Price Alert
The fastest growing lead type
Project Overview
My role
Senior Product Designer
Team
Product Manager
Designer (Me)
Developers (3)
Technical Integration Manager
Timeframe & Scope
3 months
Mobile-first, Desktop
Outcome
The feature became AutoUncle’s fastest-growing lead type
Context & The Problem
Price Alert is a feature designed to notify dealership customers the moment a vehicle they are interested in drops in price. AutoUncle recognized the need to integrate this feature into their third-party website modules in an intuitive, frictionless way.
While price tracking is a staple in traditional e-commerce, the car-buying journey often lacked this transparency. We identified a missed conversion gap: users were frequently "window shopping" for vehicles they couldn't yet afford, but had no way to stay connected to those listings. Without an automated way to monitor price drops, these high-intent leads were churning instead of being nurtured into active buyers.
Ideation and Iteration
The design process went through many rounds of iteration, starting with low-fidelity mockups and evolving into high-fidelity prototypes.
Throughout this phase, I worked closely with my project manager, developers, and company stakeholders. We followed a feedback-driven process, using insights from user interviews as the foundation for our design decisions.
Challenges
Designing this feature came with several challenges.
One key challenge was making the interaction around setting a price alert feel clear and intuitive. Specifically, when the default option “On any price drop” is selected, users needed to understand that they would be notified even if the price drops by just one unit, and that no further interaction is required.
Another challenge came with the second option, “When the price gets under.”
Here, we wanted users to understand that the section refers to how likely it is that a dealer will accept the price they’re setting. To support this, we used a colored gradient to visually represent the likelihood.
However, in some rare cases, users misunderstood the gradient. Instead of interpreting it as higher likelihood when closer to the market price, they assumed the bar should get greener the cheaper the price was, essentially reading it in reverse.
User Research & Validation
I led the discovery track by organizing and conducting user research sessions. This included recruiting participants, scheduling sessions, preparing agendas, taking notes, and recording sessions with participant consent.
Each design iteration was tested with real users through interactive prototypes. These sessions helped us validate our assumptions and improve the feature step by step. With every session, we gained new insights that made the experience more intuitive and the feature more desirable.
The user research sessions helped us address the challenges stated above, with misconception rates being very low by the end of our iteration cycles.
Result
Price Alert became a strong product-market fit. It is now AutoUncle’s fastest-growing lead type and helps keep users engaged with cars they are genuinely interested in.
Dealers value the quality of leads it generates, and the feature has also become a major asset for the sales team. Even new team members are able to close deals more easily thanks to the value it brings.
