Service Drive System
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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Turn scattered service signals into clearer acquisition opportunities.
Problem
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.
Design direction
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.
Understand the customer and dealership workflow
I combined user interviews, workflow analysis, and AI-assisted synthesis to understand upgrade intent, dealership behaviors, and where acquisition opportunities were being missed.
1:1 Interviews
Conversations with car buyers explored upgrade intent, decision triggers, and how service visits influence willingness to consider selling or trading a vehicle.
Workflow Analysis
I examined dealership service processes to identify current behaviors, gaps, and moments where acquisition opportunities could be missed.
AI-assisted Synthesis
AI-supported synthesis helped organize qualitative findings and identify recurring themes and opportunity areas across the research.
The right signals existed, but they were difficult to use in the moment.
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.
Decision-making was reactive
Teams often waited for explicit customer interest rather than receiving a prompt that a service customer might be open to selling or upgrading.
High-value signals were underused
Vehicle age, mileage, service frequency, and similar indicators were available but not surfaced together for fast interpretation.
Time pressure limited analysis
Service advisors manage multiple customers at once, leaving little time to review detailed information or manually connect signals.
Customer perspective
“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.”
Customer perspective
“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.”
Map where opportunities are lost across the service journey
I mapped the current service drive experience across the appointment lifecycle to identify moments where better visibility or guidance could improve decision-making.
Key opportunity
Support quick judgment by surfacing the right customer and vehicle signals at the point when an advisor can realistically act on them.
Explore how the dashboard fits into a real service visit
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.
Structure the experience around fast interpretation and action
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.
Review the workflow with product stakeholders and domain experts
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.
What worked
The three-stage workflow aligned with how service appointments are managed and provided a clear structure for organizing opportunities over time.
What needed refinement
Opportunity signals needed stronger context so advisors could quickly understand why a customer was being prioritized and what action to take next.
Evaluation takeaway
The dashboard needed to do more than flag an opportunity. It also needed to explain the signal clearly enough to support confident action.
Extend the system from identification to action and measurement
Stakeholder feedback highlighted several opportunities to make the experience more useful across different dealership roles and to support the full acquisition workflow.
Prioritization + Explainability
Introduce clearer opportunity scoring and provide more context behind the signals that cause a customer to be flagged.
Role-based Support
Add customizable filters and views, along with more tailored conversation prompts and action recommendations.
Automation + Measurement
Explore automated follow-up, real-time alerts for high-value arrivals, and performance tracking from service opportunity to acquisition.
Designing a decision-support system, not just a dashboard.
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.