How Rufus & Cosmo AI are transforming eCommerce for brands
- Danielle Miles
- Apr 21
- 7 min read
The eCommerce world is being reshaped at an incredible pace, and Amazon’s dynamic AI-powered innovations—Rufus and Cosmo—are leading this transformation. These groundbreaking tools aren’t just redefining how consumers search, shop, and engage online; they are opening incredible new opportunities for brands to boost visibility, drive conversions, and redefine their digital strategies.
But what exactly are Rufus and Cosmo AI, and how can brands leverage them to maximize visibility, conversion, and sales? Today, we share insights from Rachel Tetreault, General Manager. A former eCommerce and Marketing executive with Procter and Gamble, Ferrero USA, and Eastport Sports, Rachel is passionate about helping CPG brands captivate and convert consumers, ensuring they win both in-store and on key retailer platforms. Always on the lookout for the latest tech innovations, Rachel adds significant value for brands through retail media tech, digital shelf strategies, shopper marketing, and compelling content.
To learn more about COSMO AI, Rufus, and other tools and strategies that can help optimize your digital shelf, reach out to Rachel at Rachel.tetreault@mpgllc.com. As a proud Amazon Advance partner, our experienced MPG team has the deep experience and expertise needed to accelerate your platform growth.
Rufus AI – Amazon’s AI Shopping Assistant
Let’s start with Rufus AI. How does it work?
Rufus is Amazon’s AI-powered shopping assistant designed to deliver a seamless and hyper-personalized shopping experience. Think of Rufus as Amazon’s version of ChatGPT, but tailored specifically for eCommerce. Rufus processes natural language queries and provides real-time, conversational responses that guide users through the shopping process.
Rufus engages directly with customers via natural language processing (NLP), responding to queries and guiding users through a dynamic and conversational shopping experience. Whether shoppers ask for recommendations, compare products, or seek answers to common questions, Rufus provides contextual and relevant guidance at various touchpoints across the shopping platform.
What makes it a game-changer?
A number of things stand out, from a brand perspective:
Conversational Search. Shoppers no longer have to rely on keyword-dense searches like "best headphones under $100." Instead, Rufus enables queries with a more human touch, such as "What headphones are best for working out and noise cancellation?"
Product Comparisons. Rufus helps consumers make better buying decisions by presenting side-by-side product comparisons, complete with key specifications, reviews, and pricing. This allows customers to pinpoint what product meets their unique requirements the best.
Personalized Guidance. Beyond answers, Rufus refines product discovery by learning from customer preferences, browsing history, and live actions on site. Looking for a laptop but need one with extra battery life? Rufus can zero in on recommendations based on feedback in real time.
Why is Rufus such a big deal for brands?
Rufus represents a massive leap forward in how products are discovered and evaluated. It unlocks three critical advantages:
Improved discoverability. Engaging and customer-focused product recommendations reduce buyer hesitation, turning browsers into buyers. Products optimized for Rufus queries show up more prominently in search, bringing your brand to the forefront of shopper exploration.
Higher conversion rates. Detailed, conversational product information provided by Rufus effectively reduces buyer hesitation, translating into more completed purchases.
High-quality traffic. Because Rufus interacts with customers during the decision phase, it brings ready-to-buy traffic directly to product listings.
What do you advise brands looking to optimize for Rufus AI?
Brands aiming to leverage Rufus AI must rethink their content blueprint. Here’s a checklist to get started:
Write for natural language queries. Expand your product descriptions to include phrases that reflect how customers are likely to search. Move beyond technical jargon. Mirror natural conversational phrases in your copy, focusing on customer intent. Include phrases like, "Can these shoes handle long-distance running?" instead of generic descriptions like "durable." Quick tip: Walk through your product listings on Amazon using conversational queries. Check how well your content aligns with real-world customer queries and adjust accordingly.
Revamp visual content. So important! Rufus doesn’t just pull text data—It analyzes visuals—images, infographics, and more—to provide enriched search results. Make use of contextual images (e.g., a product in real-life usage) and high-resolution media to compel potential buyers. Evaluate your product images by uploading them to tools like Amazon’s “Generate Listings” feature or platforms such as ChatGPT to understand exactly how AI interprets each image. Add context-heavy visuals, like images of the product being used, to bridge the gap between features and real-life utility.
Leverage enhanced content. Refine your Product Detail Pages (PDP) to include engaging elements such as FAQs, comparison charts, and detailed narratives. Keep in mind, Rufus extracts insights from your product A+ pages, so make sure these pages provide comprehensive answers to customer pain points. Include FAQs, comparison charts, and compelling brand storytelling to enhance engagement.
Let’s turn our attention to Cosmo AI.
Why has it attracted so much attention since its introduction?
Well-deserved attention! While Rufus focuses on shopper conversations, Cosmo AI represents a fundamental shift in Amazon’s search algorithms. Cosmo AI is a semantic search engine that focuses on understanding the context and intent behind search queries. Unlike traditional searches that depend heavily on keywords, Cosmo learns what shoppers really mean when they submit a query and generates customer-centric recommendations that match those needs.
Simply put, Cosmo goes beyond answering "what" to understanding "why," ensuring every result is relevant and intuitive. Its ability to analyze behavior and past interactions allows it to deliver results that feel effortless and satisfying.
How does Cosmo AI work?
Cosmo analyzes context, behavior, and previous shopping patterns to provide highly personalized and relevant results. For instance, if a user searches for “lightweight stroller for city living,” Cosmo will tailor results based on specific attributes like size, weight, and maneuverability. This level of contextual relevance ensures shoppers spend less time filtering through irrelevant products while brands with well-optimized listings enjoy greater visibility.
To accomplish this, Cosmo uses a multi-modal approach with three primary functions:
Contextual awareness. Understanding the who, what, when, and why a user is searching. For instance, searching "lightweight jackets for winter" would prioritize products that account for warmth, style, and practicality specific to cold weather conditions.
Semantic understanding. Cosmo ensures different word meanings or synonyms are applied in the right context to provide more precise search results. For example, "smart shoes" could mean "elegant" or "tech-integrated," and Cosmo tailors results accordingly.
Ongoing learning. By analyzing user interactions and continuously optimizing based on search trends, Cosmo becomes smarter over time, predicting shopper needs more accurately during future visits.
How has Cosmo changed the game for brands on Amazon?
It’s no longer just about generating content, content, content. You’ve got to have the right context and keep the consumer at the center. Focus on answering the why and how behind a purchase decision. Why is your product the best fit? How does it solve the customer’s problem?
Importantly, Cosmo goes beyond keywords. Traditional SEO strategies alone cannot drive the same success. Brands now need to focus on aligning product attributes with shopper intent to rank prominently on the evolving Amazon search platform. Shift focus to natural, conversational queries versus rigid keywords. Refine product attributes, metadata, and backend data to align with how shoppers think.
The other thing to remember: Cosmo extracts insights from product images as well as text, turning images into powerful SEO tools. Attributes like product features visible in an image (e.g., materials, branding, and accessories) are extracted and indexed for better discoverability. Cosmo ensures that brands with well-curated images and structured metadata are prioritized in results. So brands need to use visuals strategically, ensuring they capture both the functionality and lifestyle appeal of your product. From descriptive overlays to contextual infographics, ensure your images and videos meet today’s high standards for optical recognition and engagement.
How is your team helping brands adapt their approaches to fully leverage Cosmo AI?
To succeed in this new search paradigm, it’s really critical to create listings that tell a story—not just list features. To get started, we focus on three key areas:
Elevate Product Detail Pages (PDPs). Go beyond listing features—focus on storytelling. How does the product solve a consumer’s problem? Why is it the ideal option for their particular need? Pair this with relatable lifestyle imagery to amplify your message.
Ensure complete attributes. A lot of brands miss this one, and it’s so important. Ensure all product attributes—like size, dimensions, material, and specific use cases—are filled out. Cosmo uses backend attributes to filter and recommend products. Without optimizing these overlooked details, brands risk losing opportunities to be featured.
Make reviews work hard for the brand. I think we all know that customer reviews are important, but they are absolutely vital inputs for AI systems like Cosmo. Customer reviews aligned with common queries aid AI-driven relevance. Create ways to encourage detailed reviews while addressing recurring issues to improve product sentiment. One quick tip: Search for your products on Amazon using conversational queries, and test how well the results align with your target shopper’s preferences. The feedback can guide improvements in your descriptions and attributes.
Keep it dynamic. Cosmo thrives on dynamic data. Regularly A/B test and optimize product content to meet seasonal trends, emerging patterns, and social changes.
How do you see Gen AI’s impact on performance metrics and ad costs?
There’s no doubt that with AI proliferating, traditional metrics like share of digital shelf or keyword rankings may become less relevant. Success will depend on product narratives that drive contextually relevant search results and boost engagement.
As for cost impacts, while algorithms like Cosmo improve relevancy, they tend to level the playing field, making ad placements more competitive. This means brands that don’t meet relevancy benchmarks may find themselves relying on more expensive paid promotions to stay visible.
Powering a New Era of Online Shopping
Together, Rufus and Cosmo function as a seamless duo to elevate the entire shopping experience. While Rufus bridges the gap between customer intent and product discovery, Cosmo refines the process by prioritizing relevance through semantics, patterns, and visual data. Rufus helps shoppers refine their search journeys by learning from their intent and behavior. Cosmo ensures optimized content, relevant results, and meaningful connections between products and customers. For brands, adapting to these tools with hyper-personalized content and refreshed strategies will be the key to unlocking higher sales and fewer returns.
Need help getting there? Our team of experts can guide your brand in optimizing for Amazon’s AI tools. Reach out to Rachel at Rachel.tetreault@mpgllc.com for a conversation.