Transformed the way users shop for curtains with AI and digital humans
Transforming an urban couple's home redecoration journey
Conversational AI and digital human assistant transforms the urban couple's home redecoration journey, providing personalised recommendations, a try-and-buy feature, and curated mood boards, by ensures a seamless online-to-offline transition, this redefined experience seamlessly merges AI-driven design with customer-centricity to enhance the couple's quest for a stylish home.
Success
After launching the MVP, we conducted user testing over 2 sprints with 100+ users, as a result,
Time spent on the platform has gone up from 2.2 min to 6.5 mins.
The 73% average user interact with digital human assist
The bounce rate has decreased to 35%.
ROLE & RESPONSIBILITIES
The Challenge
Urban couples face big challenges in home design or renovation, busy schedules make it hard to visit experience centers, and navigating websites, choosing products, and finding information online often add to the frustration, switching between online browsing and customer support is complicated, and clear product guidance is often missing.
Existing User Journey: Steps Through the End User’s Perspective
Bridging Insights and Actions; Key DeCISIONS
Ideas and information were systematically organised and grouped using affinity mapping to reveal how users categorised the collected data.
This collaborative approach allowed us to:
By asking the right questions and observing user behavior, we gained a deeper understanding of their pain points and needs.
Witnessing user struggles firsthand fostered a shared understanding and commitment to creating a better experience.
Key decisions factors
Diverse preferences indicated the need for a broad catalog but highlighted the importance of focusing on top-performing trends.
Challenges in balancing customization costs with operational efficiency.
Increasing mobile usage dictated the need for mobile-first design.
Usability insights emphasised the importance of safe and multimodal intuitive design for conversation.
Strong dependency on online-first approaches, requiring synchronization between online catalogs and in-store availability.
By blending qualitative and quantitative methods with design thinking principles, uncovered valuable insights that truly resonate with both users and business needs, this thoughtful approach helped us better understand user pain points and find practical opportunities to stand out and innovate, ensuring our solutions are both impactful and meaningful.
CONCEPTUALISATION
A pop-up interface was created for users to interact with a digital human assistant, acting as a sales rep, it guides users to suitable products, suggests color, texture, and material options, and helps with informed choices, store directions, and a seamless online-offline experience.
Crafting a User Interface Compatible Across Screens
Though desktop engagement was minimal, ensuring compatibility with iPads was key, early iterations focused on reducing clutter and refining hierarchy with clear headings, while adapting for iPads through brand-specific typography, colors, and illustrations.
REFECTION
Yuna Assist, a conversational AI digital human, has the potential to make a significant impact on stakeholders and users.
Users determine how specific the problem is, In this experience, I learned the importance of users in defining the problem's specificity, understanding this aided in brainstorming diverse solutions. It became clear to me how a precise problem statement promotes exploration of broader solution options, ultimately leading to enhanced creativity and increasing the chance of finding effective solutions.
Evaluating user multimodal interactions in AI design: This project has deepened, I learned valuable lessons while evaluating user multimodal interactions, as I analysed how individuals engaged with conversational interfaces like chatbots and voice assistants, I discovered how crucial this process is. It directly shaped my design approach, providing insights that allowed me to craft intuitive and user-friendly interactions tailored to diverse user preferences and behaviours.
Feedback loops are crucial in conversations: I discovered the vital role of feedback loops in conversations, as systems gathered real-time feedback from users, I realised the importance of meaningful dialogue. It became evident that dynamic interfaces were necessary to facilitate such interactions effectively. Learning to leverage this feedback loop was instrumental in refining and optimising designs, ultimately enhancing user experiences.
Next project:
EFF Application: real-time data, smarter decisions for pilots
Users determine how specific the problem is, In this experience, I learned the importance of users in defining the problem's specificity, understanding this aided in brainstorming diverse solutions. It became clear to me how a precise problem statement promotes exploration of broader solution options, ultimately leading to enhanced creativity and increasing the chance of finding effective solutions.
Evaluating user multimodal interactions in AI design: This project has deepened, I learned valuable lessons while evaluating user multimodal interactions, as I analysed how individuals engaged with conversational interfaces like chatbots and voice assistants, I discovered how crucial this process is. It directly shaped my design approach, providing insights that allowed me to craft intuitive and user-friendly interactions tailored to diverse user preferences and behaviours.
Feedback loops are crucial in conversations: I discovered the vital role of feedback loops in conversations, as systems gathered real-time feedback from users, I realised the importance of meaningful dialogue. It became evident that dynamic interfaces were necessary to facilitate such interactions effectively. Learning to leverage this feedback loop was instrumental in refining and optimising designs, ultimately enhancing user experiences.
Next project:
EFF Application: real-time data, smarter decisions for pilots