CPO Wizard

AI-powered intelligence platform that helps Certified Pre-Owned car buyers make informed purchasing decisions through predictive analytics, explainable AI, and personalized decision support. The experience is designed to simplify complex market data into clear, trustworthy insights that help users evaluate vehicle value, compare similar vehicles, negotiate confidently, and determine the best time to buy.

My Role:

I led the design of an AI-powered platform from product strategy through execution with focuse on human-in-the-loop interactions, ML and predictive analytics to help users make confident, data-informed decisions.

Sole product designer 0→1 — Alina Baiko

Understanding Our Users

Personas synthesized from 12 customer interviews and dealership research:

Price-Conscious Buyer:
Wants clear, trustworthy guidance to determine whether a Porsche is fairly priced and whether she should buy now or wait.

‍Pain Points: She worries about overpaying, struggles to interpret market trends, and lacks confidence because pricing history and dealer behavior are not transparent.

Regional Shopper:
Wants to maximize value by identifying underpriced vehicles, tracking market opportunities, and using data-driven negotiation strategies.

Pain Points: He spends significant time monitoring listings across multiple sites, comparing dealerships, and manually tracking price changes to avoid missing the best deal.

Performance Enthusiast:
Wants advanced analytics and explainable AI that validate his own research with predictive pricing and transparent recommendations.
‍
Pain Points: Current automotive platforms lack predictive insights, require manual spreadsheet analysis, and provide black-box recommendations that are difficult to trust or verify.

Understanding the Problem

Design approach to identify key objectives and improvements:

Problem Statement

Current CPO marketplaces focus on inventory listings rather than informed decision-making, missing an opportunity to deliver greater value and differentiate the buying experience. Buyers need a trustworthy, AI-powered platform that transforms complex market data into clear, personalized insights, helping them evaluate vehicle value and identify the best time to buy.

Research Approach

Conducted qualitative interviews with Porsche CPO buyers to understand their buying behaviors, pain points, and trust in AI. Research insights directly informed the personas, product strategy, and AI-powered features designed to improve pricing transparency, purchase confidence, and decision-making.

Key Findings

Users wanted transparent, explainable AI that clearly showed the reasoning behind recommendations and helped them make informed decisions. They also valued predictive insights and personalized guidance to confidently evaluate vehicle value, determine the best time to buy, and negotiate with data-backed evidence.

Strategic Insight:

“Buyers were overwhelmed by fragmented listings and hidden dealer behaviors. They needed transparent, explainable insights to confidently validate their purchase decisions.”

Product Capability Framework

Based on the research, I defined three core product capabilities that address the biggest sources of buyer uncertainty. These capabilities defined what the product needed to do. The next challenge was designing AI interactions that buyers could actually understand and trust.

Designing & Calibrating AI

AI Fair Market Pricing: Predicts fair vehicle value using market data and comparable vehicles.

Buy Now vs. Wait Predictions: Forecasts price drops and market trends to recommend the optimal purchase timing.

Smart Vehicle Comparison: Aggregates and normalizes listings across dealerships for easy side-by-side comparison.

Negotiation Intelligence: Provides data-driven negotiation strategies based on dealer behavior and historical pricing.

Explainable AI: Makes recommendations transparent by showing the data and reasoning behind each insight.

Personalized Recommendations: Adapts insights, alerts, and guidance based on each buyer's preferences and goals.

Designing Around Model Capabilities:

The predictive experience uses supervised, tree-based models trained on historical listing outcomes, allowing the system to generate probabilistic recommendations while identifying the factors that contributed most to each prediction. This supported explainable insights around days on market, prior price changes, dealer behavior, and comparable vehicles.

‍Confidence indicators were tied to calibrated model probabilities rather than presented as arbitrary scores. Different capabilities also used different approaches: comparable vehicles relied on similarity matching, while negotiation guidance remained rule-based because reliable negotiated-sale labels were unavailable. Predictions that did not meet a useful performance threshold were intentionally excluded from the experience.

Designed to Empower

Through predictive analytics, explainable AI, and personalized recommendations, users can confidently evaluate vehicle value, compare options, determine the best time to buy, and negotiate with data-backed evidence rather than guesswork.

Designed for Explainability & Trust

A major finding from the user interviews is that buyers do not simply need more information: they need to trust it enough to act on it. Participants consistently expressed skepticism toward dealership pricing and AI-generated recommendations, particularly when they could not understand how conclusions were reached. Therefore, the design goal was not to maximize trust blindly, but to appropriately calibrate trust by helping users understand when the AI is likely to be reliable and when they should apply additional judgment.

Designed for Confidence

CPO Wizard provides confidence to buyers by transforming complex market data into clear, actionable insights. By combining predictive analytics, real-time market trends, dealer behavior, comparable vehicle analysis, and explainable AI, the platform helps users evaluate vehicle value, identify the best time to buy, compare options, and negotiate with confidence.

Designed to Transform CPO Vehicle Shopping

Platform transforms CPO vehicle shopping from a listing experience into an AI-powered decision support platform that helps buyers evaluate value, determine the best time to buy, compare vehicles, negotiate confidently, understand dealer behavior and trust AI recommendations through transparency and personalization.

Our Results

User testing validated that buyers preferred an AI-powered decision support experience over a traditional vehicle listing site. Features such as Fair Market Pricing, Buy Now vs. Wait predictions, Negotiation Intelligence, and Explainable AI increased users' confidence by helping them understand vehicle value, market trends, and the reasoning behind AI recommendations.

The research demonstrated that combining Predictive Analytics, Market Intelligence, and Transparent AI can reduce the time and effort required to research, compare, and negotiate CPO vehicles. It also reinforced the importance of personalized decision support, showing that buyers with different goals benefit from tailored insights and varying levels of explanation, transforming the experience from a transactional marketplace into a trusted decision-making platform.

Model validation: 2.4% average final-sale-price error · 0.87 AUC for price-cut prediction · predicted 58.9% vs. observed 58.5% price-cut rate over 30 days.

Testimonials

“

CPO Wizard is great work. Understanding the current market and fair pricing is a big pain point for our customers. I’m sure this will help some and it’s a great addition to the tools available to them. We came across CPO wizard while preparing a benchmarking study, because many marketplaces provide „fair price estimates“ - but customers never trusted ours as the official OEM. Let’s see what a solution will be that’s trusted by the customers and supported by our dealers. Keep up the great work!

— UX Manager for finder.porsche.com, Porsche AG

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