To design a highly intuitive and efficient vehicle listing flow that minimises seller friction, reduces errors, and maximises the speed of inventory using the Lovable.io platform.
Skills Used
UX Design & CRO, Information Architecture, Rapid Prototyping
Skills Used
UX Design & CRO, Information Architecture, Rapid Prototyping
Skills Used
UX Design & CRO, Information Architecture, Rapid Prototyping
Stack
Lovable.io (AI Agent, Visual Editor), Figma
Stack
Lovable.io (AI Agent, Visual Editor), Figma
Stack
Lovable.io (AI Agent, Visual Editor), Figma
Challenge
The previous inventory process suffered from high seller drop-off due to complexity and rigid structure. The core issues we addressed were:
• Inventory Overload: Handling six distinct inventory types (Vehicles, Chargers, etc.) under confusing workflows.
• Inefficient Data Entry: Lack of options for high-volume dealers, forcing large, error-prone manual input.
• Form Fatigue: Long, static forms and complex fields that led to frustration and inaccurate data.
Approach
We created an intelligent, adaptive listing flow that customised the experience based on user needs. Our strategy focused on simplifying the user journey through progressive disclosure and smart automation. This was rapidly implemented using the AI-powered capabilities of Lovable.io, which allowed us to focus purely on UX refinement.
By utilising the Lovable.io platform, we were able to run faster design cycles, generating the base application with simple prompts and then fine-tuning the critical flow visually.
Smart Dual Workflow
This strategy immediately guides the seller to the most efficient path by allowing them to choose between Bulk Upload (Excel Template) for high-volume inventory or Manual Entry (Guided Flow) for step-by-step submission. This choice ensures maximum efficiency, as the bulk path supports instant upload while the manual path prioritizes speed and guidance for single item listings.
Adaptive, Data-Driven Design
To eliminate form fatigue, the flow uses a core VIN Auto-Population (Step 3), which automatically populates most basic vehicle specifications using verified NHTSA. Furthermore, the Inventory Details screen dynamically uses Conditional Logic, showing only relevant tabs and fields based on the initial inventory type, simplifying data entry for every user.
Key Takeaways
The adaptive and guided design, rapidly executed using Lovable.io, transformed a previously complex process into a highly efficient workflow:
• 40% Reduction in the average time taken to publish a new listing.
• 55% Decrease in form-related errors, driven by improved inline validation.
• 30% Increase in the rate of successful listings published (completed flows vs. started flows).
Creative Credits
Agency → SHAED.AI
Senior Designer → Narendra Prasath
