Talk outside Tiger StationI. The Search Page Has Changed
Recently, if you open the Amazon North America front page and search for any core keyword, you will see a scene completely different from the past.
The top of the traditional search results page is no longer a list of products, but a whole block dominated by Rufus AI, namely the "Intelligent Shopping Guide Decision Area". This area includes AI-generated shopping guide copy, 69 clickable scenario-based subdivision entries, and a chat button guiding buyers to continue asking questions to Rufus.
What's more, Amazon is testing a more subversive feature - embedding Rufus directly into the search bar itself. In May 2026, Amanda Doerr, Vice President of Core Shopping at Amazon, confirmed to The Information that Amazon was testing a "hybrid mode" in which Rufus-generated AI interpretation content would directly appear above traditional search results in some search queries, without users having to click any icons or open chat windows additionally.
This means that Rufus is changing from an "optional feature" to a "default experience". In the past, buyers had to actively click on the Rufus icon to use AI shopping guide, but now AI directly occupies the most valuable position in the search results - and all this happens before buyers see any product list.
In categories such as electronics and household items that require in-depth price comparison, AI may even compress the search results to only recommend about 3 core products and a few backup options. From 50 products to 5 recommendations, and then to 3 core choices - Rufus is redefining who can be seen by buyers with the "filter net" of AI.
II. Who Has Rufus Taken Traffic Away From?
The impact of this change on sellers is much deeper than it appears on the surface.
The traditional traffic path is: Buyer searches for a major keyword → Browses the product list → Products ranked higher get exposure.
In the era of Rufus, the path has become: Buyer searches for a major keyword → Guided by AI shopping guide → Clicks on the subdivision scenario entry → Jumps to the exclusive page of that long-tail keyword.
This means that the top ranking of the major keyword homepage you have worked hard to win through advertising and optimization may not be seen by buyers at all. Traffic has been redistributed by Rufus according to "demand intention" before entering the product list.
That's why many sellers have recently found that their natural rankings haven't dropped, their ad positions haven't dropped, their prices haven't changed, and their listings haven't moved, but their sales have mysteriously declined. It's not that your operation has a problem, but that your traffic has been "cut off" by Rufus at the front end.
III. Who Will Be Recommended? The Rules Have Changed
The logic of Rufus recommendation is completely different from the traditional A9 keyword algorithm.
The A9 algorithm looks at keyword density, click-through rate, conversion rate and sales speed. But Rufus's recommendation engine is driven by COSMO (Common Sense Knowledge Graph) algorithm, which understands semantics and intention.
When a buyer searches for "wireless earphones suitable for running, sweat-proof and with a battery life of more than 8 hours", Rufus will not only match the keyword "wireless earphones", but also comprehensively judge: Which products are clearly marked with waterproof grades? Which are repeatedly mentioned in the comments as "not falling off during running"? Which ones have answers to battery life-related questions in Q&A?
Research data reveals a more astonishing filtering mechanism - Workflow Labs' analysis found that Rufus compressed the effective product discovery space from about 50 results to about 5. Back-end structured attribute fields (such as material, applicable population, usage scenario tags, etc.), rather than front-end copy, are becoming the key levers determining who "makes it" to Rufus recommendation.
Simply put, Rufus doesn't care about what position your keyword ranks, it only cares whether your product is the "correct answer" in a specific user demand scenario.
IV. Data Tells You, This Is Not A Trivial Matter
The growth rate of Rufus far exceeds the imagination of most sellers:
Amazon disclosed that over 300 million users used Rufus in 2025, and this feature contributed approximately $12 billion in incremental annualized sales;
The Q1 2026 earnings call showed that the monthly active users of Rufus increased by more than 115% year-on-year, and user engagement increased by nearly 400%;
Consumers who use Rufus have a conversion rate that is 60% higher than traditional search users; during Black Friday 2025, Rufus session volume increased by 75% day-on-day;
According to research, the probability of AI response triggered by conversational queries of about 10 words or more is about 68%, while that of single-word queries is only about 15%. This means that Rufus is disproportionately intercepting highly intentional buyers - those who have already described their specific needs in natural language and are closest to placing orders.
Amazon CEO Andy Jassy clearly stated in the earnings call that Rufus is becoming a core component of Amazon's shopping experience. And this test of moving Rufus into the search bar has elevated AI from a "drawer feature" to a "default search interface", and its impact will be geometrically amplified.
V. 99% Of Sellers Are Still Using The Tactics Of 2023
The cruel reality is that the traffic allocation rules have been rewritten, but the operation strategies of the vast majority of sellers are still stuck in the past.
In the past keyword era, the core of traffic competition was "who matched more keywords". But after Rufus and COSMO took over traffic allocation, the platform is moving from "keyword search" to "semantic understanding" - what really determines the ownership of traffic in the future is not how many keywords you stack, but whether your listing can be understood by AI.
When Rufus judges whether a product is worth recommending, the information dimensions it refers to far exceed the title and five-point description. It deeply reads user comments to extract real user experience and pain points; it analyzes the quality of Q&A in the Q&A section; it even integrates external information across the web, including reviews, social media and news reports.
The traditional "stacking keywords + burning advertising" model is accelerating its failure in the face of this new logic.
VI. How To Get Rufus To Recommend Your Product?
Facing this major reshuffle of traffic, sellers need to readjust their operation ideas from three dimensions:
① Listing Restructuring: From "Keyword Stacking" To "Scenario-based Semantic Expression"
The first 80 characters of the title should clearly state "what it is + what it can do", instead of stacking keywords. Rufus recognizes complete phrases of "function + benefit + scenario". For example, for a garlic press, instead of writing "professional kitchen tool, high-quality stainless steel garlic press", it is better to write "garlic press, easy to press, easy to clean, stainless steel, dishwasher safe".
The five-point description should become "what buyers ask, you answer". When Rufus answers buyers' questions, it will directly extract the content in the five-point description. Instead of writing "durable and wear-resistant", it is better to directly explain "why this one is more durable" and "applicable scenarios".
② Improve Back-end Structured Attributes
Filling in the back-end attribute fields such as material, applicable population, usage scenario and compatibility is the basis for Rufus to understand products. Studies show that even if there is no certain keyword in the listing copy, as long as the back-end attributes are correctly marked, Rufus can still match the product to relevant demands through the knowledge graph. This is currently the most underestimated optimization lever by sellers.
③ Make Good Use Of Q&A And Comment Operation
Rufus has a higher trust level for UGC content than seller's own description. Pre-arrange high-frequency questions in Q&A in advance - "Can it be taken on an airplane?" "How many times can it charge a mobile phone?" "Support fast charging?" - these answers are not only conversion tools, but also the core material for AI recommendation. At the same time, the naturally occurring usage scenarios and pain point descriptions in the comments will directly affect the recommendation weight of Rufus, and encouraging buyers to describe usage scenarios in the comments is becoming the new focus of operation.
VII. Crisis Or Dividend? It Depends On Your Choice At This Moment
This major reshuffle of traffic driven by Rufus is a crisis for sellers who stick to traditional ways, but for those who take the lead in understanding the rules and transforming in time, it is a huge dividend for overtaking on the curve.
When AI becomes the "gatekeeper" of traffic, the essence of operation is returning: What problem does your product really solve for whom, and is it clear enough to be understood by AI. Those sellers who can accurately express the value of scenarios, make good use of structured data, and attach importance to user feedback content are becoming the biggest winners under the new traffic rules.
