Growing AI Search Visibility for a National Used Car Retailer

Challenge

A national used car retailer depended on its own name in both organic search and AI search. Organic visibility leaned heavily on branded searches, which limited reach to shoppers who already knew the brand. AI search platforms recognized the retailer when a shopper asked for it by name, and rarely surfaced it when a shopper described what they wanted to buy.

An AI visibility audit put a number on the gap.

• Branded promptsThe shopper names the retailer91%
• Discovery promptsThe shopper describes what they want to buy3.4%

AI platforms cited the retailer for shoppers who asked for it by name, and rarely for shoppers who were deciding what to buy.

The goal was to expand non-branded visibility by strengthening the inventory pages shoppers use while they are deciding what to buy and where to buy it.

Solution

I led the Answer Engine Optimization (AEO) work on 35 priority make and model inventory pages inside the used car folder. AEO is the practice of structuring a page so AI platforms can retrieve it and cite it as a source in their answers.

• Used keyword, prompt, and AI Overview data (the AI-written summaries Google shows above some results) to identify the questions shoppers were asking at each stage of the decision.
• Built repeatable page structures with concise copy, bullets, numbered lists, tables, and FAQs, formatted so search engines and AI platforms can both parse and cite them.
• Added internal links to the relevant make, model, and deeper inventory pages.
• Used AI to scale the work across the full page set while holding to brand standards and to SEO.

Five pages went live in April and the remaining 30 in July. Most of the set had less than two months to mature before the measurement window closed.

Outcome

33 of the 35 optimized pages earned new AI citations. Across the program there were 171 net-new AI responses citing the retailer, and 78% of them pointed at the optimized pages. 135 of the 171 came from non-branded prompts, where the audit had found the gap.

Traditional search results improved too. Top 3 non-branded rankings grew from 5 to 25, placements in Google’s AI Overviews grew from 4 to 28, and 30 of the 35 pages improved their average position.

AI referral traffic to the optimized inventory section grew 352% year over year, and those visitors went on from the landing page into the inventory.

• Top 3 non-branded rankings

  Before

  5

  After

  25

  5x

• AI Overview placements

  Before

  4

  After

  28

  7x

• Vehicle detail views from AI visitors

  Before

  254

  After

  1,070

  4x

• Test drives scheduled

  Before

  2

  After

  15

  8x

Year over year, April through August. Each pair has its own scale, set by its after value. Compare bar lengths within a metric.

Vehicle detail page views from AI visitors landing on these pages grew from 254 to 1,070. Scheduled test drives from the same sessions grew from 2 to 15.

Every figure here is scoped to the optimized inventory section, so the growth is attributable to this work. The results cover the first five months and are an early read. Work like this usually matures at six to eight months.