Case study
New Car Pricing
Dealers priced new cars across scattered tools, and competitors did it better. I led the research and design for one pricing experience in ACV MAX, then tested it with 8 dealer groups. It averaged 4.2 out of 5 for adoptability, one dealer called it "1000 times better than what we have today," and phase one shipped with immediate adoption.
In 60 seconds
- The problem: Pricing a new car in MAX meant juggling rebates, accessories, and pricing rules that were scattered, manual, or missing. Many dealers used a competitor, vAuto, for new cars instead.
- What I did: I designed a single pricing experience for new cars, then led 8 research sessions with dealer groups to test it. In every session, we compared three things side by side: MAX today, vAuto, and my prototype.
- The result: The prototype averaged 4.2 out of 5 for adoptability, with 3 of 8 groups rating it a 5. The research also showed exactly where MAX still had to catch up, and those findings became the plan for phase one, which shipped, including the rebate calculator, and was adopted by dealers right away.
The problem
New car pricing isn’t one decision. A dealer starts from the invoice or the sticker price, applies manufacturer rebates, adds accessories, follows manufacturer and state rules, and then makes sure the price shows up correctly on their website and every listing site.
In MAX, the pieces for that job were scattered or missing. Rebates, accessories, and pricing rules each lived in different places or required manual work, so dealers either did extra work or used a competitor instead.
I framed the work around two people:
- The general manager: “I need clear, central visibility into discounts, rebates, and accessories so I can keep margins healthy and stay competitive.”
- The new car manager: “I need to quickly apply and adjust pricing rules, rebates, and accessories, for one car or many, without jumping between tools.”
What I designed
I designed one place to price a new car: a pricing calculator on the vehicle page that shows every part of the price together (the starting price, discounts, rebates, and accessories) and flags when a price drops below invoice. Around it I designed a rebate manager that shows which rebates the system applied and which the dealer changed, with a way to reset back to the system. I also designed a price history that records who changed a price, when, and from what to what.

How I tested it
I led 8 mixed-methods sessions with dealer groups, each 30 to 66 minutes long. The groups ranged from single stores to some of the largest dealer groups in the country. Each session combined moderated usability testing of the prototype with task analysis. The priorities were the pricing calculator and the rebate views, with mobile navigation as a secondary check.
Every session compared three things apples to apples: MAX as it was, vAuto as dealers used it, and the prototype. That meant we weren’t just asking “do you like this?” but “is this better than what you’d use instead?” Every finding was tied to video evidence, and each group got an adoptability score.

How it scored
| Session | Score |
|---|---|
| Session 1 | 3.0 |
| Session 2 | 3.5 |
| Session 3 | 4.5 |
| Session 4 | 3.5 |
| Session 5 | 5.0 |
| Session 6 | 5.0 |
| Session 7 | 4.0 |
| Session 8 | 5.0 |
Two of the three lowest scores had less to do with the design than with rules: manufacturer and state restrictions on how those groups are allowed to price. That became one of the most important findings.
"1000 times better than what we have today."
Dealer group, session 7
"This looks like vAuto was Windows XP. This is Windows 11. Much fresher."
New car manager, Ford dealership
What dealers taught us
Across all eight sessions, the same themes kept coming up:
- Rules have to apply to cars that haven’t arrived yet. Dealers don’t want to re-price every new car by hand. Pricing rules, fees, and accessories should apply automatically to incoming inventory.
- Trust comes from a clear history. “The more we know about what’s being changed and who’s changing it and when they changed it, the better.” Every group wanted to see who changed a price, when, and from what to what.
- Compliance shapes everything. Some manufacturers only allow the sticker price. Some states require accessories as separate line items. Finance incentives can’t be in the advertised price. The tool has to know these rules, not just leave dealers to remember them.
- Show the profit, not just a badge. “Below invoice” is a warning. Dealers wanted the actual dollar amount, including accessories and upfits.
- Speed at scale. Groups with hundreds of new cars need to price every F-150 at once, not one year and one trim at a time.
- Use dealers’ words. “Internet price,” not “advertised price.” “Conditional offers,” not “cash.” One label per idea, used the same way everywhere.
Where the prototype won, and where it had to catch up
Clarity and trust
- A modern, cleaner interface dealers found easier to use
- One screen for the whole price
- A clear price history and audit trail
- Rebates clearly marked as system-managed or dealer-changed
Speed and reach
- Pricing many trims and years at once
- Syncing prices and rebates to dealer websites
- Enforcing minimum advertised price rules
- Comparing prices against local competitors
That honest split was the most useful thing the research produced. It told the team exactly which gaps would win or lose dealers.
What changed
- For dealers: Phase one shipped, including the rebate calculator, and dealers adopted it immediately, with positive results from the start.
- For the roadmap: The findings became the plan for phase one in Q1 2026. I carried the dealer insights into the backlog and acceptance criteria, then ran an alignment workshop and worked with account managers on the next round of research.
- For the product: Clear priorities for closing the gap: rules that apply to incoming cars, a price history, profit in dollars, compliance guardrails, and bulk pricing.
- For the team: A research setup other projects could reuse: the same prototype in every session, a three-way comparison with the competitor, video evidence for every finding, and a score for every group.
What I took away
Testing against the competitor, not just against nothing, changes the conversation. “Do you like it?” gets polite answers. “Would you use this instead of what you use now?” gets the truth, including the parts that are hard to hear.
And a low score isn’t always a design problem. Two of the lowest scores came from dealers whose rules limit how they can price at all. That insight pointed to one of the biggest opportunities: making the tool compliance-aware.