Designing a clearer way for dealership teams to identify acquisition opportunities across the service appointment lifecycle and act on the signals that matter most.
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Dealership teams lacked a clear way to identify which service customers were strong acquisition candidates. Relevant information existed across systems, but decisions were often reactive and depended on customers expressing interest first.
I designed a centralized dashboard structured around the service lifecycle so teams could surface high-potential opportunities, understand why a customer was being prioritized, and take action at the right point in the visit.
I combined user interviews, workflow analysis, and AI-assisted synthesis to understand upgrade intent, dealership behaviors, and where acquisition opportunities were being missed.
Conversations with car buyers explored upgrade intent, decision triggers, and how service visits influence willingness to consider selling or trading a vehicle.
I examined dealership service processes to identify current behaviors, gaps, and moments where acquisition opportunities could be missed.
AI-supported synthesis helped organize qualitative findings and identify recurring themes and opportunity areas across the research.
The research pointed to a decision-support problem. Advisors had useful customer and vehicle information, but the workflow did not surface it in a way that supported quick interpretation.
Teams often waited for explicit customer interest rather than receiving a prompt that a service customer might be open to selling or upgrading.
Vehicle age, mileage, service frequency, and similar indicators were available but not surfaced together for fast interpretation.
Service advisors manage multiple customers at once, leaving little time to review detailed information or manually connect signals.
“When I’m bringing my car in for service, I’m already thinking about how much it’s costing me. If someone made a good offer, I’d at least consider it.”
“I’m usually in a rush during service appointments. Unless someone brings it up, I’m not going to go out of my way to ask about trading in.”
I mapped the current service drive experience across the appointment lifecycle to identify moments where better visibility or guidance could improve decision-making.
Support quick judgment by surfacing the right customer and vehicle signals at the point when an advisor can realistically act on them.
The storyboard helped connect the dashboard to the real-world workflow, showing when an advisor might notice an opportunity, interpret the supporting signals, and use that information to guide a customer conversation.
The wireframes explore how opportunity signals, customer information, and next actions could be prioritized without overwhelming advisors who are already working under time pressure.
Portfolio note: These wireframes are adapted and recreated from earlier project work to communicate the core concepts and workflows without using proprietary designs. High-fidelity production designs are therefore not included.
Wireframes and prototypes were reviewed with product stakeholders and subject matter experts familiar with dealership service operations. The goal was to assess whether opportunities appeared at useful moments and whether the information hierarchy supported fast decision-making.
The three-stage workflow aligned with how service appointments are managed and provided a clear structure for organizing opportunities over time.
Opportunity signals needed stronger context so advisors could quickly understand why a customer was being prioritized and what action to take next.
The dashboard needed to do more than flag an opportunity. It also needed to explain the signal clearly enough to support confident action.
Stakeholder feedback highlighted several opportunities to make the experience more useful across different dealership roles and to support the full acquisition workflow.
Introduce clearer opportunity scoring and provide more context behind the signals that cause a customer to be flagged.
Add customizable filters and views, along with more tailored conversation prompts and action recommendations.
Explore automated follow-up, real-time alerts for high-value arrivals, and performance tracking from service opportunity to acquisition.
This project shifted my thinking from designing individual interfaces to designing a system that supports decisions across a time-based workflow. It also helped me explore how AI-assisted signals can complement human judgment when the goal is to make complex information easier to interpret and act on.