Growing AI Search Visibility for a National Used Car Retailer

Challenge

A national used car retailer had two discoverability problems that turned out to be the same problem. Organic visibility leaned heavily on branded searches, which limited reach to shoppers who already knew the brand. AI platforms had the same blind spot. They recognized the retailer when a shopper asked for it by name, and rarely surfaced it when a shopper was describing 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%

The brand was the answer when someone asked for it, and rarely the answer when someone was still deciding.

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

Solution

I led the optimization of 35 priority make and model inventory pages inside the used car folder.

• Used keyword, prompt, and AI Overview data 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 SEO and brand standards.

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 citing responses, and 78% of them pointed at the optimized pages. 135 of those responses were non-branded, which is the exact gap the audit had found.

Traditional search moved with it. Top 3 non-branded placements grew from 5 to 25, AI Overview placements 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 the visitors it brought went deeper than the page they landed on.

• 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 is drawn against its own after value, so bar lengths compare within a metric and not between them.

Vehicle detail page views from AI visitors landing on these pages grew from 254 to 1,070, which means those visitors moved from the optimized pages into actual inventory rather than stopping at the article. Scheduled test drives from the same sessions grew from 2 to 15.

Every figure here is scoped to the optimized inventory section rather than the site as a whole, so the growth is attributable to this work.

These results cover the first five months. Work like this usually matures at six to eight months, so the figures above are an early read rather than a finished one.