.
However, Jacob Miller, VP of Data Science at Pattern, emphasizes the importance of product quality: “If it’s a bad product, it doesn’t help. You can customize content and make the best possible listing, but if customers ultimately don’t find value in the product, AI won’t sustain it in search rankings.”
As AI-powered search continues to evolve, sellers are closely following consumer adoption trends. Miller notes that the trend of AI-assisted product discovery extends beyond Amazon, with platforms like OpenAI’s ChatGPT and Google’s AI tools also providing product recommendations. Previously, Modern Retail reported that some brands are experiencing significant traffic spikes driven by Google Gemini and ChatGPT search recommendations.
Optimizing for search goes beyond simply using the right keywords. Miller noted, “Amazon’s AI can now factor in contextual elements about a shopper’s background or past behavior, even if they don’t explicitly search for those details. If a shopper mentions in a query that they’re looking for a birthday gift for their mother, AI can pull from listings that have signals indicating they are good for gifting.”
Miller shared an example, saying that when he tested Rufus by searching for triathlon gear, Amazon recognized his prior searches for equipment that could withstand chlorinated water, likely due to his previous triathlon-related queries.
For sellers, the challenge lies in adapting to this new reality, especially as the technology evolves. Will Haire, co-founder and CEO of BellaVix, a marketing agency that supports brand growth on Amazon and Walmart marketplaces, has been experimenting with Rufus to understand its impact better: “What we do know is that the AI looks at the product detail page, it looks at the question and answer section, and it looks at reviews,” Haire said.
To better align with AI search behavior, Haire’s team has been experimenting with incorporating natural language patterns into product content and tracking long-tail keyword performance. However, Haire said BellaVix hasn’t yet observed a direct correlation between the AI optimizations and increased sales. This is due to the many variables involved, which make it difficult to isolate AI search as a single major driver for growth.
In November, Rajiv Mehta, a VP at Amazon working on conversational AI shopping, including Rufus, told Modern Retail that a crucial factor for sellers in search optimization is the accuracy, currency, and factual nature of their product listings. “One of the things we know when customers are shopping on Amazon is that they’re really trying to make informed decisions and get good information about the products they’re trying to choose and shop for,” Mehta said.
“With Rufus, you can just ask those questions, and Rufus is able to predict what sorts of questions that customer may have and actually surface those questions proactively to a customer.”
