VEHICLEAI
NEON by Vehicle AI · Use Case · Listing Quality Audit

Find the listings costing you traffic.Before customers do.

Vehicle AI scores every VDP on photo quality, description completeness, pricing transparency, and merchandising overlays — then tells you which listings to fix first, ranked by traffic impact.

The Problem

Half your inventory has weak listings. You don't know which half.

Buyers shop your VDPs before they shop your lot. A 6-photo Murano with no description and pricing inconsistency loses to your competitor's 24-photo Murano with a clean writeup — every time, regardless of which one is the better car.

Your merchandising team can't fix every listing every week. They need a triage: which 5 listings are losing the most traffic, and what specifically needs to change? Vehicle AI runs the audit weekly, scores every VDP, and surfaces the underperformers with the specific issue called out.

How Vehicle AI Solves It

From signalto action.

Step 1

Every VDP gets a weekly quality score.

Photo count vs. segment average. Stock-photo detection. Description completeness. Pricing transparency. Merchandising overlay presence (price-drop badges, certified pre-owned callouts). Score 0-100, distributed across Best-in-Class / Strong / Average / Failed tiers.

VDP Quality Audit · 47 used listings
Quality tier distribution
Best-in-Class(85-100)
2 · 5.4%
Strong(70-84)
32 · 86.5%
Average(50-69)
3 · 8.1%
Failed(<50)
0 · 0%
Underperformers · fix first
2026 Murano SL
5N1AZ3CS6...
Stock photo · 8 photos vs 24 segment avg
59
2026 Frontier PRO-4X
1N6ED1EK8...
No description · pricing inconsistency vs comps
62
2026 Kicks SV AWD
3N8AP6CB5...
Hero photo missing · 6 photos total
64
Step 2

Underperformers surface with the specific issue.

"This Murano has 8 photos vs. 24 segment average." "This Frontier has no description." "This Kicks has pricing inconsistency vs. comparable trims." Not vague — specific.

Step 3

Approved fixes go to your merchandising team as work tickets.

Your team reviews the list. Approved tickets get assigned (photographer for photo gaps, copywriter for description gaps, manager review for pricing inconsistency). Completion gets tracked.

Step 4

Ask the chat for any merchandising question.

"Which vehicles in our inventory have the weakest listings?" "How does our photo count compare to the closest Toyota stores?" "Which listings should we fix this week to maximize traffic?"

Chat

analyze the price to market of all of my used inventory. where are my biggest opportunities for improvement?

Used Inventory P2M Distribution
LowIn-LineHighNo Data

47 active used units. Three distinct areas of opportunity: 12 underpriced units could capture margin, 10 overpriced units risk aging.

Manager Controls

Your team approves everything.

  • Set scoring weights for your store (photo-heavy vs. description-heavy)
  • Configure photo count thresholds per segment
  • Approve every work ticket before it goes to the merchandising team
  • Audit log: completion tracked per VIN, per issue
Data Sources

Everything traceable to its source.

  • Your VDP merchandising data (photos, descriptions, overlays, pricing)
  • Segment benchmarks computed from MarketCheck and marketplace data
  • Stock-photo detection via image analysis
  • Your dealer-set merchandising standards
Metrics This Moves

What your team should expect to see.

Average VDP Score

Store-wide quality score across all active listings.

Underperformer Count

Listings scoring below your store threshold (typically 70).

Time-to-Fix

Days from underperformer flag to merchandising fix complete.

Book a Demo

See your worst-performing listings this week.

No commitment · We do the setup · Your data stays yours