Defining the Role of AI in a National Furniture Brand’s Digital Experience
Explored and framed opportunities in visual search, personalization, AR, and conversational agents to elevate the room shopping journey across mobile, in-store, and digital touchpoints.
The Challenge
Furniture shopping is overwhelming. Customers struggle to visualize products in their space, compare styles, and feel confident in big-ticket purchases. The brand needed to define where AI could create meaningful value by helping customers explore, discover, and decide while keeping the experience simple and clear.
Working with the product team, we identified:
Overwhelming choice: Thousands of products with limited guidance created decision fatigue
Confidence gap: Users lacked tools to visualize pieces in context, leading to hesitation on purchases
Retail misalignment: Online discovery was not always connected to in-store availability or promotions
The business impact: High cart abandonment rates, increased returns due to mismatched expectations, and missed revenue from customers who couldn't visualize products in their homes.
The opportunity: Leverage AI to help customers visualize furniture in their space, get personalized recommendations, and make confident purchase decisions while connecting the online and in-store experience.
Project Details
My Role: Lead Product Designer
Team: Product Manager, Product Designer, Retail Stakeholders, AI/ML Engineers
Scope: Product strategy, AI feature definition, experience design & prototyping, user testing & iteration, cross-functional collaboration, design systems integration
Timeline: 6 months
Scale: $2.5B+ annual revenue retailer, 200+ showrooms across 10+ states, iOS shopping app serving millions of customers annually
Tools: Figma, FigJam, UserTesting.com
Cross-Industry Research on AI Tools
We began by looking beyond our category, studying how AI was being used in adjacent industries to uncover useful patterns and design metaphors. This helped frame what “smart” could feel like in a furniture shopping context.
Audited cross industry apps and tools across fashion, fitness, and interiors
Mapped use cases by AI behavior type (generation, personalization, recommendation)
Identified interaction patterns that could inspire low-friction entry points
visual search
Personalization through style preference quizzes
Conversational AI
Virtual staging tools that impress and delight
Customer Storyboarding
This storyboard illustrates three distinct customer personas and how they engage with the home design experience, each with unique needs, concerns, and goals. The framework maps their journey from initial mindset to the features that best support them.
Flow Mapping
Once we had directional clarity, we mapped the full end-to-end experience. This included integrating new entry points, handling edge cases, and extending the visual system to reflect the tool’s dynamic logic.
Defined user flows for first-time use, returning users, and fail states
Created modular screens that flexed based on user input and backend data
Updated visual system to accommodate AI-specific UI components and guidance cues
AI-Driven Shopping Flows
From early concepts, we moved into defining the core product flows that would bring AI to life in a shoppable experience. These flows explored how customers could search naturally, save favorites, and purchase entire room sets, while ensuring everything stayed aligned with retail inventory.
The personalized home screen acted as a central hub for exploration, adapting to each shopper’s taste and history. AI-driven modules surfaced inspiration, curated rooms, and saved favorites in one unified view.
AI-powered search transformed product discovery from keyword matching into intent recognition. Customers could describe what they needed in their own words and see results organized into meaningful sets.
“Shop This Room” turned styled inspiration into an actionable shopping flow. Instead of browsing disconnected SKUs, customers explored complete rooms and tapped directly into product details, pricing, and availability.
Favorites gave shoppers a way to pause decision-making without losing momentum, helping reduce abandonment and drive return visits. By tying saved items back to live inventory, customers always knew what was available when they came back.
User Testing & Design Validation
To validate usability and ensure alignment with user expectations, a series of moderated testing sessions were conducted, focusing on key features and flows. Testers navigated through a prototype, completing tasks while providing live feedback on functionality and design. Tester qualifications included age, region, familiarity with the Rooms To Go brand, and recent experience shopping for furniture.
In the first round, five testers evaluated the prototype, and their feedback was synthesized to inform design updates. The updated prototype was then tested by four additional users to validate the changes and identify any remaining concerns.
Final Testing & Design Delivery
After a second round of user testing confirmed the direction, we finalized the designs, documented the system updates, and delivered everything to the client—complete with flows, patterns, and annotations for integration into their existing design system. The outcome was a fully realized AI-assisted experience that fits naturally within the Clients mobile app while opening doors for future personalization at scale.
Customer Validation
User testing showed that shoppers felt more confident when AI suggested complete rooms rather than single items. Natural language search reduced frustration and helped customers find products faster.
Business Alignment
By tying AI flows to real inventory and promotions, we created a seamless bridge between online discovery and in-store sales. This alignment positioned AI as both a shopper benefit and a retail growth driver.
Launching AI search, shoppable rooms, and favorites delivered immediate impact on engagement and conversion. These flows laid the foundation for future enhancements like expanded personalization.
Quick Wins
Delivering the Room Builder experience required balancing simplicity with inspiration, guided by user feedback, retail alignment, and on-the-floor sales insights. The result was a set of flows that helped customers shop more confidently while creating new opportunities for the business.
The most rewarding outcome? Shoppers felt empowered to visualize and plan their spaces, while in-store teams gained a stronger foundation for customer conversations. Early testing showed faster product discovery, higher engagement with shoppable rooms, and stronger intent to purchase from saved favorites.
Reflection
3
Distinct product vision tracks developed to meet key business goals: in-store integration, self-service utility, and inspiration-driven browsing.
6
Future-forward feature concepts ranging from AI decor quizzes to AR room builders, UGC-style galleries, and smart post-purchase delivery tracking.
156M+
Estimated app market opportunity based on analysis of top competitors’ download volume used to support ASO and product roadmap prioritization.