When a shopper asks ChatGPT to recommend a dealership or find a vehicle, what influences the answer? Wikimotive’s early research puts common AI optimization claims to the test.
In the second installment of State of AI Search, Wikimotive Co-founder and CEO Zach Billings introduces findings from an ongoing dealership AI Visibility Study. The research tracks brand, dealer, and inventory discovery prompts, collecting more than 5,000 data points per dealership each month to examine the characteristics of prominent results.
Watch the June briefing to explore the roles of customer reviews, website content, inventory, and third-party marketplaces—and learn why relevant, location-specific prompt tracking provides more useful context than a generic AI visibility score.
What the Early Research Revealed
- Different questions require different analysis. Questions about a named dealership reveal its online reputation. Dealer-discovery prompts reveal which stores get recommended, while inventory prompts reveal where AI directs shoppers looking for vehicles.
- Reviews strongly shaped dealership recommendations. In the observed “best dealer” results, customer feedback stood out more than dealerships’ own claims about their businesses.
- Content was common among cited inventory pages. Of the dealership pages appearing in inventory-discovery results, 90% contained written content, while 70% contained inventory.
- Third-party marketplaces were prominent. Slightly more than half of the observed inventory-discovery results came from third-party listing sites. Zach explains why that finding alone does not justify additional spending.
- Technical differences did not establish a clear advantage. Early observations did not identify a consistent preference for a particular website platform or specialized schema type. Accurate information remained an important baseline.
- Tracking needed local context. The study also surfaced out-of-state inventory and other inconsistencies, prompting further testing of both AI responses and the tracking environment.
Live Q&A: Measuring What Matters
The session addresses how dealers should evaluate vendor-provided AI visibility reports and what to ask before treating a low score as a business problem.
Zach also explores how dealership recommendations can influence a shopper’s consideration set without producing a direct click—and why reputation and carefully selected prompts matter when evaluating that visibility.
About the Research
These are early findings from Wikimotive’s ongoing AI Visibility Study, reflecting the data available for the June 2026 briefing. The study examines patterns in observed results rather than establishing universal ranking rules. Further testing is planned across additional makes, markets, content characteristics, and tracking environments.
Keep Following the Research
State of AI Search brings dealership decision-makers ongoing research and practical observations about AI, organic search, and paid search—with a focus on meaningful opportunities to sell and service vehicles.
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