Amazon’s AI-Driven Search in 2025: How Sellers Can Optimize for Rufus & COSMO

Amazon’s search is rapidly evolving from simple keyword matching to a conversational, AI-powered experience. In late 2024, Amazon rolled out Rufus, a generative-AI shopping assistant, and increasingly embeds its new COSMO model behind the scenes. Consumers are already using AI shopping tools – an Adobe study found 39% of U.S. shoppers have tried AI for shopping, and shopping traffic from AI sources surged over 1,200% year-over-year.

In other words, buyers now “Ask Rufus” for help instead of just typing keywords. For Amazon sellers, this means old SEO tactics (keyword-stuffing titles) are fading in favor of conversational, user-focused content. Below, we explain Rufus and COSMO, why they matter, and data-backed strategies to optimize your listings in this new era.

What Are Rufus and COSMO?

Rufus is Amazon’s new AI chat assistant in the shopping app and desktop site. Imagine a friendly store clerk you can text: Rufus understands natural-language questions (“what to consider when buying running shoes?”) and responds with recommendations, comparisons, and product info. Under the hood, COSMO is the powerful AI model that drives Rufus and Amazon’s search engine. It’s a “common-sense” knowledge graph built from trillions of shopper behaviors, LLM outputs, and curated data. In fact, Amazon’s research shows COSMO-LM expanded its product knowledge graph across 18 major categories, generating millions of high-quality facts from just 30K examples.

Figure: Amazon’s Rufus AI shopping assistant sits in the search bar (“Ask Rufus”), drawing on product data, reviews and Q&As to answer customer questions.

In practice, COSMO is the unseen “brain” analyzing your past shopping behavior and intent, while Rufus is the chat interface (“voice”) you interact with. Sellers should know: Rufus taps your product listings directly. Amazon confirms Rufus has already answered tens of millions of questions, using “helpful information found in product listing details, customer reviews, and community Q&As”. In short, anything you put on your detail page text, images, videos, reviews and answers can feed Rufus’s responses.

Why This Matters for Sellers

Generative AI is not a novelty – it’s changing how people shop. According to Adobe Analytics, traffic from AI-powered shopping agents to U.S. retail sites jumped ~1,300% during the 2024 holiday season and continues to double every few months. In fact, 55% of surveyed shoppers say they use AI for product research and 47% for recommendations. These consumers are more engaged: Adobe reports AI-driven visitors view 12% more pages and bounce 23% less on retail sites, indicating they want detailed information from smart assistants.

Amazon itself is signaling a shift. In early 2025 it shut down its TikTok-style “Inspire” feed to double down on AI-driven search. CEO Andy Jassy revealed Amazon will spend most of its $100 billion 2025 capex on AI (mostly AWS infrastructure). Amazon has also launched other AI shopping tools – from fit review highlights to AI Shopping Guides – to make discovery smarter. As Amazon VP Daniel Lloyd notes, new AI features like Rufus and Shopping Guides will “meaningfully improve how you learn about, explore, and discover products”.

Bottom line: Buyers are using AI-enhanced search, and Amazon is committed to it. Sellers who adapt will reach these customers; those who don’t risk being “forgotten” by COSMO’s new algorithm.

AI vs. Traditional Search: Key Differences

The rise of Rufus/COSMO adds new layers to Amazon SEO. Here’s how AI-driven search differs from the old model, and what it means for your content:

• Conversational, Intent-Focused Queries: Traditional Amazon SEO focused on embedding high-volume keywords in titles and bullets. Now, Rufus understands full questions and context, not just keyword matches. Listings need to use natural, conversational language that matches how real people ask questions. Think in terms of user intent: e.g. “best lightweight running shoes for trail” rather than a string of keywords.

• Holistic PDP Storytelling: With COSMO, every element of the detail page matters. It’s no longer just specs and features – you need to tell a cohesive story about the product. Include use cases, benefits and context. Acadia recommends balancing product-focused bullet points with audience-focused ones to address specific personas. For example, after listing features, add a bullet like “Perfect for marathon training – this shoe’s advanced cushioning supports heavy mileage” to speak to runners’ needs.

• Leveraging Reviews and Q&As: Amazon’s AI actively reads your reviews and Q&A. Official Amazon documentation states Rufus answers questions by pulling info from listing details, customer reviews, and community Q&As. That means encourage detailed reviews (they get aggregated in AI summaries) and seed your own Q&A section with common questions. Answer buyer queries promptly – Rufus can draw on them directly. For example, a well-written answer “Yes, this jacket is machine-washable” can surface when someone asks Rufus that exact question.

• Image and Video SEO: AI search “reads” your images too. Acadia notes that “Rufus now processes images and videos, not just text,” so a bare lifestyle photo is less effective. Use infographics or text overlays in images to capture key points (e.g. a bag image labeled “Waterproof material for rain protection”). Amazon’s AI Shopping Guides and Shopping Assistant will consider this visual text in understanding products. Also include detailed product videos or AR views if possible – these richer assets can improve engagement, which correlates to better ranking.

• Personalization and Common Sense: COSMO infuses “common-sense” understanding into search. For example, it knows “winter clothes” should relate to warmth, insulation, layers, not just any clothing item. When writing listings, align with user intent and associations. If a sweater is thermal and fleece-lined, mention those warm materials in bullets – COSMO will connect that to winter needs.

Strategies to Optimize for AI-Driven Search

Given these shifts, here are actionable, data-backed tips to tune your listings for Rufus/COSMO:

• Use Natural Language and Long-Tail Phrases: Rewrite bullets and descriptions in a conversational tone. Instead of “Lightweight hiking boots,” try “Boots designed for all-day hiking comfort.” Include common long-tail queries (e.g. “best hiking boots for flat feet”) naturally in your content. Code3 SEO advises using a variety of keywords, including common misspellings and different product uses, so Rufus can match diverse user inputs.

• Tell a Story on Your PDP: Don’t just list specs. Start by briefly describing why someone would want the product. For example: “This ergonomic office chair was built to relieve back pain during long workdays.” Then bullet the main features. This narrative approach maps to the shopper’s “why” and helps COSMO understand context.

• Enhance with A+ Content: Amazon’s A+ Content (enhanced brand story) is more important than ever. Use it to weave in detailed explanations, comparison charts, and lifestyle images that address customers’ needs. Since COSMO considers “user-generated content, review summaries, and mobile readability”, well-formatted A+ layouts can boost your product’s relevance. For example, include a comparison table of similar products (“choose this one if you need waterproof material; otherwise see XYZ for lightweight design”).

• Optimize Images with Text Overlays: As noted, text in images can trigger AI attention. Use at least one image with a textual highlight (“Oil-Resistant, High-Grip Handle”) or an infographic that answers a common question. This way, when Rufus scans images, it reads those cues.

• Leverage Amazon’s AI Listing Tools: Amazon has its own generative AI tools for sellers. The “Enhance My Listing” feature (Powered by Bedrock) can auto-generate titles, bullets, and descriptions from a few inputs. Over 900K sellers have used Amazon’s AI and report a ~40% improvement in listing quality and discoverability. Use these tools as a starting point, then customize the results to match your brand’s voice. These AI suggestions are based on customer shopping data and can highlight missing keywords or benefits you hadn’t thought of.

• Keep Content Fresh: Amazon’s AI models re-crawl listings over time. According to experts, updates can take 3–6 months to fully register in COSMO’s model. Plan to update content every quarter or so. When a new season or trend emerges, edit your listing right away. For example, if a new certification or award is earned, add that to your bullets. Patience is key: COSMO needs time to “re-learn” your page.

• Test Prompts & Monitor Metrics: Manually test how your listing appears in Rufus. Enter sample questions (“best Bluetooth speaker under $100”) and see if your product is in the top recommendations. Over time, you should see your ASIN appear more frequently in such AI-driven results if your optimization is effective. Also track traditional KPIs: Conversion Rate (CVR), Best Seller Rank (BSR), and Organic Share-of-Voice. Acadia suggests these remain critical. If CVR and sales increase after your changes, that’s a good sign your listing aligns with customer intent. Since direct “Rufus impressions” aren’t available, use these indirect signals as proxies for AI ranking impact.

• Encourage Reviews & Q&A Activity: Specifically ask customers for reviews and vote on helpful ones. More and richer reviews feed the AI. Amazon’s new “Review Highlights” feature already uses AI to summarize dozens of reviews. The more five-star and detailed reviews you have, the better content Rufus has to quote. Similarly, when buyers ask questions on your listing, respond thoroughly. This not only improves conversion for human shoppers but also populates the knowledge Rufus uses.

Measuring Impact and KPIs

Tracking success in this new environment means both old and new metrics. Continue monitoring Conversion Rate (CVR) and Sales Velocity/BSR, since higher conversion signals to the algorithm that your page matches intent. Organic traffic share is still valuable: if your ASIN is surfacing more in search (including Rufus results), you’ll likely see improved metrics. Also watch engagement: AI-driven shoppers tend to engage more deeply, so time-on-page or pages-per-session (if you have tracking) can indicate if shoppers find your content useful.

Don’t expect overnight results. Industry analysts note that AI-driven indexing is slower. As [Acadia’s experts] stress, you may need 3–6 months or longer before content changes fully affect Rufus rankings. Keep experimenting iteratively: update one aspect (e.g. title, or add an infographic) and check metrics over time.

Finally, stay informed. Amazon frequently releases new AI features (Interests AI, visual search, etc.). For example, Interests (launched in late 2024) proactively shows products based on passions. Align your content for these as well: use relevant topic tags and attributes so your products are eligible in these AI-driven feeds.

Actionable Takeaways

• Write for humans and AI: Use natural language, answer questions directly, and tell the product’s “story.”

• Rich content wins: Invest in quality images (with text callouts), videos, and A+ content. These help COSMO understand your product’s purpose and benefits.

• Leverage feedback loops: Encourage reviews and answer FAQs. Their text flows into the AI model.

• Use Amazon’s AI tools: Try “Enhance My Listing” or related tools to generate optimized titles and bullets, then fine-tune the suggestions.

• Be patient and data-driven: Track CVR, BSR, and prompt-test results over weeks. Small ranking changes may take time to show in these KPIs.

• Stay adaptive: The era of “write once and forget” is over. Amazon’s shopping AI is a moving target – keep testing new queries and iterating your listings.

Amazon’s shift to AI-driven search means sellers have a huge opportunity: rankings now reward listings that communicate value and context. By focusing on customer intent and leveraging Amazon’s own AI features, you can make your products more discoverable in Rufus and beyond. The brands that adapt early will capture loyal AI-era shoppers those who don’t risk falling off the radar entirely.