From E-Commerce to Immersive Commerce: Building Next-Generation Retail Experiences on AWS

1. Introduction

E-commerce has fundamentally reshaped retail, bringing speed and convenience to millions of shoppers worldwide. Yet despite decades of optimization, the online journey still falls short of replicating the in-store confidence that comes from trying, touching, and comparing products physically. Customers must rely on static images, reviews, and assumptions about quality or fit, which often leads to disappointment and higher return rates. This lack of sensory engagement represents a major friction point for digital retail - increases costs for returns, and limits brand differentiation in highly competitive markets.

Immersive commerce is emerging as the solution. By weaving together 3D product visualization, augmented reality (AR), virtual reality (VR), and generative AI, retailers can create digital experiences that rival the store floor. Immersive tools replicate the experience, offer contextual recommendations, and give customers a sense of confidence long missing from online retail. For businesses, the case is compelling: improved conversions, fewer returns, richer customer engagement, and stronger brand loyalty.

2. Traditional vs. Immersive Experience

The contrast is significant. Traditional digital commerce provides limited interaction and leaves customers uncertain until products arrive. Immersive commerce, by contrast, bridges this gap by enabling visualization, simulation, and guided interaction in real time. Customers can not only view products but also test how they fit into their lives, whether that means virtually placing a sofa in a living room, trying on a jacket with accurate drape simulation, or receiving personalized guidance for an upcoming event.

Research from Shopify indicates AR product visualization can increase conversions by as much as 94% compared to static imagery. For business leaders, adopting immersive commerce is not only a customer-experience upgrade—it is a way to differentiate and compete as an innovation-driven brand. Retailers that adopt immersive commerce early are also more likely to capture younger demographics—particularly Gen Z and Gen Alpha—who expect digital experiences to be social, interactive, and immersive.

3. Examples of Immersive AI Offerings

Immersive AI is no longer experimental; it is already redefining customer engagement:

• Virtual Try-On: Customers can preview apparel, cosmetics, or furniture in their own context before purchasing, reducing uncertainty and fit-related returns. Retailers using AR or 3D/AR content report up to 94% higher conversion rates compared to non-AR products, and some see 20-30% fewer returns when virtual try-on is enabled.

• AI Stylist Chatbots: Intelligent agents combine purchase history, trend data, and real-time context (weather, events) to deliver dynamic recommendations. Brands implementing conversational AI see conversion rates increase by up to 4×, and shopping sessions speed up by nearly 50% for customers who interact with AI chat versus those who don’t. AI stylists help personalize experiences, reduce uncertainty, and improve engagement and basket size.

• Visual Similarity & “Complete-the-Look” Search: Shoppers upload an image or select a product to find stylistically similar items or complementary pieces. Amazon’s personalization solutions demonstrate this reduces bounce rates significantly. For fashion, beauty, and home décor, similarity search transforms inspiration into conversion by connecting desire with available inventory.

• Immersive Environments & Social Commerce: Platforms like Roblox allow brands to build immersive showrooms where users can explore, co-create, and even purchase physical products. These spaces are not limited to marketing—they are becoming new points of sale, allowing retail to intersect with gaming, events, and culture.

Collectively, these examples show how immersive AI directly impacts conversion, loyalty, and brand differentiation. They demonstrate that immersive retail is not a passing trend, but a structural shift in how consumers expect to interact with brands.

4. AWS Architecture for Immersive Commerce

To realize immersive experiences, AWS provides a reference blueprint built for scalability, security, and agility.

Architecture Diagram: Virtual Personal Stylist on AWS

• Application Hosting & Security: The application runs on AWS Fargate (ECS), served through Amazon CloudFront and secured with AWS WAF (Web Application Firewall). Users authenticate with Amazon Cognito user pools. Secrets Manager stores API keys, URLs, and Cognito IDs securely. This ensures apps are distributed globally, load quickly, and remain hardened against threats.

• API Gateway & Routing: API Gateway exposes endpoints, routing traffic from users to the correct AWS Lambda functions. Routes include /text for chat, /image for try-on, and /search for product discovery. Gateway integration simplifies scaling and monitoring, while Secrets Manager integration enforces secure access.

  • Text Generation Flow:

    The /text endpoint invokes a Lambda that calls Agents for Amazon Bedrock. The agent considers user context, such as location and weather, and queries data stored in S3 and indexed in Amazon OpenSearch Serverless knowledge bases. The response includes grounded style recommendations, preventing hallucination and ensuring outputs align with brand data.

  • Image Generation Flow:

    The /image endpoint triggers a Lambda that calls Bedrock’s image generation model. The model returns a Base64-encoded result to API Gateway, which delivers the try-on image to the end user. This provides fast, interactive results for shoppers experimenting with looks and items.

  • Visual Search Flow: The /search endpoint activates a Lambda that creates query embeddings and matches them against embeddings in Amazon DynamoDB using cosine similarity. Uploading new images to S3 automatically triggers a Lambda that uses Titan Multimodal Embeddings to update Amazon DynamoDB. Top matches are returned instantly to the user interface, providing seamless visual discovery.

• Catalog & Image Pipelines: Uploading catalog files to S3 invokes a Lambda that ingests documents into Bedrock knowledge bases, updating vector indexes in Amazon OpenSearch Serverless. Uploading product images triggers Titan Embedding pipelines to generate embeddings stored in Amazon DynamoDB or, at production scale, Amzon OpenSearch Serverless. These pipelines keep catalogs fresh, synchronized, and fully searchable.

This design supports multiple immersive features simultaneously. By incorporating Amazon Nova foundational models, retailers extend capabilities with:

• Multimodal Understanding (Lite, Pro, Premier): Process text, image, and video for contextual queries, enabling multimodal recommendations.

• Creative Models (Canvas, Reel): Generate imagery and video such as composites or reels, powering campaigns and social experiences.

• Retrieval-Augmented Generation (RAG): Ground responses in live product and inventory data

• Advanced Features: Handle multimodal queries (e.g., “show me items like this photo”) and enable browser-agent extensions.

This blueprint demonstrates how AWS services interconnect to deliver immersive shopping experiences that are secure, responsive, and easily scalable. It highlights that AWS solutions are not limited to technology—they are enablers of business transformation.

5. Moving from Traditional to Immersive Commerce

Shifting to immersive commerce is a strategic initiative that requires experimentation, measurement, and scaling:

1. Start with a Targeted Pilot: Choose categories where uncertainty is high, such as fashion or home furnishings, and deploy features like try-on or AI stylist. Early wins create internal momentum and deliver measurable ROI quickly.

2. Leverage AWS GenAI Tools: Use Amazon Nova multimodal models coupled with RAG to ensure recommendations remain accurate, contextual, and aligned with live inventory. Nova reduces time-to-market by removing the need to train foundation models from scratch.

3. Design for Scale and Security: Apply serverless design, encryption, moderation, and IAM best practices to meet compliance and performance standards. Align solutions with the AWS Well-Architected Framework for reliability.

4. Iterate and Learn: Continuously track metrics like conversion uplift, engagement duration, and return-rate delta. Employ A/B testing to refine user experience and create a cycle of ongoing improvement.

5. Integrate Omnichannel: Feed digital insights back into CRM systems and in-store experiences to create a seamless journey. In practice, this means a shopper who tries an item virtually receives consistent recommendations in marketing emails and at physical touchpoints.

Encora, an AWS Retail Competency Partner, specializes in designing and operationalizing these immersive solutions. Encora has demonstrated expertise through:

• Building recommendation engines and immersive shopping pilots using Bedrock and Nova.

• Designing secure, high-performance architectures with optimized costs and resilience.

• Delivering POCs quickly and scaling them into enterprise-grade platforms.

• Integrating immersive commerce with omnichannel operations and store systems, ensuring consistent experiences.

With Encora’s proprietary frameworks and AWS’s cutting-edge AI services, retailers reduce risk, accelerate timelines, and ensure business outcomes align with measurable KPIs.

6. Conclusion: Beginning the Immersive Commerce Journey

Immersive commerce is no longer optional; it is becoming a baseline expectation for digital-first consumers. The sooner retailers adopt, the sooner they shape experiences that set the standard for the next decade. Hesitation risks being left behind as competitors capture customer loyalty with immersive features.

A staged roadmap to adoption:

• Phase 1 (0–2 weeks): Identify categories and KPIs with highest impact. Focus on categories like apparel or furniture where fit and context matter most.

• Phase 2 (2–6 weeks): Deploy a pilot such as stylist chat or similarity search for limited products. Prove the concept and communicate results internally.

• Phase 3 (6–12 weeks): Add AI try-on, expand catalog integration, and measure outcomes at larger scale. Use analytics to validate ROI.

• Phase 4 (12+ weeks): Scale across categories, integrate with omnichannel strategies, and harness insights for product planning and marketing.

Call to Action

Executives and architects should initiate immersive commerce pilots immediately. Explore Amazon Nova models, assess targeted features, and collaborate with an AWS Retail Competency Partner like Encora to accelerate deployment.

The future of retail will be defined by immersive experiences that combine creativity, intelligence, and trust. Those who start building now will set tomorrow’s standards in customer experience, operational excellence, and sustained business growth.

About the authors

Gustavo Alejandro Romero Sanchez is a Principal Cloud Solutions Architect at Encora. He delivers guidance on Cloud Security, Generative AI solutions, DevSecOps, and scalable architecture to Encora’s customers.

Prateek Agrawal is a Sr. Partner Solutions Architect with Amazon Web Services. He provides architecture guidance on enterprise cloud adoption, migration, and AI strategy to AWS partners and customers