Investors
Fleet selection at Provenance is not judgment. It is methodology. A proprietary filtering and scoring model — built on data science, deep automotive expertise, and access to leading industry sources — eliminates 95% of candidates before a single acquisition decision is made. What remains is ranked, not just approved.
The screening standard
Initial filtering applies economics, residual profile, and quality history. Vehicles that pass are scored across 25 sub-dimensions in five pillars. The result is a ranked fleet — where position reflects genuine, quantified advantage across subscriber desirability and long-term asset economics.
What makes it proprietary
Standard automotive data — ALG, Black Book, Manheim — optimizes for residual value and transaction pricing. None attempt to score subscriber-facing desirability. The PVI fills that gap with 25 dimensions including exhaust note, driver engagement, rarity on local roads, and known issue propensity by engine and trim — none of which appear in any standard model.
TCO intelligence
True Cost of Ownership scoring goes beyond depreciation. We cross-reference model-year and trim-specific service histories, engine-known failure points, TSB and recall records, enthusiast forum intelligence, and real ownership data — then score each candidate against the cost of delivering subscriber value. Broad brand averages hide the variance. We score the specific vehicle.
The compounding advantage
Pillar V — Member Signal — captures live subscriber ratings, post-drive feedback, and waitlist demand pressure. As member interactions accumulate, this pillar enriches every composite score with behavioral data no competitor can replicate without the same subscriber base. The longer Provenance operates, the sharper the acquisition intelligence becomes.
95%
Elimination rate
The vast majority of candidates are filtered out before scoring begins.
25+
Scored dimensions
Sub-dimension weights calibrated by pillar, applied consistently across every candidate.
∞
Improves with scale
Member Signal data enriches every score automatically as the subscriber base grows.
Discover — the engagement and data flywheel
Tool 01 — Name the Model Year
Weekly rotating vehicles, a live leaderboard, and a score that resets every Monday create a genuine reason to return before anyone has committed to a subscription. Every play session reinforces the core insight — model year is nearly invisible on a well-maintained exotic — and every registration converts a curious visitor into a named, opted-in contact on the waitlist. The game does not entertain. It converts.
Tool 02 — TCO Calculator
A visitor who selects their own vehicle and watches the true all-in monthly emerge — with dealer fees, doc fees, down payment amortized, and every asterisk surfaced — has done the math themselves. We don't claim Provenance is better value. We show it, using their own numbers. The moment the Provenance alternative appears alongside, the sale is largely made. No sales team required.
Tool 03 — Garage Recommender
The recommender collects something no standard automotive data model has: individual aesthetic preference at scale. Sound profile, design language, brand affinity ranking, driving character, presence — all subjective, all personally meaningful, all invisible in residual value tables. A member who matched to their vehicle through the recommender arrives at the subscription already attached. Attachment reduces early swap behavior, lowers churn, and extends average hold duration.
The data layer
Slider positions, brand rankings, and scenario choices feed directly into the Member Signal pillar of the Perceived Value Index. Aggregate preference patterns reveal which attributes drive desirability by market, season, and demographic — intelligence that sharpens fleet acquisition decisions over time. A competitor can build a similar interface. They cannot replicate the dataset that accumulates behind it without the same user base.
Together the three Discover tools form a self-reinforcing loop. The game builds the contact list. The calculator proves the value proposition. The recommender converts interest into a specific vehicle attachment — the last step before a subscription. Each tool feeds preference data back into the PVI. The longer they run, the smarter the entire platform becomes. No competitor can replicate this without the same user base, the same fleet intelligence, and the same willingness to build the category from scratch.
Investor inquiry
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