UX
UI
Vibe Code
I explored how AI could simplify the tire shopping journey by replacing traditional filters and product searches with a more conversational, guided experience. The goal was to create an experience where customers could describe what they need naturally and receive personalized recommendations based on their vehicle, driving habits, and preferences.
Buying tires can be an overwhelming experience. Customers often need to know technical details like tire size, vehicle compatibility, and tire categories before they can even begin comparing options.
I wanted to explore how AI could remove some of that friction by helping customers navigate the decision-making process instead of forcing them to learn the product category first.
Traditional ecommerce search works well when customers already know what they’re looking for, but tires are often a high-consideration purchase. Customers may know they want “something quiet,” “good for snow,” or “better for off-road driving” without knowing exactly which product fits their needs.
The opportunity was to create an experience that understands intent, asks helpful questions, and guides customers toward the right choice.
I designed the experience around a conversational flow that balances guidance with flexibility. Instead of a traditional search bar, users can describe their needs naturally, whether they know their vehicle details, tire size, or simply what type of driving they do.
The AI experience was designed to support follow-up questions, recommendations, comparisons, and decision-making moments throughout the journey.
A major focus was designing how the AI responds when users don’t provide perfect information. Real customers may enter incomplete vehicle details, ask follow-up questions, or change direction mid-conversation.
I created conversation patterns to handle unsupported inputs, clarify missing information, and keep users moving forward without creating dead ends.
Through testing the prototype, I identified areas where the AI experience needed improvement, especially around understanding follow-up questions and maintaining context throughout a conversation.
I refined the experience to make recommendations feel more natural, relevant, and conversational, allowing users to ask questions like “Which one do you recommend?” or “What’s the best value?”.
