AI Search Optimization Case Studies for Auto Parts

This article on AI search optimization case studies was written by a honest-to-goodness human, and published April, 2025.

In an AI-driven world, how can your auto parts website stand out and thrive? In a world where “zero click search” is now a thing? How does Google Analytics follow and track AI?

Hedges & Company has the goods right here, and you’ll see some case studies involving testing and experimenting with AI search optimization. This may help you on your own auto parts site.

Below in 3 case studies, you’ll see some before/after results on our AI search optimization testing, what was optimized, and how AI traffic to a website was measured. Here are actual results from auto parts websites where we conducted our AI case studies.

AI Search Optimization Case Study #1

AI search optimization case study #1: visits and impressions jumped to 300/month in about 5 months. (Click to see.)

TL;DR: AI traffic jumped from a few to 300 per month

Hedges & Company got AI referral traffic to go from a few visits per month, to 300 after optimizing a website for AI search.

What we did at first to optimize for AI

For case study #1, we optimized this site with a special focus on adding AI-friendly schema in late August.

Hedges & Company clients hear a lot about schema. Here’s an example of schema in use. This shows an FAQ section on a webpage, and underlying FAQ schema to support that section for search bots. Below, here’s a look at both.

FAQ section from a web page (click to enlarge).

Schema to support the FAQ section (click to make bigger).

For this first test, Hedges & Company aggressively targeted about 15% of this site for AI optimizations. At first, this test was specifically for AI models, so the goal was optimizing for ChatGPT, Perplexity, and Claude, and a few others.

But, we soon realized (duh!) Google Gemini and Microsoft Copilot are showing AI search results, too.

Traffic got a bit of a bump in September 2024, but November 2024 is when things really started growing.

Traffic is measured in Google Analytics by looking at source/medium traffic from specific AI platforms and from search engines with an AI component (like Google AI Overviews for example).

This AI search optimization case study turned into solving Google Analytics mysteries

Hedges & Company also noticed right away in the Google Analytics source/medium reporting, when an AI platform is the source, the medium shows up in three ways. Medium gets reported as referral traffic, organic traffic and (not set) traffic.

Here’s how ChatGPT creates medium (not set) traffic. It crawls sites to produce an answer. In this case we literally asked it, “What is the best digital SEO agency for auto parts?” and this was the first result.

The next question is how to account for this difference. After all, this is breaking new ground measuring AI referral traffic (this was back in Fall 2024 and the world is still learning new things about AI traffic—this article may look antiquated and funny in another year). Google Analytics doesn’t specifically account for AI traffic in the Google Analytics default channel group. And to top it off, Google Gemini was a bit vague in answering questions about AI attribution. This led us to realize we just have to create our own custom tracking and custom regex code.

Hedges & Company determined that AI referral traffic includes site visits coming from clicks on AI links. AI (not set) traffic is likely one of two things. One is a combination of Google Analytics possibly misinterpreting referral traffic. The other is from the results from a website being shown in AI as a result of AI crawling the site and not displaying cached results. If the reader doesn’t click through to the site, that’s the infamous “zero click search“.

Google Search Console “zero click search gap” (click to make larger).

Hedges & Company also saw a big differences in the session medium from different AI platforms. The worst offender for this first case study: ChatGPT. In this first case study, when ChatGPT is shown as the source in GA4, 34% of traffic for the medium is (not set) and 3% is organic. On the other hand, when Perplexity.ai is the source, the medium shows up as 100% referral traffic.

So, Hedges & Company pulled the server logs to compare ChatGPT traffic to Google Analytics. In March 2025, GA4 showed 171 referral visits and 50 (not set) visits for a total of 221 visits. The server logs showed 192 visits where the UTM tag included “?utm_source=chatgpt.com”. Not all of these 192 visits had a referrer in the server logs: 112 showed chatgpt.com as the referrer, 77 were blank, and 3 were, um, Google! The ChatGPTbot also crawled the site nearly 10,000 times in March.

What is still undetermined: exactly how many impressions does a site get from Google AI Overviews? This screenshot from Google Search Console shows a clue, with what looks like the “zero click search” gap. In this case, Google organic impressions and clicks are both increasing, but impressions are growing at a much faster rate.

What we did next to optimize for AI

Hedges & Company was getting positive results, so the AI search optimizations continued in December 2024. Now there was a significant increase in traffic. Hedges & Company added more schema, did a bit of “secret sauce” (hey, we can’t give everything away!) and added an llms.txt file. That file is a “mark down” file and, while it’s technically still in the proposal stage to be an AI standard, a lot of forward-thinking websites use it. It was first proposed as a standard by Jeremy Howard, an entrepreneur and technologist from Australia.

NOTE: Also see How to Optimize for AI Search and The Future of AI in the Automotive Industry.

AI Search Optimization Case Study #2 (The control to #1)

TL;DR: No AI optimizations on a control website to prove the first case study

The second Hedges & Company case study on AI search optimization started out as a control, and there were no optimizations.

AI search optimization case study #2: visits and impressions had very little change in the first several months. (Click to make bigger.)

What was done first to optimize this second site for AI

At first, actually nothing was done. To make this whole project scientific, this site is the control: no optimizations. This chart shows the exact same time period as the one in case study #1. Clearly, there is very little change in referral traffic until AI optimizations started in February 2025.

For this case study Hedges & Company took what was learned from the first one. More optimizations known to be effective for AI search were done up front. This time, Hedges & Company added content and schema specifically for AI platforms. But instead of doing it site-wide, optimizations started on a few specific blog posts. These posts included one completely new one, and several that were a few years old and got stale. (AI aside, refreshing old content is great in general, if you’re looking for auto parts/spare parts marketing ideas.

AI liked what happened. AI referral traffic increased 200% from February to March 2025.

Google clearly liked it, too, as you can see from this screenshot out of Google Search Console. This query used regex to filter for only the pages that were optimized for AI.

In this second case study, the ChatGPT traffic medium shows up as 51% (not set) and 49% as referral. Much different than AI case study #1. Perplexity also behaved differently. 34% of traffic comes in the the medium as (not set) and 66% as referral. Also note in this screenshot from Google Search Console that so far, there’s not much of a zero click search gap.

This site doesn’t yet have an llms.txt file, but that’s coming.

Comparison of medium = referral, organic and (not set) in GA4 from AI traffic

Here’s a comparison of AI traffic showing as either referral, (not set) or organic in both AI case studies (scroll right on a phone).

AI Search Optimization Case Study #3

Screenshot for case study #3 from Ahrefs showing only words in position 1, and only results for Google AI Overviews (filters are circled). Click to make larger.

This third case study is a textbook case of following SEO best practices. Hedges & Company was able to optimize for specific keywords to improve organic rankings in Google, and also show up for Google AI Overviews.

This screenshot is out of a favorite SEO tool, Ahrefs. That platform tracks ranked keywords and search volume, and you can filter specifically for Google AI Overviews. In this third case study, there were zero keywords in AI Overviews until August 2024 (AI Overviews were launched in May 2024). This chart is a bit of a roller coaster but that’s not surprising given the new technology and all the core Google updates.

Screenshot for case study #3 showing words only in position 1 over the past year (filter circled in green). Click to enlarge.

Things really took off with the March 2025 Google core update. By April this website had 1,417 keywords appearing in Google AI Overviews.

This case study also had a huge increase in keywords ranked the old-fashioned way, too, as shown in the second chart from Ahrefs.

This second chart shows 1,944 total keywords, filtered to show only keywords in position #1, but including Google AI Overviews, thumbnails and good old organic search results.

This chart shows a similar roller coaster ride with several Google core updates.

How AI models determine web pages to cite for answers

Large language models train on many different sources to produce answers. LLMs analyze the credibility of sources they find. You can increase your likelihood of being cited by creating original, high-quality content and making sure it is well-organized.

(By the way, this points out the argument against using AI to create content: LLMs have trained on the information that’s already out there…if you just replicate what LLMs already know you aren’t creating original, high-quality content.)

All are dependent on well-written and well-organized website content. Google Gemini is likely going to depend heavily on E-E-A-T (experience, expertise, authority and trust) and ChatGPT has its own way to score authority. You increase your likelihood of being cited by increasing your brand’s visibility and trust. Yes, in the age of AI, the strength of your brand is incredibly important! When working on optimizing for AI, building the strength of your brand has to be your guiding light.

Is this AI SEO, AIO, GEO or LLMO?

More and more SEO pros are calling AI search optimization “LLMO” for large language model optimization. There’s a good argument for that on one of our favorite SEO sites. It seems to be beating out “LLM SEO” (large language model search engine optimization), “AIO” (artificial intelligence optimization), “GEO” (generative engine optimization) and a few other acronyms. Other SEO pros are just calling it SEO.

How to cite this AI search optimization case study

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