Jaguar/Land Rover New York Metro AI Visibility Index
Comparing 28 Jaguar/Land Rover dealerships on how well AI models can discover and recommend them
Last updated: 2026-03-02
View on Map →How to Read This Index
Strong AI visibility — AI models can easily discover and accurately represent this dealer
Moderate visibility — some information is accessible but key details may be missed
Weak visibility — AI can find this dealer but struggles to accurately represent them
Limited visibility — significant gaps make it hard for AI to recommend this dealer
| Rank | Dealer Name |
|---|---|
| #1 | Land Rover New Rochelle |
| #2 | Land Rover White Plains |
| #3 | White Plains Jaguar |
| #4 | Land Rover Mt. Kisco |
| #5 | Land Rover Paramus |
| #6 | Land Rover Huntington |
| #7 | Land Rover Englewood |
| #8 | Land Rover Monmouth |
| #9 | Land Rover Marlboro |
| #10 | Land Rover Darien |
| #11 | Jaguar Glen Cove |
| #12 | Jaguar Parsippany |
| #13 | Jaguar Huntington |
| #14 | Land Rover Parsippany |
| #15 | Jaguar Brooklyn |
| #16 | Land Rover Princeton |
| #17 | Jaguar at Manhattan |
| #18 | Jaguar Marlboro |
| #19 | Land Rover Brooklyn - Land Rover Dealer |
| #20 | Land Rover Nyack |
| #21 | Land Rover Manhattan |
| #22 | Land Rover Freeport |
| #23 | Land Rover Glen Cove |
| #24 | Ray Catena Land Rover Edison |
| #25 | Ray Catena Jaguar of Edison |
| #26 | Jaguar Parsippany |
| #27 | Jaguar Monmouth |
| #28 | Jaguar Freeport |
Methodology
AI visibility scores measure how well a dealership website can be discovered and understood by AI models like ChatGPT, Claude, and Perplexity. We analyze four key dimensions:
- Discoverability: Can AI systems find your website?
- Content Quality: Does AI understand what your dealership offers?
- Technical Health: Does your website work well with AI systems?
- Information Currency: Is your online information up to date?
- Agent Readiness: Can AI assistants take actions for your customers?
Scores range from 0-100, with higher scores indicating better AI visibility. This index is updated monthly to track improvements and changes across the cohort.
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