User Needs & Business Objectives

Process Deep Dive | Vehicle Passport | Stage 1

Meet Nick and Alan

A friend of mine, Nick, is a bit of a car enthusiast. Over just three years, I watched him trade in and purchase three different vehicles—all initiated online. Each time, he ran into the same pain points: friction and frustration, all tied to the trade-in aspect of the transaction. His frustration sparked the investigation below.

Blog posts of Stage 1 AI experiments

Click here for a list of articles covering various AI experiments supporting, replacing and augmenting Stage 1 work efforts.

Nick Patterson

Archetype – Car Buyer (with Trade-in)

Alan Subran

Archetype – Dealer Agent

The Pain Points

In today’s modern world, you can buy and sell cars completely online from start to finish. It’s pretty remarkable. Even with all of the technology that’s currently in place though, the trade-in experience still misses the mark. Let’s take a closer look at Carvana’s current-state trade-in funnel to learn more.

My mantra

“Advocate for users. Serve the business.”

Current-state analysis

Next, I spent a few hours analyzing Carvana’s online purchase funnel, including the trade-in flow. Using Jesse James Garrett’s Visual Vocabulary best practices for flow diagramming, I mapped and visualized the complex conditional logic underlying Carvana’s online digital experience.

Between…

5-10

screens

…required to satisfy Carvana’s trade-in funnel experience

Between…

25-35

unique topics and questions

…necessary to address to satisfy Carvana’s trade-in funnel experience

Between…

~3-8

minutes

…devoted to satisfying Carvana’s trade-in funnel experience

Funnel Entry (License Plate)

⭣

Information Recall

Funnel Entry (VIN)

⭣

Information Recall

Information Hunt

⭣

Information Recall

Step 1: The Basics

⭣

Dynamic Attribute

Static Attribute

Poor Microcopy

User Intent

Step 2: Vehicle Features

⭣

Information Recall

Need to create brand style guide and tone of voice

Step 3: Condition & History (1)

⭣

Smart Car (Not)

Legal & Compliance

Dynamic Attribute

Step 3: Condition & History (2)

⭣

User Explicit

Information Recall

Need to create brand style guide and tone of voice

Service History

Step 3: Condition & History (3)

⭣

User Explicit

Subjective Guesswork

Business Numbers

Business is inseparable from risk. Anticipating customer needs and investing in solutions is often uncertain and high-stakes. As a Product Designer, I see it as essential to understand those risks, empathize with the business context, and design structured solutions that reduce exposure while maximizing results.

Risk and user adoption

Mitigating risk to user adoption

Overall volume

So I asked the questions: “What’s up with vehicle trade-ins, anyway? What sort of numbers are we dealing with here on a national scale?”¹

2016

~16

million

…new and used cars sold through trade-in deals

2024

~15-18

million

…new and used cars sold through trade-in deals

Empathy and early stage research

Primary and secondary research painted an interesting picture of buyer perception regarding trade-in.²³

When asked…

12%

stated

…trade-in activities were top frustration with purchase process

Around…

$1,500

dollars

…per transaction could be saved by not having physical dealerships

Only…

10%

stated

…they completed trade-in valuation activities online

Only…

:26

seconds

…was saved completing trade-in valuation activities online

UX Challenge

Market and user research exposes today’s vehicle purchase challenges. Trying to purchase a vehicle online today is often burdened and intertwined with vehicle trade-in valuation distractions. People are often unable to recall many important trade-in valuation data points (like vehicle trim and associated extras) causing them to guess their way through the digital experience. These burdens make online trade-in valuations inaccurate and a frustrating distraction that interrupts the user’s primary goal – buying their next vehicle.

Fascilitating collabortive, Design Thinking workshops

Click here to learn more about Ideo Labs, cross-functional, collaborative workshops.

Future-state experience outcomes

Nick – Vehicle Owner / Buyer (with Trade-in)

Improving Nick’s life might sound something like this…

Alan – Dealer Agent

Improving Alan’s life might sound something like this…

How might we statements

➤ How might we exploit emerging technologies to turn smart vehicles into active agents along the buy, sell and trade-in transaction funnels?

➤ How might we personalize buy, sell and trade-in funnel experiences overall that engage human beings in new ways?

➤ How might we do a better job of disconnecting the vehicle trade-in funnel from the vehicle purchase funnel; reducing the friction users find when both funnels are combined?

Strategic intent

➤ Untangle the dependency between buying and trade-in to reduce funnel abandonment

➤ Use AI/automation to create parallel, optimized experiences for both flows

➤ Personalize interactions based on intent signals (e.g., is the user buying first or offloading a vehicle?)

Solution hypothesis

➤ Achieving a richer, more personalized car buying experience would likely mean leveraging emerging technologies to collect, collate, interrogate, integrate, track and broadcast every detail of a vehicle’s attributes and activities (static and dynamic) from cradle-to-grave.

Clickable Prototype

I vibe-coded a potential high-fidelity clickable native iOS MVP prototype that could be used for internal alignment and proof-of-concept validation.

➤ Nick buys a new car from Alan.

➤ Alan provides Nick with a vehicle passport via QR code. Nick now has all of the vehicle’s static and dynamic data points in an easy-to-use standardized digital certificate.

➤ Nick drives the car for 2 years. During this time, the car is serviced. As time passes, Nick forgets the extras, trim and minor details about the car’s service history and profile. But that’s ok, because Nick’s Vehicle Passport keeps up with it all.

➤ After 2 years, Nick is now interested in getting into a new car. He uses the Market feature of the Vehicle Passport app to identify the best time to trade up and schedules an appointment with Alan. His Vehicle Passport automatically generates an accurrate valuation and sends the recommendation to Alan with the in-person appointment request. Trade in handled. Nick and Alan can focus on the purchase effort.

Business Objectives & Strategic Themes

Based on the available market analysis and the user research recommendations, we have determined one of this year’s strategic themes is to Decouple and Optimize to Convert. Delivering on this strategic theme will likely address the friction caused by intertwined purchase and trade-in flows, and will likely support a disruptive shift toward simplified, faster, and more personalized trade and buy funnel experiences. This strategy is likely to reduce cognitive load, speed up decision-making, and improve customer confidence. The proposed UX vision is consistent with the organization’s Mission, Vision and Values and hereby adopted.

The Scientific Method

The word ‘likely‘ is used significantly within this section — it’s not by mistake. Click here to watch this brief video on the Scientific Method by Dr. Richard Feynman (Nobel).

Guiding principles

The business is prepared to fund and support concrete design solutions that adhere to and represent the following guiding principles:

➤ Meet customers where they are

Our customers are constantly moving from device to device and from channel to channel. And they have very different needs along their journeys. With so many moving parts, the only way to deliver highly relevant interactions is to bring together everything we know about them: how they like to communicate, where they like to shop, and what interests they have. Meet them where they are and they’ll have no reason to go anywhere else.

➤ Shorten path to value

The quickest path to business value starts with knowing what our customers want to accomplish, and then helping them get there. After all, when we our help customers reach their own goals — they’re much more likely to take actions that help us reach ours.

➤ Let AI sweat the small stuff

Artificial intelligence and machine learning should be implemented sensibly. Exploit the available time, money and resources to reimagine the experience exploiting these technologies where they make sense to do so. Use emerging technologies where they demonstrate stability and true value-add potential aimed at engaging every customer on a deeply personal level.

Key Performance Indicators

KPI 1:
Decrease

by 5%

Buyer Frustration

…that users have expressed experiencing with trade-in

KPI 2:
Increase

by 10%

Online Purchase
Transactions

…which is the primary objective for both users and business

KPI 3:
Decrease

by 30%

Time-on-Task

…users want to spend time driving a new vehicle… not purchasing one. Let’s focus on getting them into their next vehicle instead of the steps that go into procuring one

Cox Automotive, 2019. 2019 Car Buyer Journey Study. [pdf] Cox Automotive. Available at: https://www.coxautoinc.com/wp-content/uploads/2019-Car-Buyer-Journey-Study-FINAL-6-11-19.pdf [Accessed 2 July 2025]. ↩︎
Carvana Carvana Careers: Between Two Erns [Online Video]. YouTube. Available at: https://www.youtube.com/watch?v=sp5YOPlSBuA. ↩︎
Cox Automotive, 2019. 2019 Cox Automotive Car Buyer Journey Study – Media Deck. [pdf] Cox Automotive. Available at: https://www.coxautoinc.com/wp-content/uploads/2019-Cox-Automotive-Car-Buyer-Journey-Study-Media-Deck.pdf [Accessed 2 July 2025]. ↩︎

Archetype: Vehicle Buyer (with Trade-in)

Persona: Early Adopter / Frequent Trader

Name: Nick Patterson

Actual user verbatim communicated using HeyGen

Demographics

Age:

Occupation:

Personal Wealth Mgmt

Income:

$195K annually

Location:

Savannah, Georgia

Education:

Masters in Finance

Status:

Married

Vehicle Trading Behavior

Frequency:

Every 12-15 months

Motivation:

Enjoys latest tech, vanity

History:

3 vehicles in 3 years

Spends:

$85K – $125K

Prefers:

New and Pre-owned

Primary Frustrations

Trade-in/Purchase Coupling:
Forced to navigate complex dual flows simultaneously

Inaccurate Valuations:
Online estimates don’t match reality (part of 40% who research online, 10% who get actual offers gap)

Information Overload:
40-56 clicks through Carvana-style flows while trying to buy AND trade

Paperwork Burden:
Spends 2+ hours at dealerships on documentation

Memory Gaps:
Can’t recall specific trim details, options, maintenance history for trade-in

Primary Goals

Separation of Concerns:
Trade current vehicle on its merits, buy next vehicle on its merits

Accurate Trade Valuations:
Real-time, data-driven assessments based on actual vehicle condition

Purchase Efficiency:
Complete more transaction steps online, minimize dealership time

Information Transparency:
Access to complete vehicle history and predictive insights

Digital & Technology Profile

Early Adopter:
First to try new automotive apps and connected car features

Device Usage:
Heavy multi-device user (smartphone primary, desktop for research, tablet for comparisons)

Connected Vehicle Enthusiast:
Actively uses vehicle apps, OTA updates, remote features

AI Comfort Level:
High – regularly uses AI tools in work and personal life

Data Sharing Attitude:
Privacy-conscious but pragmatic – willing to share vehicle data for tangible value

Technology Adoption

Vehicle Data Collection:
Willing to share driving patterns, maintenance data, location for accurate valuations

AI-Driven Insights:
Wants predictive analytics on vehicle value, optimal trade timing

Automated Processes:
Interested in “smart car selling itself” concept

IoT Integration:
Uses connected features, comfortable with vehicle data APIs

Archetype: Dealer Agent

Persona: Experienced Sales Agent

Name: Alan Subran

Actual user verbatim communicated using HeyGen

Demographics

Age:

Occupation:

Dealer Sales Agent

Income:

$125K annually

Location:

Savannah, Georgia

Education:

Bachelors in Business

Status:

Married

Vehicle Trading Experience

Frequency:

3-4 / mo

Motivation:

Repeat business

History:

13 years

Avg Sale:

$55K – $75K

Prefers:

New and Pre-owned

Primary Frustrations

Trade-in/Purchase Coupling:
Forced to navigate complex dual flows simultaneously

Primary Goals

Separation of Concerns:
Trade current vehicle on its merits, buy next vehicle on its merits

Design Thinking

The core ideas behind design thinking — such as empathy, iteration, and human-centered problem solving — trace back to design disciplines in the 1960s–1980s, particularly in architecture, industrial design, and engineering. IDEO, led by people like David Kelley, was pivotal in applying design thinking to business and technology in the 1990s and early 2000s. They helped package design thinking as a repeatable process that could be used by non-designers:

Empathize → Define → Ideate → Prototype → Test

The Deep Dive, 2009. The Deep Dive. YouTube, 14 May 2009.

Mitigating Risk to User Adoption

Time and money don’t grow on trees—and validating business and design decisions with real users can be resource-intensive. But not every project carries the same adoption risk. When Amazon introduced the Alexa Show, it was introducing a new interaction paradigm—voice-first computing—requiring extensive user research to ensure acceptance. Contrast that with a bank launching a feature that allows car loan payments from third-party institutions—a useful update, but one that builds on familiar behavior. The five models below outline different approaches to design validation, from blind guessing to user-informed rigor. AI can help streamline each, but it can’t replace the judgment needed to match the method to the risk.

Rapidly generate hypotheses, wireframes, or user scenarios.
Analyze large datasets for behavioral patterns.
Assist with survey synthesis or usability test tagging.
Simulate some user behavior (in limited contexts).

Accurately judge the emotional, cultural, or contextual nuances of user behavior.
Replace real-world exposure to novel paradigms (e.g., Alexa’s voice interface).
Understand unspoken needs or hesitations that come through in qualitative research.
Decide how much validation is necessary based on risk, regulation, or brand implications.

When the Designer only considers themselves for the design decisions.

When no consideration. isgiven. to users. Only to technology and business objectives.

When a solution uses only existing research to make design decisions.

When the necessary time and money required to conduct activity-based user research in order. to mitigate risk is made available.

When the necessary time and money required to conduct experienced-based user research. inorder to mitigate risk is made available.

Rapidly generate hypotheses, wireframes, or user scenarios.
Analyze large datasets for behavioral patterns.
Assist with survey synthesis or usability test tagging.
Simulate some user behavior (in limited contexts).

Accurately judge the emotional, cultural, or contextual nuances of user behavior.
Replace real-world exposure to novel paradigms (e.g., Alexa’s voice interface).
Understand unspoken needs or hesitations that come through in qualitative research.
Decide how much validation is necessary based on risk, regulation, or brand implications.

AI Experiments

User Needs & Business Objectives

Drafting a PRD with Claude and Perplexity (Pro)

I’ve been exploring a problem space in the automotive industry for a few years now—long before AI entered the spotlight. What started as a client-led Design Thinking project that ultimately stalled became a personal pursuit. After the client engagement ended, I continued the investigation on my own, initially applying classical product design methods to draft a PRD. Recently, I’ve returned to the project, now leveraging AI to push the work further.

Giving Users a Voice: Avatar Generators for Presenting User Verbatim and Insights

Nothing will ever beat talking to human beings. Not even AI. But, lately I’ve been exploring new ways to bring user voices into the room—especially when the room is full of stakeholders. And not just quotes on a slide. I mean really bringing users to life.